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Robotics, Volume 11, Issue 2 (April 2022) – 24 articles

Cover Story (view full-size image): With the introduction of the metaverse, the virtual digital world is going to take a conceptual leap forward. As technology progresses, bringing us new immersive worlds, we must adapt how we educate students and equip teachers to face these new challenges. In this perspective, hands-on laboratory work and practical experience are currently under-supported. This is especially crucial in science, technology, engineering, and mathematics (STEM) subjects. In this work, a unique strategy to attain multisensory learning in STEM education by combining virtual and augmented reality (VR/AR) with haptic wearables is proposed. The implications of this novel viewpoint on established pedagogical notions are discussed. The goal is to support initiatives throughout the world to make fully immersive, open, and remote laboratory learning a reality. View this paper
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20 pages, 5015 KiB  
Article
The Effect of the Degree of Freedom and Weight of the Hand Exoskeleton on Joint Mobility Function
by Ilham Priadythama, Wen Liang Yeoh, Ping Yeap Loh and Satoshi Muraki
Robotics 2022, 11(2), 53; https://doi.org/10.3390/robotics11020053 - 18 Apr 2022
Cited by 2 | Viewed by 3347
Abstract
This study aims to investigate the effects of the degree of freedom (DOF) and weight of the hand exoskeleton (HE) on hand joint mobility function (ease of movement, movement range) in fine hand use activities. A three-digit passive HE prototype was built to [...] Read more.
This study aims to investigate the effects of the degree of freedom (DOF) and weight of the hand exoskeleton (HE) on hand joint mobility function (ease of movement, movement range) in fine hand use activities. A three-digit passive HE prototype was built to fit each of the 12 participants. Two DOF setups (three DOF, two DOF), two digits’ weight levels (70 g, 140 g), and barehand conditions were tested. A productivity task (performed with Standardized-Nine Hole Peg Test) and motion tasks, both performing the tip pinch and tripod pinch, were conducted to measure the task completion time and the range of motion (ROM) of the digit joints, respectively, using a motion capture system. The perceived ease rating was also measured. The results showed that DOF reduction and weight addition caused a significant task completion time increase and rating drop (p < 0.05). Meanwhile, the DOF reduction increased the ROM reduction of the proximal interphalangeal joints; however, the weight addition caused a correction of the ROM reduction of several joints (p < 0.05) at the tripod pinch. In conclusion, wearing an HE reduces hand joint mobility, especially in lower DOF. However, a certain weight addition may improve joint mobility in terms of the fingers’ movement range. Full article
(This article belongs to the Section Medical Robotics and Service Robotics)
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18 pages, 2497 KiB  
Article
Source Localisation Using Wavefield Correlation-Enhanced Particle Swarm Optimisation
by George Rossides, Alan Hunter and Benjamin Metcalfe
Robotics 2022, 11(2), 52; https://doi.org/10.3390/robotics11020052 - 18 Apr 2022
Viewed by 2496
Abstract
Particle swarm optimisation (PSO) is a swarm intelligence algorithm used for controlling robotic swarms in applications such as source localisation. However, conventional PSO algorithms consider only the intensity of the received signal. Wavefield signals, such as propagating underwater acoustic waves, permit the measurement [...] Read more.
Particle swarm optimisation (PSO) is a swarm intelligence algorithm used for controlling robotic swarms in applications such as source localisation. However, conventional PSO algorithms consider only the intensity of the received signal. Wavefield signals, such as propagating underwater acoustic waves, permit the measurement of higher order statistics that can be used to provide additional information about the location of the source and thus improve overall swarm performance. Wavefield correlation techniques that make use of such information are already used in multi-element hydrophone array systems for the localisation of underwater marine sources. Additionally, the simplest model of a multi-element array (a two-element array) is characterised by operational simplicity and low-cost, which matches the ethos of robotic swarms. Thus, in this paper, three novel approaches are introduced that enable PSO to consider the higher order statistics available in wavefield measurements. In simulations, they are shown to outperform the standard intensity-based PSO in terms of robustness to low signal-to-noise ratio (SNR) and convergence speed. The best performing approach, cross-correlation bearing PSO (XB-PSO), is capable of converging to the source from as low as −5 dB initial SNR. The original PSO algorithm only manages to converge at 10 dB and at this SNR, XB-PSO converges 4 times faster. Full article
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14 pages, 3219 KiB  
Article
Performance Index for Dimensional Synthesis of Robots for Specific Tasks
by Miguel Díaz-Rodríguez, Pedro Araujo-Gómez and Octavio Andrés González-Estrada
Robotics 2022, 11(2), 51; https://doi.org/10.3390/robotics11020051 - 16 Apr 2022
Cited by 1 | Viewed by 2505
Abstract
This study proposes a performance index for the dimensional optimization of parallel manipulators with specific tasks. In particular, the index evaluates the dexterity of the mechanism to be designed and compares it with that of the required specific task, e.g., rehabilitation tasks. The [...] Read more.
