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Robotics, Volume 11, Issue 5 (October 2022) – 32 articles

Cover Story (view full-size image): In space applications, the use of lightweight and deployable robotic systems is an advantage in terms of costs. In this work, POPUP robot is introduced: a manipulator with inflatable links that can be stored into a relatively small volume and deployed when required. Its architecture aims to match the benefits of rigid robots and the features of having light and deployable parts, ensuring simple control, low energy consumption and low compressed gas requirement. The first robot prototype is described highlighting the design criteria and the effect of internal pressure on the performances. A pseudo-rigid body model is developed looking towards control design. Finally, multi-body simulations are performed to test control strategies and validate a visual servoing solution. View this paper
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20 pages, 6337 KiB  
Technical Note
Trajectory Control of An Articulated Robot Based on Direct Reinforcement Learning
by Chia-Hao Tsai, Jun-Ji Lin, Teng-Feng Hsieh and Jia-Yush Yen
Robotics 2022, 11(5), 116; https://doi.org/10.3390/robotics11050116 - 20 Oct 2022
Cited by 3 | Viewed by 2162
Abstract
Reinforcement Learning (RL) is gaining much research attention because it allows the system to learn from interacting with the environment. Yet, with all these successful applications, the application of RL in direct joint torque control without the help of an underlining dynamic model [...] Read more.
Reinforcement Learning (RL) is gaining much research attention because it allows the system to learn from interacting with the environment. Yet, with all these successful applications, the application of RL in direct joint torque control without the help of an underlining dynamic model is not reported in the literature. This study presents a split network structure that enables successful training of RL to learn the direct torque control for trajectory following a six-axis articulated robot without prior knowledge of the dynamic robot model. The training took a very long time to converge. However, we were able to show the successful control of four different trajectories without needing an accurate dynamics model and complex inverse kinematics computation. To show the RL-based control’s effectiveness, we also compare the RL control with the Model Predictive Control (MPC), another popular trajectory control method. Our results show that while the MPC achieves smoother and more accurate control, it does not automatically treat the singularity. In addition, it requires complex inverse dynamics calculations. On the other hand, the RL controller instinctively avoided the violent action around the singularities. Full article
(This article belongs to the Section Industrial Robots and Automation)
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12 pages, 2462 KiB  
Article
An Educational Test Rig for Kinesthetic Learning of Mechanisms for Underactuated Robotic Hands
by Gabriele Maria Achilli, Silvia Logozzo and Maria Cristina Valigi
Robotics 2022, 11(5), 115; https://doi.org/10.3390/robotics11050115 - 19 Oct 2022
Cited by 2 | Viewed by 1856
Abstract
Teaching robotics requires interdisciplinary skills and a good creativity, providing instructions and hands-on experiences, exploiting different kinds of learning. Two kinds of learning methods are commonly used: the ‘visual learning’ and the ‘auditory learning’, recognizable by the preference of an approach for images, [...] Read more.
Teaching robotics requires interdisciplinary skills and a good creativity, providing instructions and hands-on experiences, exploiting different kinds of learning. Two kinds of learning methods are commonly used: the ‘visual learning’ and the ‘auditory learning’, recognizable by the preference of an approach for images, rather than for texts, or oral explanations. A third possible learning style is the ‘kinesthetic learning’, based on tactile activities, which is generally least exploited, both by teachers in the classroom and by students during individual study. In this perspective, the use of educational test rigs is a good practice and adds an opportunity to share a passion for robotics. The paper focuses on the realization and application of an educational test rig aimed at explaining how a differential mechanism works and how it can be applied to robotic underactuated soft grippers to move multiple robotic fingers independently of each other using just a single actuator. The differential test bench was realized by 3D printing and mounted with the help of students in high school seminaries oriented to encourage students towards robotic or mechatronic studies. This activity was very thrilling for the students and helped them to approach robotics in a natural way, exploiting kinesthetic learning as it is demonstrated by test results. Full article
(This article belongs to the Special Issue Advances and Challenges in Educational Robotics II)
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24 pages, 6361 KiB  
Article
Benchmarking Dynamic Balancing Controllers for Humanoid Robots
by Juan A. Castano, Joseph Humphreys, Enrico Mingo Hoffman, Noelia Fernández Talavera, Maria Cristina Rodriguez Sanchez and Chengxu Zhou
Robotics 2022, 11(5), 114; https://doi.org/10.3390/robotics11050114 - 19 Oct 2022
Cited by 2 | Viewed by 2567
Abstract
This paper presents a comparison study of three control design approaches for humanoid balancing based on the Center of Mass (CoM) stabilization and body posture adjustment. The comparison was carried out under controlled circumstances allowing other researchers to replicate [...] Read more.
This paper presents a comparison study of three control design approaches for humanoid balancing based on the Center of Mass (CoM) stabilization and body posture adjustment. The comparison was carried out under controlled circumstances allowing other researchers to replicate and compare our results with their own. The feedback control from state space design is based on simple models and provides sufficient robustness to control complex and high Degrees of Freedom (DoFs) systems, such as humanoids. The implemented strategies allow compliant behavior of the robot in reaction to impulsive or periodical disturbances, resulting in a smooth and human-like response while considering constraints. In this respect, we implemented two balancing strategies to compensate for the CoM deviation. The first one uses the robot’s capture point as a stability principle and the second one uses the Force/Torque sensors at the ankles to define a CoM reference that stabilizes the robot. In addition, was implemented a third strategy based on upper body orientation to absorb external disturbances and counterbalance them. Even though the balancing strategies are implemented independently, they can be merged to further increase balancing performance. The proposed strategies were previously applied on different humanoid bipedal platforms, however, their performance could not be properly benchmarked before. With this concern, this paper focuses on benchmarking in controlled scenarios to help the community in comparing different balance techniques. The key performance indicators (KPIs) used in our comparison are the CoM deviation, the settling time, the maximum measured orientation, passive gait measure, measured ankles torques, and reconstructed Center of Pressure (CoP). The benchmarking experiments were carried out in simulations and using the facility at Istituto Italiano di Tecnologia on the REEM-C humanoid robot provided by PAL robotics inside the EU H2020 project EUROBENCH framework. Full article
(This article belongs to the Special Issue Legged Robots into the Real World)
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24 pages, 3449 KiB  
Article
Digital Twin as Industrial Robots Manipulation Validation Tool
by Vladimir Kuts, Jeremy A. Marvel, Murat Aksu, Simone L. Pizzagalli, Martinš Sarkans, Yevhen Bondarenko and Tauno Otto
Robotics 2022, 11(5), 113; https://doi.org/10.3390/robotics11050113 - 18 Oct 2022
Cited by 7 | Viewed by 2889
Abstract
The adoption of Digital Twin (DT) solutions for industrial purposes is increasing among small- and medium-sized enterprises and is already being integrated into many large-scale companies. As there is an increasing need for faster production and shortening of the learning curve for new [...] Read more.
The adoption of Digital Twin (DT) solutions for industrial purposes is increasing among small- and medium-sized enterprises and is already being integrated into many large-scale companies. As there is an increasing need for faster production and shortening of the learning curve for new emerging technologies, Virtual Reality (VR) interfaces for enterprise manufacturing DTs seem to be a good solution. Furthermore, with the emergence of Industry 5.0 (I5.0) paradigm, human operators will be increasingly integrated in the systems interfaces though advanced interactions, pervasive sensors, real time tracking and data acquisition. This scenario is especially relevant in collaborative automated systems where the introduction of immersive VR interfaces based on production cell DTs might provide a solution for the integration of the human factors in the modern industrial scenarios. This study presents experimental results of the comparison between users controlling a physical industrial robot system via a traditional teach pendant and a DT leveraging a VR user interface. The study group involves forty subjects including experts in robotics and VR as well as non-experts. An analysis of the data gathered in both the real and the virtual use case scenario is provided. The collected information includes time for performing a task with an industrial robot, stress level evaluation, physical and mental effort, and the human subjects’ perceptions of the physical and simulated robots. Additionally, operator gazes were tracked in the VR environment. In this study, VR interfaces in the DT representation are exploited to gather user centered metrics and validate efficiency and safety standards for modern collaborative industrial systems in I5.0. The goal is to evaluate how the operators perceive and respond to the virtual robot and user interface while interacting with them and detect if any degradation of user experience and task efficiency exists compared to the real robot interfaces. Results demonstrate that the use of DT VR interfaces is comparable to traditional tech pendants for the given task and might be a valuable substitute of physical interfaces. Despite improving the overall task performance and considering the higher stress levels detected while using the DT VR interface, further studies are necessary to provide a clearer validation of both interfaces and user impact assessment methods. Full article
(This article belongs to the Special Issue Human Factors in Human–Robot Interaction)
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24 pages, 1999 KiB  
Article
I Let Go Now! Towards a Voice-User Interface for Handovers between Robots and Users with Full and Impaired Sight
by Dorothea Langer, Franziska Legler, Philipp Kotsch, André Dettmann and Angelika C. Bullinger
Robotics 2022, 11(5), 112; https://doi.org/10.3390/robotics11050112 - 15 Oct 2022
Cited by 3 | Viewed by 1992
Abstract
Handing over objects is a collaborative task that requires participants to synchronize their actions in terms of space and time, as well as their adherence to social standards. If one participant is a social robot and the other a visually impaired human, actions [...] Read more.
Handing over objects is a collaborative task that requires participants to synchronize their actions in terms of space and time, as well as their adherence to social standards. If one participant is a social robot and the other a visually impaired human, actions should favorably be coordinated by voice. User requirements for such a Voice-User Interface (VUI), as well as its required structure and content, are unknown so far. In our study, we applied the user-centered design process to develop a VUI for visually impaired humans and humans with full sight. Iterative development was conducted with interviews, workshops, and user tests to derive VUI requirements, dialog structure, and content. A final VUI prototype was evaluated in a standardized experiment with 60 subjects who were visually impaired or fully sighted. Results show that the VUI enabled all subjects to successfully receive objects with an error rate of only 1.8%. Likeability and accuracy were evaluated best, while habitability and speed of interaction were shown to need improvement. Qualitative feedback supported and detailed results, e.g., how to shorten some dialogs. To conclude, we recommend that inclusive VUI design for social robots should give precise information for handover processes and pay attention to social manners. Full article
(This article belongs to the Special Issue Communication with Social Robots)
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29 pages, 16763 KiB  
Article
Robust Prescribed Trajectory Tracking Control of a Robot Manipulator Using Adaptive Finite-Time Sliding Mode and Extreme Learning Machine Method
by Mona Raoufi, Hamed Habibi, Amirmehdi Yazdani and Hai Wang
Robotics 2022, 11(5), 111; https://doi.org/10.3390/robotics11050111 - 15 Oct 2022
Cited by 4 | Viewed by 2349
Abstract
This study aims to provide a robust trajectory tracking controller which guarantees the prescribed performance of a robot manipulator, both in transient and steady-state modes, experiencing parametric uncertainties. The main core of the controller is designed based on the adaptive finite-time sliding mode [...] Read more.
This study aims to provide a robust trajectory tracking controller which guarantees the prescribed performance of a robot manipulator, both in transient and steady-state modes, experiencing parametric uncertainties. The main core of the controller is designed based on the adaptive finite-time sliding mode control (SMC) and extreme learning machine (ELM) methods to collectively estimate the parametric model uncertainties and enhance the quality of tracking performance. Accordingly, the global estimation with a fast convergence rate is achieved while the tracking error and the impact of chattering on the control input are mitigated significantly. Following the control design, the stability of the overall control system along with the finite-time convergence rate is proved, and the effectiveness of the proposed method is investigated via extensive simulation studies. The results of simulations confirm that the prescribed transient and steady-state performances are obtained with enough accuracy, fast convergence rate, robustness, and smooth control input which are all required for practical implementation and applications. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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33 pages, 10546 KiB  
Article
A Reconfigurable Parallel Robot for On-Structure Machining of Large Structures
by Abdur Rosyid, Cesare Stefanini and Bashar El-Khasawneh
Robotics 2022, 11(5), 110; https://doi.org/10.3390/robotics11050110 - 14 Oct 2022
Cited by 3 | Viewed by 2542
Abstract
This paper presents a novel walking hybrid-kinematics robot that can be reconfigured to have three, five, and six degrees of freedom (DOFs) for adsorption machining of large structures. A symmetric 3PRPR or 3PRRR parallel mechanism with three translational (3T) DOFs is used to [...] Read more.