This study proposes a performance index for the dimensional optimization of parallel manipulators with specific tasks. In particular, the index evaluates the dexterity of the mechanism to be designed and compares it with that of the required specific task, e.g., rehabilitation tasks. The proposed index is implemented to design a 3UPS + RPU parallel manipulator for performing physical rehabilitation treatments on lower limbs. First, the condition numbers of both the mechanism and the lower limb are determined. Subsequently, the indexes are compared such that both systems exhibit similar dexterity. As a case study, the approach is implemented in the dimensional synthesis of the 3UPS + RPU parallel manipulator. The optimization approach enables obtaining a dexterity space of the mechanism that best matches that of the lower limb. The results are graphically presented, showing the matching areas of both workspaces, verifying the effectiveness of the proposed index. Full article
(This article belongs to the Special Issue Medical and Rehabilitation Robots)
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30 pages, 5320 KiB  
Article
Investigating the Impact of Triangle and Quadrangle Mesh Representations on AGV Path Planning for Various Indoor Environments: With or Without Inflation
by Ahmadreza Meysami, Jean-Christophe Cuillière, Vincent François and Sousso Kelouwani
Robotics 2022, 11(2), 50; https://doi.org/10.3390/robotics11020050 - 13 Apr 2022
Cited by 10 | Viewed by 3396
Abstract
In a factory with different kinds of spatial atmosphere (warehouses, corridors, small or large workshops with varying sizes of obstacles and distribution patterns), the robot’s generated paths for navigation tasks mainly depend on the representation of that environment. Hence, finding the best representation [...] Read more.
In a factory with different kinds of spatial atmosphere (warehouses, corridors, small or large workshops with varying sizes of obstacles and distribution patterns), the robot’s generated paths for navigation tasks mainly depend on the representation of that environment. Hence, finding the best representation for each particular environment is necessary to forge a compromise between length, safety, and complexity of path planning. This paper aims to scrutinize the impact of environment model representation on the performance of an automated guided vehicle (AGV). To do so, a multi-objective cost function, considering the length of the path, its complexity, and minimum distance to obstacles, is defined for a perfect circular robot. Unlike other similar studies, three types of representation, namely quadrangle, irregular triangle, and varying-size irregular triangle, are then utilized to model the environment while applying an inflation layer to the discretized view. Finally, a navigation scenario is tested for different cell decomposition methods and an inflation layer size. The obtained results indicate that a nearly constant coarse size triangular mesh is a good candidate for a fixed-size robot in a non-changing environment. Moreover, the varying size of the triangular mesh and grid cell representations are better choices for factories with changing plans and multi-robot sizes due to the effect of the inflation layer. Based on the definition of a metric, which is a criterion for quantifying the performance of path planning on a representation type, constant or variable size triangle shapes are the only and best candidate for discretization in about 59% of industrial environments. In other cases, both cell types, the square and the triangle, can together be the best representation. Full article
(This article belongs to the Topic Industrial Robotics)
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18 pages, 2530 KiB  
Article
Empirically Comparing Magnetic Needle Steering Models Using Expectation-Maximization
by Richard L. Pratt and Andrew J. Petruska
Robotics 2022, 11(2), 49; https://doi.org/10.3390/robotics11020049 - 13 Apr 2022
Cited by 6 | Viewed by 2230
Abstract
Straight-line needle insertion is a prevalent tool in surgical interventions in the brain, such as Deep Brain Stimulation and Convection-Enhanced Delivery, that treat a range of conditions from Alzheimer’s disease to brain cancer. Using a steerable needle to execute curved trajectories and correct [...] Read more.