This paper presents a novel walking hybrid-kinematics robot that can be reconfigured to have three, five, and six degrees of freedom (DOFs) for adsorption machining of large structures. A symmetric 3PRPR or 3PRRR parallel mechanism with three translational (3T) DOFs is used to perform three-axis machining tasks. Three attachment pads connected to passive spherical joints are used to attach the robot to the surface of a large structure. Two or three rotational degrees of freedom can be added to the robot to adapt to a large structure’s irregular surface geometry and perform five- or six-axis machining tasks. This is achieved through modular reassembly or joint locking that reconfigures the robot from a three-DOF robot to a five- or six-DOF robot. A serial module providing two rotational DOFs can be added to the 3T parallel mechanism to provide five DOFs. A parallel module, namely 3SPR or 3SU mechanism, can be added to the 3T parallel mechanism to provide six DOFs. The mobility, pose kinematics, differential kinematics, singularities, and workspace of the 3SPR and 3SU parallel mechanisms alone and combined with the 3T mechanism are discussed in this paper. It is shown that the singularities of the mechanism can be easily avoided by making the moving platform of the 3SPR or 3SU mechanism smaller than the base, limiting the range of some joints, and having an appropriate length of the links. Furthermore, a method to optimize the workspace of the mechanism was also discussed. Full article
(This article belongs to the Special Issue Robotics and Parallel Kinematic Machines)
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15 pages, 11273 KiB  
Article
Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots
by Halil Ibrahim Ugurlu, Xuan Huy Pham and Erdal Kayacan
Robotics 2022, 11(5), 109; https://doi.org/10.3390/robotics11050109 - 13 Oct 2022
Cited by 6 | Viewed by 3129
Abstract
In this study, a novel end-to-end path planning algorithm based on deep reinforcement learning is proposed for aerial robots deployed in dense environments. The learning agent finds an obstacle-free way around the provided rough, global path by only depending on the observations from [...] Read more.
In this study, a novel end-to-end path planning algorithm based on deep reinforcement learning is proposed for aerial robots deployed in dense environments. The learning agent finds an obstacle-free way around the provided rough, global path by only depending on the observations from a forward-facing depth camera. A novel deep reinforcement learning framework is proposed to train the end-to-end policy with the capability of safely avoiding obstacles. The Webots open-source robot simulator is utilized for training the policy, introducing highly randomized environmental configurations for better generalization. The training is performed without dynamics calculations through randomized position updates to minimize the amount of data processed. The trained policy is first comprehensively evaluated in simulations involving physical dynamics and software-in-the-loop flight control. The proposed method is proven to have a 38% and 50% higher success rate compared to both deep reinforcement learning-based and artificial potential field-based baselines, respectively. The generalization capability of the method is verified in simulation-to-real transfer without further training. Real-time experiments are conducted with several trials in two different scenarios, showing a 50% higher success rate of the proposed method compared to the deep reinforcement learning-based baseline. Full article
(This article belongs to the Topic Safe and Secure Autonomous Systems)
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17 pages, 20371 KiB  
Article
Human-Centered Navigation and Person-Following with Omnidirectional Robot for Indoor Assistance and Monitoring
by Andrea Eirale, Mauro Martini and Marcello Chiaberge
Robotics 2022, 11(5), 108; https://doi.org/10.3390/robotics11050108 - 10 Oct 2022
Cited by 5 | Viewed by 2427
Abstract
Robot assistants and service robots are rapidly spreading out as cutting-edge automation solutions to support people in their everyday life in workplaces, health centers, and domestic environments. Moreover, the COVID-19 pandemic drastically increased the need for service technology to help medical personnel in [...] Read more.
Robot assistants and service robots are rapidly spreading out as cutting-edge automation solutions to support people in their everyday life in workplaces, health centers, and domestic environments. Moreover, the COVID-19 pandemic drastically increased the need for service technology to help medical personnel in critical conditions in hospitals and domestic scenarios. The first requirement for an assistive robot is to navigate and follow the user in dynamic environments in complete autonomy. However, these advanced multitask behaviors require flexible mobility of the platform to accurately avoid obstacles in cluttered spaces while tracking the user. This paper presents a novel human-centered navigation system that successfully combines a real-time visual perception system with the mobility advantages provided by an omnidirectional robotic platform to precisely adjust the robot orientation and monitor a person while navigating. Our extensive experimentation conducted in a representative indoor scenario demonstrates that our solution offers efficient and safe motion planning for person-following and, more generally, for human-centered navigation tasks. Full article
(This article belongs to the Special Issue Service Robotics against COVID-2019 Pandemic)
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18 pages, 13775 KiB  
Article
Design and Scaling of Exoskeleton Power Units Considering Load Cycles of Humans
by Marcel Waldhof, Isabell Wochner, Katrin Stollenmaier, Nejila Parspour and Syn Schmitt
Robotics 2022, 11(5), 107; https://doi.org/10.3390/robotics11050107 - 8 Oct 2022
Viewed by 1803
Abstract
Exoskeletons are powerful tools for aiding humans with pathological conditions, in dangerous environments or in manually exhausting tasks. Typically, they are designed for specific maximum scenarios without taking into account the diversity of tasks and the individuality of the user. To address this [...] Read more.
Exoskeletons are powerful tools for aiding humans with pathological conditions, in dangerous environments or in manually exhausting tasks. Typically, they are designed for specific maximum scenarios without taking into account the diversity of tasks and the individuality of the user. To address this discrepancy, a framework was developed for personalizing an exoskeleton by scaling the components, especially the electrical machine, based on different simulated human muscle forces. The main idea was to scale a numerical arm model based on body mass and height to predict different movements representing both manual labor and daily activities. The predicted torques necessary to produce these movements were then used to generate a load/performance cycle for the power unit design. Considering these torques, main operation points of this load cycle were defined and a reference power unit was scaled and optimized. Therefore, a scalability model for an electrical machine is introduced. This individual adaptation and scaling of the power unit for different users leads to a better performance and a lighter design. Full article
(This article belongs to the Special Issue Mechatronics Systems and Robots)
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16 pages, 875 KiB  
Article
When Robots Fail—A VR Investigation on Caregivers’ Tolerance towards Communication and Processing Failures
by Kim Klüber and Linda Onnasch
Robotics 2022, 11(5), 106; https://doi.org/10.3390/robotics11050106 - 7 Oct 2022
Cited by 2 | Viewed by 1965
Abstract
Robots are increasingly used in healthcare to support caregivers in their daily work routines. To ensure an effortless and easy interaction between caregivers and robots, communication via natural language is expected from robots. However, robotic speech bears a large potential for technical failures, [...] Read more.