Straight-line needle insertion is a prevalent tool in surgical interventions in the brain, such as Deep Brain Stimulation and Convection-Enhanced Delivery, that treat a range of conditions from Alzheimer’s disease to brain cancer. Using a steerable needle to execute curved trajectories and correct positional deviation could enable more intervention possibilities, while reducing the risk of complication in these procedures. This paper experimentally identifies model parameters using an expectation-maximization (EM) algorithm for two different steerable needle models. The results compared a physically motivated model to the established bicycle needle model and found the former to be preferred for modeling soft brain tissue needle insertion. The results also supported the experimentally parameterized models’ use in future applications such as needle steering control. Full article
(This article belongs to the Section Medical Robotics and Service Robotics)
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24 pages, 5772 KiB  
Article
Elasto-Geometrical Model-Based Control of Industrial Manipulators Using Force Feedback: Application to Incremental Sheet Forming
by Marwan Johra, Eric Courteille, Dominique Deblaise and Sylvain Guégan
Robotics 2022, 11(2), 48; https://doi.org/10.3390/robotics11020048 - 12 Apr 2022
Cited by 3 | Viewed by 2682
Abstract
This paper aims to improve the positioning accuracy of serial industrial manipulators using force feedback in manufacturing processes by implementing an elasto-geometrical model-based control. Initially, the real-time position control strategy using a force feedback to elastically correct the Tool Center Point (TCP) pose [...] Read more.
This paper aims to improve the positioning accuracy of serial industrial manipulators using force feedback in manufacturing processes by implementing an elasto-geometrical model-based control. Initially, the real-time position control strategy using a force feedback to elastically correct the Tool Center Point (TCP) pose of serial industrial manipulators is detailed. To continue, an efficient model structure identification and calibration is proposed to shorten the elasto-geometrical modeling process. The Virtual Joint Method (VJM) is chosen to iterate and complete the robot stiffness modeling. This method considers that the elastic deformations are only localized at the joints of the robot. An appropriate and original test-model approach allows a minimum of optimization iterations to find the best compromise between complexity and accuracy of the modeling. The proposed approach is illustrated in detail by the Stäubli TX200 robot modeling. Finally, the reliability and responsiveness of the developed control framework is then evaluated through experimental tests in an Incremental Sheet Forming (ISF) context. An average improvement of 70% in trajectory-tracking accuracy is achieved during these tests. Overall, the high accuracy and responsiveness of the developed system demonstrate a promising potential for deploying industrial manipulators to a cost-effective manufacturing processes in industry 4.0. Full article
(This article belongs to the Special Issue Industrial Robotics in Industry 4.0)
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24 pages, 8017 KiB  
Article
A Novel Adaptive Sliding Mode Controller for a 2-DOF Elastic Robotic Arm
by Hua Minh Tuan, Filippo Sanfilippo and Nguyen Vinh Hao
Robotics 2022, 11(2), 47; https://doi.org/10.3390/robotics11020047 - 5 Apr 2022
Cited by 9 | Viewed by 3582
Abstract
Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of [...] Read more.
Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with uncertainties and disturbance on the load side of the robot arm. For the inner loops, model reference adaptive controllers (MRAC) are utilised to handle the uncertainties on the motor side of the robot arm. To show the effectiveness of the proposed controller, extensive simulation experiments and a comparison with the conventional sliding mode controller (SMC) are carried out. As a result, the ASMC has a 50.35% lower average RMS error than the SMC controller, and a shorter settling time (5% criterion) (0.44 s compared to 2.11 s). Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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14 pages, 2190 KiB  
Article
Using Simulation to Evaluate a Tube Perception Algorithm for Bin Picking
by Gonçalo Leão, Carlos M. Costa, Armando Sousa, Luís Paulo Reis and Germano Veiga
Robotics 2022, 11(2), 46; https://doi.org/10.3390/robotics11020046 - 5 Apr 2022
Cited by 3 | Viewed by 2395
Abstract
Bin picking is a challenging problem that involves using a robotic manipulator to remove, one-by-one, a set of objects randomly stacked in a container. In order to provide ground truth data for evaluating heuristic or machine learning perception systems, this paper proposes using [...] Read more.