Robots are increasingly used in healthcare to support caregivers in their daily work routines. To ensure an effortless and easy interaction between caregivers and robots, communication via natural language is expected from robots. However, robotic speech bears a large potential for technical failures, which includes processing and communication failures. It is therefore necessary to investigate how caregivers perceive and respond to robots with erroneous communication. We recruited thirty caregivers, who interacted in a virtual reality setting with a robot. It was investigated whether different kinds of failures are more likely to be forgiven with technical or human-like justifications. Furthermore, we determined how tolerant caregivers are with a robot constantly returning a process failure and whether this depends on the robot’s response pattern (constant vs. variable). Participants showed the same forgiveness towards the two justifications. However, females liked the human-like justification more and males liked the technical justification more. Providing justifications with any reasonable content seems sufficient to achieve positive effects. Robots with a constant response pattern were liked more, although both patterns achieved the same tolerance threshold from caregivers, which was around seven failed requests. Due to the experimental setup, the tolerance for communication failures was probably increased and should be adjusted in real-life situations. Full article
(This article belongs to the Special Issue Communication with Social Robots)
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21 pages, 30658 KiB  
Article
Kinematic Graph for Motion Planning of Robotic Manipulators
by Burkhard Corves and Amir Shahidi
Robotics 2022, 11(5), 105; https://doi.org/10.3390/robotics11050105 - 5 Oct 2022
Cited by 1 | Viewed by 2266
Abstract
We introduce a kinematic graph in this article. A kinematic graph results from structuring the data obtained from the sampling method for sampling-based motion planning algorithms in robotics with the motivation to adapt the method to the positioning problem of robotic manipulators. The [...] Read more.
We introduce a kinematic graph in this article. A kinematic graph results from structuring the data obtained from the sampling method for sampling-based motion planning algorithms in robotics with the motivation to adapt the method to the positioning problem of robotic manipulators. The term kinematic graph emphasises the fact that any path computed by sampling-based motion planning algorithms using a kinematic graph is guaranteed to correspond to a feasible motion for the positioning of the robotic manipulator. We propose methods to combine the information from the configuration and task spaces of the robotic manipulators to cluster the samples. The kinematic graph is the result of this systematic clustering and a tremendous reduction in the size of the problem. Hence, using a kinematic graph, it is possible to effectively employ sampling-based motion planning algorithms for robotic manipulators, where the problem is defined in higher dimensions than those for which these algorithms were developed. Other barriers that hindered adequate utilisation of such algorithms for robotic manipulators with articulated arms, such as the non-injective surjection of the forward kinematic function, are also addressed in the structure of the kinematic graph. Full article
(This article belongs to the Special Issue Kinematics and Robot Design V, KaRD2022)
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15 pages, 4665 KiB  
Article
Shelf Replenishment Based on Object Arrangement Detection and Collapse Prediction for Bimanual Manipulation
by Tomohiro Motoda, Damien Petit, Takao Nishi, Kazuyuki Nagata, Weiwei Wan and Kensuke Harada
Robotics 2022, 11(5), 104; https://doi.org/10.3390/robotics11050104 - 22 Sep 2022
Cited by 5 | Viewed by 3049
Abstract
Object manipulation automation in logistic warehouses has recently been actively researched. However, shelf replenishment is a challenge that requires the precise and careful handling of densely piled objects. The irregular arrangement of objects on a shelf makes this task particularly difficult. This paper [...] Read more.
Object manipulation automation in logistic warehouses has recently been actively researched. However, shelf replenishment is a challenge that requires the precise and careful handling of densely piled objects. The irregular arrangement of objects on a shelf makes this task particularly difficult. This paper presents an approach for generating a safe replenishment process from a single depth image, which is provided as an input to two networks to identify arrangement patterns and predict the occurrence of collapsing objects. The proposed inference-based strategy provides an appropriate decision and course of action on whether to create an insertion space while considering the safety of the shelf content. In particular, we exploit the bimanual dexterous manipulation capabilities of the associated robot to resolve the task safely, without re-organizing the entire shelf. Experiments with a real bimanual robot were performed in three typical scenarios: shelved, stacked, and random. The objects were randomly placed in each scenario. The experimental results verify the performance of our proposed method in randomized situations on a shelf with a real bimanual robot. Full article
(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)
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22 pages, 9822 KiB  
Article
RoboNav: An Affordable Yet Highly Accurate Navigation System for Autonomous Agricultural Robots
by Rocco Galati, Giacomo Mantriota and Giulio Reina
Robotics 2022, 11(5), 99; https://doi.org/10.3390/robotics11050099 - 21 Sep 2022
Cited by 9 | Viewed by 2561
Abstract
The paper presents RoboNav, a cost-effective and accurate decimeter-grade navigation system that can be used for deployment in the field of autonomous agricultural robots. The novelty of the system is the reliance on a dual GPS configuration based on two u-blox modules that [...] Read more.
The paper presents RoboNav, a cost-effective and accurate decimeter-grade navigation system that can be used for deployment in the field of autonomous agricultural robots. The novelty of the system is the reliance on a dual GPS configuration based on two u-blox modules that work in conjunction with three low-cost inertial sensors within a Gaussian Sum Filter able to combine multiple Extended Kalman filters dealing with IMU bias and GPS signal loss. The system provides estimation of both position and heading with high precision and robustness, at a significantly lower cost than existing equivalent navigation systems. RoboNav is validated in a commercial vineyard by performing experimental tests using an all-terrain tracked robot commanded to follow a series of GPS waypoints, trying to minimize the crosstrack error and showing average errors on the order of 0.2 m and 0.2 for the measurement of position and yaw angle, respectively. Full article
(This article belongs to the Section Agricultural and Field Robotics)
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19 pages, 7792 KiB  
Article
Development of an End-Effector Type Therapeutic Robot with Sliding Mode Control for Upper-Limb Rehabilitation
by Md Mahafuzur Rahaman Khan, Asif Al Zubayer Swapnil, Tanvir Ahmed, Md Mahbubur Rahman, Md Rasedul Islam, Brahim Brahmi, Raouf Fareh and Mohammad Habibur Rahman
Robotics 2022, 11(5), 98; https://doi.org/10.3390/robotics11050098 - 21 Sep 2022
Cited by 5 | Viewed by 3466
Abstract
Geriatric disorders, strokes, spinal cord injuries, trauma, and workplace injuries are all prominent causes of upper limb disability. A two-degrees-of-freedom (DoFs) end-effector type robot, iTbot (intelligent therapeutic robot) was designed to provide upper limb rehabilitation therapy. The non-linear control of iTbot utilizing modified [...] Read more.
Geriatric disorders, strokes, spinal cord injuries, trauma, and workplace injuries are all prominent causes of upper limb disability. A two-degrees-of-freedom (DoFs) end-effector type robot, iTbot (intelligent therapeutic robot) was designed to provide upper limb rehabilitation therapy. The non-linear control of iTbot utilizing modified sliding mode control (SMC) is presented in this paper. The chattering produced by a conventional SMC is undesirable for this type of robotic application because it damages the mechanical structure and causes discomfort to the robot user. In contrast to conventional SMC, our proposed method reduces chattering and provides excellent dynamic tracking performance, allowing rapid convergence of the system trajectory to its equilibrium point. The performance of the developed robot and controller was evaluated by tracking trajectories corresponding to conventional passive arm movement exercises, including several joints. According to the results of experiment, the iTbot demonstrated the ability to follow the desired trajectories effectively. Full article
(This article belongs to the Special Issue Kinematics and Robot Design V, KaRD2022)
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20 pages, 10085 KiB  
Article
Tunable Vibration Absorber Design for a High-Precision Cartesian Robot
by Simone D’Imperio, Teresa Maria Berruti, Chiara Gastaldi and Pietro Soccio
Robotics 2022, 11(5), 103; https://doi.org/10.3390/robotics11050103 - 21 Sep 2022
Cited by 3 | Viewed by 2354
Abstract
In metal sheet processing for automotive application, it is crucial to guarantee high robot dynamics for reduced cycle times and adequate components accuracy to be competitive in the market. Since the two aspects are closely and inversely related, the problem becomes challenging. After [...] Read more.
In metal sheet processing for automotive application, it is crucial to guarantee high robot dynamics for reduced cycle times and adequate components accuracy to be competitive in the market. Since the two aspects are closely and inversely related, the problem becomes challenging. After the first cutting tests, the Cartesian Robot prototype displayed insufficient dimensional accuracy when undergoing high accelerations. The solution hereby proposed is the design of a Tuned Mass Damper (TMD), working in shear mode, to reduce the robot vibration amplitude. To this end, an initial assessment of the robot frequency response and natural frequencies was performed both by using a Finite Element (FE) model of the machine and experimentally. Further, frequency response analyses were carried out to evaluate the TMD effectiveness and to highlight possible criticalities from the manufacturing point of view. On a numerical level, the proposed design can damp the machine resonant frequencies, also showing a certain grade of tunability before operation and in-plane orientation insensitiveness thanks to the use of cylindrically shaped springs. Full article
(This article belongs to the Section Industrial Robots and Automation)
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16 pages, 1856 KiB  
Article
Learning-Based Shared Control Using Gaussian Processes for Obstacle Avoidance in Teleoperated Robots
by Catalin Stefan Teodorescu, Keir Groves and Barry Lennox
Robotics 2022, 11(5), 102; https://doi.org/10.3390/robotics11050102 - 21 Sep 2022
Viewed by 1953
Abstract
Physically inspired models of the stochastic nature of the human-robot-environment interaction are generally difficult to derive from first principles, thus alternative data-driven approaches are an attractive option. In this article, Gaussian process regression is used to model a safe stop maneuver for a [...] Read more.
Physically inspired models of the stochastic nature of the human-robot-environment interaction are generally difficult to derive from first principles, thus alternative data-driven approaches are an attractive option. In this article, Gaussian process regression is used to model a safe stop maneuver for a teleoperated robot. In the proposed approach, a limited number of discrete experimental training data points are acquired to fit (or learn) a Gaussian process model, which is then used to predict the evolution of the process over a desired continuous range (or domain). A confidence measure for those predictions is used as a tuning parameter in a shared control algorithm, and it is demonstrated that it can be used to assist a human operator by providing (low-level) obstacle avoidance when they utilize the robot to carry out safety-critical tasks that involve remote navigation using the robot. The algorithm is personalized in the sense that it can be tuned to match the specific driving style of the person that is teleoperating the robot over a specific terrain. Experimental results demonstrate that with the proposed shared controller enabled, the human operator is able to more easily maneuver the robot in environments with (potentially dangerous) static obstacles, thus keeping the robot safe and preserving the original state of the surroundings. The future evolution of this work will be to apply this shared controller to mobile robots that are being deployed to inspect hazardous nuclear environments, ensuring that they operate with increased safety. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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21 pages, 15099 KiB  
Article
A New Design Identification and Control Based on GA Optimization for An Autonomous Wheelchair
by Mohamed A. Shamseldin, Eissa Khaled, Abdelrahman Youssef, Diaaeldin Mohamed, Shady Ahmed, Abdallah Hesham, Amira Elkodama and Mohamed Badran
Robotics 2022, 11(5), 101; https://doi.org/10.3390/robotics11050101 - 21 Sep 2022
Cited by 8 | Viewed by 3001
Abstract
The daily lifestyle of an average human has changed drastically. Robotics and AI systems are applied to many fields, including the medical field. An autonomous wheelchair that improves the degree of independence that a wheelchair user has can be a very useful contribution [...] Read more.
The daily lifestyle of an average human has changed drastically. Robotics and AI systems are applied to many fields, including the medical field. An autonomous wheelchair that improves the degree of independence that a wheelchair user has can be a very useful contribution to society. This paper presents the design and implementation of an autonomous wheelchair that uses LIDAR to navigate and perform SLAM. It uses the ROS framework and allows the user to choose a goal position through a touchscreen or using deep learning-based voice recognition. It also presents a practical implementation of system identification and optimization of PID control gains, which are applied to the autonomous wheelchair robot. Input/output data were collected using Arduino, consisting of linear and angular speeds and wheel PWM signal commands, and several black-box models were developed to simulate the actual wheelchair setup. The best-identified model was the NLARX model, which had the highest square error (0.1259) among the other candidate models. In addition, using MATLAB, Optimal PID gains were obtained from the genetic algorithm. Performance on real hardware was evaluated and compared to the identified model response. The two responses were identical, except for some of the noise due to the encoder measurement errors and wheelchair vibration. Full article
(This article belongs to the Special Issue Medical and Rehabilitation Robots)
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18 pages, 101119 KiB  
Article
Assisted Operation of a Robotic Arm Based on Stereo Vision for Positioning near an Explosive Device
by Andres Montoya Angulo, Lizardo Pari Pinto, Erasmo Sulla Espinoza, Yuri Silva Vidal and Elvis Supo Colquehuanca
Robotics 2022, 11(5), 100; https://doi.org/10.3390/robotics11050100 - 21 Sep 2022
Cited by 8 | Viewed by 2438
Abstract
This document presents an assisted operation system of a robotic arm for positioning near an explosive device selected by the user through the visualization of the cameras on the screen. Two non-converging cameras mounted on the robotic arm in camera-in-hand configuration provide the [...] Read more.