Bin picking is a challenging problem that involves using a robotic manipulator to remove, one-by-one, a set of objects randomly stacked in a container. In order to provide ground truth data for evaluating heuristic or machine learning perception systems, this paper proposes using simulation to create bin picking environments in which a procedural generation method builds entangled tubes that can have curvatures throughout their length. The output of the simulation is an annotated point cloud, generated by a virtual 3D depth camera, in which the tubes are assigned with unique colors. A general metric based on micro-recall is proposed to compare the accuracy of point cloud annotations with the ground truth. The synthetic data is representative of a high quality 3D scanner, given that the performance of a tube modeling system when given 640 simulated point clouds was similar to the results achieved with real sensor data. Therefore, simulation is a promising technique for the automated evaluation of solutions for bin picking tasks. Full article
(This article belongs to the Special Issue Advances in Industrial Robotics and Intelligent Systems)
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12 pages, 2045 KiB  
Article
Requirements and Solutions for Motion Limb Assistance of COVID-19 Patients
by Marco Ceccarelli, Matteo Bottin, Matteo Russo, Giulio Rosati, Med Amine Laribi and Victor Petuya
Robotics 2022, 11(2), 45; https://doi.org/10.3390/robotics11020045 - 4 Apr 2022
Cited by 4 | Viewed by 2561
Abstract
COVID-19 patients are strongly affected in terms of limb motion when imbedded during the acute phase of the infection, but also during the course of recovery therapies. Peculiarities are investigated for design requirements for medical devices in limb motion assistance for those patients. [...] Read more.
COVID-19 patients are strongly affected in terms of limb motion when imbedded during the acute phase of the infection, but also during the course of recovery therapies. Peculiarities are investigated for design requirements for medical devices in limb motion assistance for those patients. Solutions are analyzed from existing medical devices to outline open issues to provide guidelines for the proper adaption or for new designs supporting patients against COVID-19 effects. Examples are reported from authors’ activities with cable driven assisting devices. Full article
(This article belongs to the Special Issue Service Robotics against COVID-2019 Pandemic)
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17 pages, 3478 KiB  
Article
A Deep Reinforcement-Learning Approach for Inverse Kinematics Solution of a High Degree of Freedom Robotic Manipulator
by Aryslan Malik, Yevgeniy Lischuk, Troy Henderson and Richard Prazenica
Robotics 2022, 11(2), 44; https://doi.org/10.3390/robotics11020044 - 2 Apr 2022
Cited by 14 | Viewed by 6402
Abstract
The foundation and emphasis of robotic manipulator control is Inverse Kinematics (IK). Due to the complexity of derivation, difficulty of computation, and redundancy, traditional IK solutions pose numerous challenges to the operation of a variety of robotic manipulators. This paper develops a Deep [...] Read more.
The foundation and emphasis of robotic manipulator control is Inverse Kinematics (IK). Due to the complexity of derivation, difficulty of computation, and redundancy, traditional IK solutions pose numerous challenges to the operation of a variety of robotic manipulators. This paper develops a Deep Reinforcement Learning (RL) approach for solving the IK problem of a 7-Degree of Freedom (DOF) robotic manipulator using Product of Exponentials (PoE) as a Forward Kinematics (FK) computation tool and the Deep Q-Network (DQN) as an IK solver. The selected approach is architecturally simpler, making it faster and easier to implement, as well as more stable, because it is less sensitive to hyperparameters than continuous action spaces algorithms. The algorithm is designed to produce joint-space trajectories from a given end-effector trajectory. Different network architectures were explored and the output of the DQN was implemented experimentally on a Sawyer robotic arm. The DQN was able to find different trajectories corresponding to a specified Cartesian path of the end-effector. The network agent was able to learn random Bézier and straight-line end-effector trajectories in a reasonable time frame with good accuracy, demonstrating that even though DQN is mainly used in discrete solution spaces, it could be applied to generate joint space trajectories. Full article
(This article belongs to the Special Issue Nonlinear Control and Neural Networks in Robotics)
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17 pages, 5339 KiB  
Article
Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators
by Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo
Robotics 2022, 11(2), 43; https://doi.org/10.3390/robotics11020043 - 2 Apr 2022
Cited by 5 | Viewed by 3264
Abstract
The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the [...] Read more.
The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the Radial Basis Function Neural Network (RBFNN) architecture tuned by a novel meta-heuristic algorithm, namely, the Cooperative Search Optimisation Algorithm (CSOA). The architecture presented is able to automatically learn the kinematic properties of the manipulator. Learning is accomplished iteratively based only on the observation of the input–output relationship. Related simulations are carried out on a 3-Degrees of Freedom (DOF) manipulator on the Robot Operating System (ROS). The dataset created from the simulation is divided 65–35 for training–testing of the proposed model. The metrics used for model validation include spread value, cost and runtime for the training dataset, and Mean Relative Error, Normal Mean Square Error, and Mean Absolute Error for the testing dataset. A comparative analysis of the CSOA-RBFNN model is performed with an artificial neural network, support vector regression model, and with with other meta-heuristic RBFNN models, i.e., PSO-RBFNN and GWO-RBFNN, that show the effectiveness and superiority of the proposed technique. Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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14 pages, 3677 KiB  
Article
The Redesigned Serpens, a Low-Cost, Highly Compliant Snake Robot
by Askan Duivon, Pino Kirsch, Boris Mauboussin, Gabriel Mougard, Jakub Woszczyk and Filippo Sanfilippo
Robotics 2022, 11(2), 42; https://doi.org/10.3390/robotics11020042 - 1 Apr 2022
Cited by 7 | Viewed by 3169
Abstract
The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from [...] Read more.
The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from a control standpoint, the accurate identification of push-points and reliable determination of feasible contact reaction forces are required. This is difficult to achieve with rigidly actuated robots because of the lack of compliance. As a possible solution to this challenge, our research group recently presented Serpens, a low-cost, open-source, and highly compliant multi-purpose modular snake robot with a series elastic actuator (SEA). In this paper, we propose a new prototyping iteration for our snake robot to achieve a more dependable design. The following three contributions are outlined in this work as a whole: the remodelling of the elastic joint with the addition of a damper element; a refreshed design for the screw-less assembly mechanism that can now withstand higher transverse forces; the re-design of the joint module with an improved reorganisation of the internal hardware components to facilitate heat dissipation and to accommodate a larger battery with easier access. The Robot Operating System (ROS) serves as the foundation for the software architecture. The possibility of applying machine learning approaches is considered. The results of preliminary simulations are provided. Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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20 pages, 1631 KiB  
Review
A Perspective Review on Integrating VR/AR with Haptics into STEM Education for Multi-Sensory Learning
by Filippo Sanfilippo, Tomas Blazauskas, Gionata Salvietti, Isabel Ramos, Silviu Vert, Jaziar Radianti, Tim A. Majchrzak and Daniel Oliveira
Robotics 2022, 11(2), 41; https://doi.org/10.3390/robotics11020041 - 31 Mar 2022
Cited by 22 | Viewed by 9494
Abstract
As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and [...] Read more.
As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and provide possibilities for remote learning. A variety of educational programs, platforms, and technologies are now accessible to support student learning; while these tools are important for society, they are primarily concerned with the dissemination of theoretical material. There is a lack of support for hands-on laboratory work and practical experience. This is particularly important for all disciplines related to science, technology, engineering, and mathematics (STEM), where labs and pedagogical assets must be continuously enhanced in order to provide effective study programs. In this study, we describe a unique perspective to achieving multi-sensory learning through the integration of virtual and augmented reality (VR/AR) with haptic wearables in STEM education. We address the implications of a novel viewpoint on established pedagogical notions. We want to encourage worldwide efforts to make fully immersive, open, and remote laboratory learning a reality. Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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17 pages, 5105 KiB  
Article
A Natural Language Interface for an Autonomous Camera Control System on the da Vinci Surgical Robot
by Maysara Elazzazi, Luay Jawad, Mohammed Hilfi and Abhilash Pandya
Robotics 2022, 11(2), 40; https://doi.org/10.3390/robotics11020040 - 25 Mar 2022
Cited by 6 | Viewed by 3715
Abstract
Positioning a camera during laparoscopic and robotic procedures is challenging and essential for successful operations. During surgery, if the camera view is not optimal, surgery becomes more complex and potentially error-prone. To address this need, we have developed a voice interface to an [...] Read more.