This document presents an assisted operation system of a robotic arm for positioning near an explosive device selected by the user through the visualization of the cameras on the screen. Two non-converging cameras mounted on the robotic arm in camera-in-hand configuration provide the three-dimensional (3D) coordinates of the object being tracked, using a 3D reconstruction technique with the help of the continuously adaptive mean shift (CAMSHIFT) algorithm for object tracking and feature matching. The inverse kinematics of the robot is implemented to locate the end effector close to the explosive so that the operator can perform the operation of grabbing the grenade more easily. Inverse kinematics is implemented in its geometric form, thus reducing the computational load. Tests conducted with various explosive devices verified the effectiveness of the system in locating the robotic arm in the desired position. Full article
(This article belongs to the Special Issue Autonomous Robots for Inspection and Maintenance)
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18 pages, 4572 KiB  
Article
Modelling and Analysis of the Spital Branched Flexure-Hinge Adjustable-Stiffness Continuum Robot
by Nan Ma, Stephen Monk and David Cheneler
Robotics 2022, 11(5), 97; https://doi.org/10.3390/robotics11050097 - 14 Sep 2022
Cited by 6 | Viewed by 2453
Abstract
Continuum robots are increasingly being used in industrial and medical applications due to their high number of degrees of freedom (DoF), large workspace and their ability to operate dexterously. However, the positional accuracy of conventional continuum robots with a backbone structure is usually [...] Read more.
Continuum robots are increasingly being used in industrial and medical applications due to their high number of degrees of freedom (DoF), large workspace and their ability to operate dexterously. However, the positional accuracy of conventional continuum robots with a backbone structure is usually low due to the low stiffness of the often-lengthy driving cables/tendons. Here, this problem has been solved by integrating additional mechanisms with adjustable stiffness within the continuum robot to improve its stiffness and mechanical performance, thus enabling it to be operated with high accuracy and large payloads. To support the prediction of the improved performance of the adjustable stiffness continuum robot, a kinetostatic model was developed by considering the generalized internal loads that are caused by the deformation of the flexure-hinge mechanism and the structural stiffening caused by the external loads on the end-effector. Finally, experiments were conducted on physical prototypes of 2-DoF and 6-DoF continuum robots to validate the model. It was found that the proposed kinetostatic model validates experimental observations within an average deviation of 9.1% and 6.2% for the 2-DoF and 6-DoF continuum robots, respectively. It was also found that the kinematic accuracy of the continuum robots can be improved by a factor of 32.8 by adding the adjustable stiffness mechanisms. Full article
(This article belongs to the Section Intelligent Robots and Mechatronics)
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20 pages, 6159 KiB  
Article
Dances with Social Robots: A Pilot Study at Long-Term Care
by Yizhu Li, Nan Liang, Meysam Effati and Goldie Nejat
Robotics 2022, 11(5), 96; https://doi.org/10.3390/robotics11050096 - 13 Sep 2022
Cited by 2 | Viewed by 3180
Abstract
Dance therapy can have significant physical, emotional and cognitive benefits for older adults. In particular, social robots can be developed to autonomously facilitate dance sessions to engage these individuals with the aim of improving quality of life. To successfully integrate and promote long-term [...] Read more.
Dance therapy can have significant physical, emotional and cognitive benefits for older adults. In particular, social robots can be developed to autonomously facilitate dance sessions to engage these individuals with the aim of improving quality of life. To successfully integrate and promote long-term use of social robots into long-term care homes for such recreational activities, it is important to explore both residents’ and staff’s perceptions of such robots. In this paper, we present the first pilot human–robot interaction study that investigates the overall experiences and attitudes of both residents and staff in a long-term care home for robot-facilitated dance sessions. In general, the questionnaire results from our study showed that both staff and residents had positive attitudes towards the robot-facilitated dance activity. Encouraging trends showed residents had higher ratings for statements on perceived ease of use, safety, and enjoyment than the staff. However, the staff had a statistically significantly higher rating for willingness to use the robots for dance facilitation. Some key statistical differences were also determined with respect to: (1) gender within the resident group (men had higher ratings for the robots being useful in helping facilitate recreational activities), as well as between staff and residents (resident men had higher perceived safety), and (2) prior robot experience (residents with limited prior experience had higher ratings on perceived ease of use and perceived enjoyment than staff with the same level of experience). The robot-facilitated dance activity was positively received by both older adults and staff as an activity of daily living that can enhance wellbeing while also being safe, easy to use and enjoyable. Full article
(This article belongs to the Special Issue Social Robots for the Human Well-Being)
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20 pages, 9423 KiB  
Article
Deep Reinforcement Learning for Autonomous Dynamic Skid Steer Vehicle Trajectory Tracking
by Sandeep Srikonda, William Robert Norris, Dustin Nottage and Ahmet Soylemezoglu
Robotics 2022, 11(5), 95; https://doi.org/10.3390/robotics11050095 - 9 Sep 2022
Cited by 3 | Viewed by 2218
Abstract
Designing controllers for skid-steered wheeled robots is complex due to the interaction of the tires with the ground and wheel slip due to the skid-steer driving mechanism, leading to nonlinear dynamics. Due to the recent success of reinforcement learning algorithms for mobile robot [...] Read more.
Designing controllers for skid-steered wheeled robots is complex due to the interaction of the tires with the ground and wheel slip due to the skid-steer driving mechanism, leading to nonlinear dynamics. Due to the recent success of reinforcement learning algorithms for mobile robot control, the Deep Deterministic Policy Gradients (DDPG) was successfully implemented and an algorithm was designed for continuous control problems. The complex dynamics of the vehicle model were dealt with and the advantages of deep neural networks were leveraged for their generalizability. Reinforcement learning was used to gather information and train the agent in an unsupervised manner. The performance of the trained policy on the six degrees of freedom dynamic model simulation was demonstrated with ground force interactions. The system met the requirement to stay within the distance of half the vehicle width from reference paths. Full article
(This article belongs to the Special Issue Nonlinear Control and Neural Networks in Robotics)
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12 pages, 1944 KiB  
Article
Preliminary Experimental Results of Context-Aware Teams of Multiple Autonomous Agents Operating under Constrained Communications
by Jose Martinez-Lorenzo, Jeff Hudack, Yutao Jing, Michael Shaham, Zixuan Liang, Abdullah Al Bashit, Yushu Wu, Weite Zhang, Matthew Skopin, Juan Heredia-Juesas, Yuntao Ma, Tristan Sweeney, Nicolas Ares and Ari Fox
Robotics 2022, 11(5), 94; https://doi.org/10.3390/robotics11050094 - 9 Sep 2022
Viewed by 1605
Abstract
This work presents and experimentally tests the framework used by our context-aware, distributed team of small Unmanned Aerial Systems (SUAS) capable of operating in real time, in an autonomous fashion, and under constrained communications. Our framework relies on a three-layered approach: (1) an [...] Read more.
This work presents and experimentally tests the framework used by our context-aware, distributed team of small Unmanned Aerial Systems (SUAS) capable of operating in real time, in an autonomous fashion, and under constrained communications. Our framework relies on a three-layered approach: (1) an operational layer, where fast temporal and narrow spatial decisions are made; (2) a tactical layer, where temporal and spatial decisions are made for a team of agents; and (3) a strategical layer, where slow temporal and wide spatial decisions are made for the team of agents. These three layers are coordinated by an ad hoc, software-defined communications network, which ensures sparse but timely delivery of messages amongst groups and teams of agents at each layer, even under constrained communications. Experimental results are presented for a team of 10 small unmanned aerial systems tasked with searching for and monitoring a person in an open area. At the operational layer, our use case presents an agent autonomously performing searching, detection, localization, classification, identification, tracking, and following of the person, while avoiding malicious collisions. At the tactical layer, our experimental use case presents the cooperative interaction of a group of multiple agents that enables the monitoring of the targeted person over wider spatial and temporal regions. At the strategic layer, our use case involves the detection of complex behaviors, i.e., the person being followed enters a car and runs away, or the person being followed exits the car and runs away, which require strategic responses to successfully accomplish the mission. Full article
(This article belongs to the Section Aerospace Robotics and Autonomous Systems)
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19 pages, 6621 KiB  
Article
Collision Avoidance for Redundant 7-DOF Robots Using a Critically Damped Dynamic Approach
by Henrique Simas and Raffaele Di Gregorio
Robotics 2022, 11(5), 93; https://doi.org/10.3390/robotics11050093 - 8 Sep 2022
Cited by 2 | Viewed by 2189
Abstract
The presence of collaborative robots in industrial environments requires that their control strategies include collision avoidance in the generation of trajectories. In general, collision avoidance is performed via additional displacements of the kinematic chain that make the robot move far from the objects [...] Read more.
The presence of collaborative robots in industrial environments requires that their control strategies include collision avoidance in the generation of trajectories. In general, collision avoidance is performed via additional displacements of the kinematic chain that make the robot move far from the objects that are occasionally inserted into its safety workspace. The variability of the coordinates of the collision points inside the safety volume leads to abrupt movements for the robot. This paper presents a general method for smoothing abrupt movements in robots with one degree of redundancy for collision-avoidance trajectories, employing a second-order digital filter designed with adjustable critical damping. The method is illustrated by applying it to a redundant robot with a spherical–revolute–spherical type (SRS-type) kinematic chain, which is a benchmark used to test the algorithms ideated for solving this problem. This paper also presents an alternative algorithm for the inverse kinematics of the SRS-type robot and the computational experiments that show the collision avoidance proposal’s performance and its properties through graphical results. Full article
(This article belongs to the Special Issue Kinematics and Robot Design V, KaRD2022)
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21 pages, 5447 KiB  
Article
Social Robots Outdo the Not-So-Social Media for Self-Disclosure: Safe Machines Preferred to Unsafe Humans?
by Rowling L. Luo, Thea X. Y. Zhang, Derrick H.-C. Chen, Johan F. Hoorn and Ivy S. Huang
Robotics 2022, 11(5), 92; https://doi.org/10.3390/robotics11050092 - 7 Sep 2022
Cited by 4 | Viewed by 2842
Abstract
COVID-19 may not be a ‘youth disease’ but it nevertheless impacts the life of young people dramatically, loneliness and a negative mood being an unexpected additional pandemic. Many young people rely on social media for their feeling of connectedness with others. However, social [...] Read more.
COVID-19 may not be a ‘youth disease’ but it nevertheless impacts the life of young people dramatically, loneliness and a negative mood being an unexpected additional pandemic. Many young people rely on social media for their feeling of connectedness with others. However, social media is suggested to have many negative effects on people’s anxiety. Instead of self-disclosing to others, design may develop alternatives to employ social robots for self-disclosure. In a follow-up on earlier work, we report on a lab experiment of self-disclosing negative emotions to a social media group as compared to writing a conventional diary journal or to talking to an AI-driven social robot after negative mood induction (i.e., viewing shocking earthquake footage). Participants benefitted the most from talking to a robot rather than from writing a journal page or sharing their feelings on social media. Self-disclosure on social media or writing a journal page did not differ significantly. In the design of interventions for mental well-being, human helpers thus far took center stage. Based on our results, we propose design alternatives for an empathic smart home, featuring social robots and chatbots for alleviating stress and anxiety: a social-media interference chatbot, smart watch plus speaker, and a mirror for self-reflection. Full article
(This article belongs to the Special Issue Communication with Social Robots)
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18 pages, 4591 KiB  
Article
Improved Visual SLAM Using Semantic Segmentation and Layout Estimation
by Ahmed Mahmoud and Mohamed Atia
Robotics 2022, 11(5), 91; https://doi.org/10.3390/robotics11050091 - 6 Sep 2022
Viewed by 2397
Abstract
The technological advances in computational systems have enabled very complex computer vision and machine learning approaches to perform efficiently and accurately. These new approaches can be considered a new set of tools to reshape the visual SLAM solutions. We present an investigation of [...] Read more.
The technological advances in computational systems have enabled very complex computer vision and machine learning approaches to perform efficiently and accurately. These new approaches can be considered a new set of tools to reshape the visual SLAM solutions. We present an investigation of the latest neuroscientific research that explains how the human brain can accurately navigate and map unknown environments. The accuracy suggests that human navigation is not affected by traditional visual odometry drifts resulting from tracking visual features. It utilises the geometrical structures of the surrounding objects within the navigated space. The identified objects and space geometrical shapes anchor the estimated space representation and mitigate the overall drift. Inspired by the human brain’s navigation techniques, this paper presents our efforts to incorporate two machine learning techniques into a VSLAM solution: semantic segmentation and layout estimation to imitate human abilities to map new environments. The proposed system benefits from the geometrical relations between the corner points of the cuboid environments to improve the accuracy of trajectory estimation. Moreover, the implemented SLAM solution semantically groups the map points and then tracks each group independently to limit the system drift. The implemented solution yielded higher trajectory accuracy and immunity to large pure rotations. Full article
(This article belongs to the Section Aerospace Robotics and Autonomous Systems)
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19 pages, 4072 KiB  
Article
Augmented and Virtual Reality Experiences for Learning Robotics and Training Integrative Thinking Skills
by Igor Verner, Dan Cuperman, Huberth Perez-Villalobos, Alex Polishuk and Sergei Gamer
Robotics 2022, 11(5), 90; https://doi.org/10.3390/robotics11050090 - 6 Sep 2022
Cited by 4 | Viewed by 3150
Abstract
Learning through augmented reality (AR) and virtual reality (VR) experiences has become a valuable approach in modern robotics education. This study evaluated this approach and investigated how 99 first-year industrial engineering students explored robot systems through such online experiences while staying at home. [...] Read more.