Positioning a camera during laparoscopic and robotic procedures is challenging and essential for successful operations. During surgery, if the camera view is not optimal, surgery becomes more complex and potentially error-prone. To address this need, we have developed a voice interface to an autonomous camera system that can trigger behavioral changes and be more of a partner to the surgeon. Similarly to a human operator, the camera can take cues from the surgeon to help create optimized surgical camera views. It has the advantage of nominal behavior that is helpful in most general cases and has a natural language interface that makes it dynamically customizable and on-demand. It permits the control of a camera with a higher level of abstraction. This paper shows the implementation details and usability of a voice-activated autonomous camera system. A voice activation test on a limited set of practiced key phrases was performed using both online and offline voice recognition systems. The results show an on-average greater than 94% recognition accuracy for the online system and 86% accuracy for the offline system. However, the response time of the online system was greater than 1.5 s, whereas the local system was 0.6 s. This work is a step towards cooperative surgical robots that will effectively partner with human operators to enable more robust surgeries. A video link of the system in operation is provided in this paper. Full article
(This article belongs to the Special Issue Advanced Technologies for Autonomous Surgical Robotics)
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43 pages, 68841 KiB  
Article
Mechanical Design and Analysis of a Novel Three-Legged, Compact, Lightweight, Omnidirectional, Serial–Parallel Robot with Compliant Agile Legs
by David Feller and Christian Siemers
Robotics 2022, 11(2), 39; https://doi.org/10.3390/robotics11020039 - 24 Mar 2022
Cited by 7 | Viewed by 8135
Abstract
In this work, the concept and mechanical design of a novel compact, lightweight, omnidirectional three-legged robot, featuring a hybrid serial–parallel topology including leg compliance is proposed. The proposal focusses deeply on the design aspects of the mechanical realisation of the robot based on [...] Read more.
In this work, the concept and mechanical design of a novel compact, lightweight, omnidirectional three-legged robot, featuring a hybrid serial–parallel topology including leg compliance is proposed. The proposal focusses deeply on the design aspects of the mechanical realisation of the robot based on its 3D-CAD assembly, while also discussing the results of multi-body simulations, exploring the characteristic properties of the mechanical system, regarding the locomotion feasibility of the robot model. Finally, a real-world prototype depicting a single robot leg is presented, which was built by highly leaning into a composite design, combining complex 3D-printed parts with stiff aluminium and polycarbonate parts, allowing for a mechanically dense and slim construction. Eventually, experiments on the prototype leg are demonstrated, showing the mechanical model operating in the real world. Full article
(This article belongs to the Section Sensors and Control in Robotics)
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19 pages, 1960 KiB  
Article
Study of Variational Inference for Flexible Distributed Probabilistic Robotics
by Malte Rørmose Damgaard, Rasmus Pedersen and Thomas Bak
Robotics 2022, 11(2), 38; https://doi.org/10.3390/robotics11020038 - 24 Mar 2022
Cited by 2 | Viewed by 2353
Abstract
By combining stochastic variational inference with message passing algorithms, we show how to solve the highly complex problem of navigation and avoidance in distributed multi-robot systems in a computationally tractable manner, allowing online implementation. Subsequently, the proposed variational method lends itself to more [...] Read more.
By combining stochastic variational inference with message passing algorithms, we show how to solve the highly complex problem of navigation and avoidance in distributed multi-robot systems in a computationally tractable manner, allowing online implementation. Subsequently, the proposed variational method lends itself to more flexible solutions than prior methodologies. Furthermore, the derived method is verified both through simulations with multiple mobile robots and a real world experiment with two mobile robots. In both cases, the robots share the operating space and need to cross each other’s paths multiple times without colliding. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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14 pages, 4507 KiB  
Article
Active Soft Brace for Scoliotic Spine: A Finite Element Study to Evaluate in-Brace Correction
by Athar Ali, Vigilio Fontanari, Werner Schmölz and Sunil K. Agrawal
Robotics 2022, 11(2), 37; https://doi.org/10.3390/robotics11020037 - 21 Mar 2022
Cited by 3 | Viewed by 5345
Abstract
Scoliosis is a spinal disorder that is conventionally treated using rigid or soft braces. Computational methods such as finite element-based models are used to investigate the mechanics of the spine and the effect of braces. Most spinal braces are either passive, static, or [...] Read more.
Scoliosis is a spinal disorder that is conventionally treated using rigid or soft braces. Computational methods such as finite element-based models are used to investigate the mechanics of the spine and the effect of braces. Most spinal braces are either passive, static, or rigid and do not allow mobility to the spine, resulting in muscle atrophy, skin deterioration and other spine complexities. Lack of control over the amount of force being exerted by braces on the human spine could have adverse effects. Therefore, developing an active soft brace which allows mobility to the spine while applying controlled corrective forces could be a promising solution. This study presents finite element analysis (FEA) of an active soft brace that applies corrective forces using elastic bands. The pressure exerted by the brace on the spine can be controlled by varying the tensions in the elastic bands. The elastic band tensions are controlled using low-power, lightweight, and twisted string actuators (TSAs). This study aims to demonstrate the immediate corrections induced by the soft active brace using a scoliotic spine finite element (FE) model. A FE model of the patient’s trunk was created and validated with in vitro study. The brace model was installed on the simulated trunk to evaluate in-brace correction in both sagittal and coronal planes. The brace was evaluated under various load cases by simulating the actuator action. Full article
(This article belongs to the Special Issue Medical and Rehabilitation Robots)
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21 pages, 5160 KiB  
Article
Dynamics Modeling of a Delta Robot with Telescopic Rod for Torque Feedforward Control
by Sai Zhang, Xinjun Liu, Bingkai Yan, Xiangdong Han and Jie Bi
Robotics 2022, 11(2), 36; https://doi.org/10.3390/robotics11020036 - 20 Mar 2022
Cited by 1 | Viewed by 5568
Abstract
This paper presents dynamics modeling of a Delta robot with three revolute legs and a telescopic rod. Firstly, two generalized coordinate systems are established to describe the relationship between the movement of the telescopic rod and the position of the moving platform, and [...] Read more.
This paper presents dynamics modeling of a Delta robot with three revolute legs and a telescopic rod. Firstly, two generalized coordinate systems are established to describe the relationship between the movement of the telescopic rod and the position of the moving platform, and the telescopic rod system kinematics are established through singularity analysis. Secondly, taking the telescopic rod as the research object, the corresponding dynamics model is established using the Euler–Lagrange method. Moreover, this paper proposes a method to convert the force exerted by the telescopic rod motion on the moving platform into actuator torques. Thirdly, the dynamics model of the Delta robot with a telescopic rod is established, and numerical simulations are performed to demonstrate this approach. Finally, the influence of the telescopic rod on the actuator torques is verified using an experiment. A comparison is drawn between the two dynamics models used in torque feedforward control to validate the proposed dynamics model. Full article
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17 pages, 6151 KiB  
Article
Research on Game-Playing Agents Based on Deep Reinforcement Learning
by Kai Zhao, Jia Song, Yuxie Luo and Yang Liu
Robotics 2022, 11(2), 35; https://doi.org/10.3390/robotics11020035 - 18 Mar 2022
Cited by 7 | Viewed by 2336
Abstract
Path planning is a key technology for the autonomous mobility of intelligent robots. However, there are few studies on how to carry out path planning in real time under the confrontation environment. Therefore, based on the deep deterministic policy gradient (DDPG) algorithm, this [...] Read more.