Learning through augmented reality (AR) and virtual reality (VR) experiences has become a valuable approach in modern robotics education. This study evaluated this approach and investigated how 99 first-year industrial engineering students explored robot systems through such online experiences while staying at home. The objective was to examine learning in the AR/VR environment and evaluate its contribution to understanding the robot systems and to fostering integrative thinking. During the AR experiences that we developed using Vuforia Studio, the students learned about TurtleBot2 and RACECAR MN robots while disassembling and modifying their models and by obtaining information about their components. In the VR experience with the RacecarSim simulator, the students explored sensor-based robot navigation. Quizzes were used to assess understanding of robot systems, and a post-workshop questionnaire evaluated the workshop’s contribution to learning about the robots and to training integrative thinking skills. The data indicate that the students gained understanding of the robot systems, appreciated the contribution of the augmented and virtual reality apps, and widely used integrative thinking throughout the practice. Our study shows that AR apps and virtual simulators can be effectively used for experiential learning about robot systems in online courses. However, these experiences cannot replace practice with real robots. Full article
(This article belongs to the Special Issue Advances and Challenges in Educational Robotics II)
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28 pages, 37079 KiB  
Article
Design of a Rapid Structure from Motion (SfM) Based 3D Reconstruction Framework Using a Team of Autonomous Small Unmanned Aerial Systems (sUAS)
by Douglas Shane Smith, Jr. and Hakki Erhan Sevil
Robotics 2022, 11(5), 89; https://doi.org/10.3390/robotics11050089 - 4 Sep 2022
Cited by 2 | Viewed by 2177
Abstract
The aim of this research effort was to develop a framework for a structure from motion (SfM)-based 3D reconstruction approach with a team of autonomous small unmanned aerial systems (sUASs) using a distributed behavior model. The framework is composed of two major goals [...] Read more.
The aim of this research effort was to develop a framework for a structure from motion (SfM)-based 3D reconstruction approach with a team of autonomous small unmanned aerial systems (sUASs) using a distributed behavior model. The framework is composed of two major goals to accomplish this: a distributed behavior model for a team of sUASs and a SfM-based 3D reconstruction using team of sUASs. The developed distributed behavior model is based on the entropy of the system, and when the entropy of the system is high, the sUASs get closer to reducing the overall entropy. This is called the grouping phase. If the entropy is less than the predefined threshold, then the sUASs switch to the 3D reconstruction phase. The novel part of the framework is that sUASs are only given the object of interest to reconstruct the 3D model, and they use the developed distributed behavior to coordinate their motion for that goal. A comprehensive parameter analysis was performed, and optimum sets of parameters were selected for each sub-system. Finally, optimum parameters for two sub-systems were combined in a simulation to demonstrate the framework’s operability and evaluate the completeness and speed of the reconstructed model. The simulation results show that the framework operates successfully and is capable of generating complete models as desired, autonomously. Full article
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16 pages, 6286 KiB  
Article
Design of a Lightweight and Deployable Soft Robotic Arm
by Pierpaolo Palmieri, Matteo Melchiorre and Stefano Mauro
Robotics 2022, 11(5), 88; https://doi.org/10.3390/robotics11050088 - 31 Aug 2022
Cited by 9 | Viewed by 5874
Abstract
Soft robotics represents a rising trend in recent years, due to the ability to work in unstructured environments or in strict contact with humans. Introducing soft parts, robots can adapt to various contexts overcoming limits relative to the rigid structure of traditional ones. [...] Read more.
Soft robotics represents a rising trend in recent years, due to the ability to work in unstructured environments or in strict contact with humans. Introducing soft parts, robots can adapt to various contexts overcoming limits relative to the rigid structure of traditional ones. Main issues of soft robotics systems concern the relatively low force exertion and control complexity. Moreover, several fields of application, as space industry, need to develop novel lightweight and deployable robotic systems, that can be stored into a relatively small volume and deployed when required. In this paper, POPUP robot is introduced: a soft manipulator having inflatable links and rigid joints. Its hybrid structure aims to match the advantages of rigid robots and the useful properties of having a lightweight and deployable parts, ensuring simple control, low energy consumption and low compressed gas requirement. The first robot prototype and the system architecture are described highlighting design criteria and effect of internal pressure on the performances. A pseudo-rigid body model is used to describe the behavior of inflatable links looking forward to control design. Finally, the model is extended to the whole robot: multi-body simulations are performed to highlight the importance of suitable sensor equipment for control development, proposing a visual servoing solution. Full article
(This article belongs to the Special Issue Frontiers in Bionic and Flexible Robotics)
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22 pages, 10538 KiB  
Article
A Backstepping Approach to Nonlinear Model Predictive Horizon for Optimal Trajectory Planning
by Younes Al Younes and Martin Barczyk
Robotics 2022, 11(5), 87; https://doi.org/10.3390/robotics11050087 - 31 Aug 2022
Cited by 3 | Viewed by 2015
Abstract
This paper presents a novel trajectory planning approach for nonlinear dynamical systems; a multi-rotor drone, built on an optimization-based framework proposed by the authors named the Nonlinear Model Predictive Horizon. In the present work, this method is integrated with a Backstepping Control technique. [...] Read more.
This paper presents a novel trajectory planning approach for nonlinear dynamical systems; a multi-rotor drone, built on an optimization-based framework proposed by the authors named the Nonlinear Model Predictive Horizon. In the present work, this method is integrated with a Backstepping Control technique. The goal is to remove the non-convexity of the optimization problem in order to provide real-time computation of reference trajectories for the vehicle which respects its dynamics while avoiding sensed static and dynamic obstacles in the environment. Our method is applied to two models of multi-rotor drones to demonstrate its flexibility. Several simulation and hardware flight experiments are presented to validate the proposed design and demonstrate its performance improvement over earlier work. Full article
(This article belongs to the Section Aerospace Robotics and Autonomous Systems)
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