Path planning is a key technology for the autonomous mobility of intelligent robots. However, there are few studies on how to carry out path planning in real time under the confrontation environment. Therefore, based on the deep deterministic policy gradient (DDPG) algorithm, this paper designs the reward function and adopts the incremental training and reward compensation method to improve the training efficiency and obtain the penetration strategy. The Monte Carlo experiment results show that the algorithm can effectively avoid static obstacles, break through the interception, and finally reach the target area. Moreover, the algorithm is also validated in the Webots simulator. Full article
(This article belongs to the Special Issue Robot Learning: Mapping from Perception to Action)
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23 pages, 4048 KiB  
Article
Online Deflection Compensation of a Flexible Hydraulic Loader Crane Using Neural Networks and Pressure Feedback
by Konrad Johan Jensen, Morten Kjeld Ebbesen and Michael Rygaard Hansen
Robotics 2022, 11(2), 34; https://doi.org/10.3390/robotics11020034 - 17 Mar 2022
Viewed by 3320
Abstract
The deflection compensation of a hydraulically actuated loader crane is presented. Measurement data from the laboratory are used to design a neural network deflection estimator. Kinematic expressions are derived and used with the deflection estimator in a feedforward topology to compensate for the [...] Read more.
The deflection compensation of a hydraulically actuated loader crane is presented. Measurement data from the laboratory are used to design a neural network deflection estimator. Kinematic expressions are derived and used with the deflection estimator in a feedforward topology to compensate for the static deflection. A dynamic deflection compensator is implemented, using pressure feedback and an adaptive bandpass filter. Simulations are conducted to verify the performance of the control system. Experimental results showcase the effectiveness of both the static and dynamic deflection compensator while running closed-loop motion control, with a 90% decrease in static deflection. Full article
(This article belongs to the Special Issue Mechatronics Systems and Robots)
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28 pages, 12593 KiB  
Article
Gait Analysis for a Tiltrotor: The Dynamic Invertible Gait
by Zhe Shen and Takeshi Tsuchiya
Robotics 2022, 11(2), 33; https://doi.org/10.3390/robotics11020033 - 16 Mar 2022
Cited by 7 | Viewed by 2510
Abstract
A conventional feedback-linearization-based controller, when applied to a tiltrotor (eight inputs), results in extensive changes in tilting angles, which are not expected in practice. To solve this problem, we introduce the novel concept of “UAV gait” to restrict the tilting angles. The gait [...] Read more.
A conventional feedback-linearization-based controller, when applied to a tiltrotor (eight inputs), results in extensive changes in tilting angles, which are not expected in practice. To solve this problem, we introduce the novel concept of “UAV gait” to restrict the tilting angles. The gait plan was initially used to solve the control problems in quadruped (four-legged) robots. Applying this approach, accompanied by feedback linearization, to a tiltrotor may give rise to the well-known non-invertible problem in the decoupling matrix. In this study, we explored invertible gait in a tiltrotor, and applied feedback linearization to stabilize the attitude and the altitude. The conditions necessary to achieve a full-rank decoupling matrix were deduced and simplified to near-zero roll and zero pitch. This paper proposes several invertible gaits to conduct an attitude–altitude control test. The accepted gaits within the region of interest were visualized. The simulation was conducted in Simulink, MATLAB. The results show promising responses in stabilizing attitude and altitude. Full article
(This article belongs to the Section Aerospace Robotics and Autonomous Systems)
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15 pages, 3008 KiB  
Article
An Analysis of Power Consumption of Fluid-Driven Robotic Arms Using Isotropy Index: A Proof-of-Concept Simulation-Based Study
by Yaser Maddahi and Kourosh Zareinia
Robotics 2022, 11(2), 32; https://doi.org/10.3390/robotics11020032 - 5 Mar 2022
Cited by 1 | Viewed by 3236
Abstract
The manipulability of a robotic arm may be defined based on ease of motion in different directions or ease of applying force/torque. In this study, we use manipulability measures to investigate how the kinematics of robots can be employed to calculate the optimal [...] Read more.
The manipulability of a robotic arm may be defined based on ease of motion in different directions or ease of applying force/torque. In this study, we use manipulability measures to investigate how the kinematics of robots can be employed to calculate the optimal power required to drive the actuation systems of their arms. We hypothesize that the isotropy measure is related to the power consumption of the robotic arm. In addition to theoretical aspects, we consider practical applications that can minimize power consumption in robotic systems. Since the method is simple to implement and has no assumption on the robot’s work environment or dependence on information on the main power supply, manipulability measures can be used as a tool to predict the power consumption of robotic manipulators. Full article
(This article belongs to the Section Medical Robotics and Service Robotics)
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21 pages, 1988 KiB  
Article
Kinematic Model Pruning: A Design Optimization Technique for Simultaneous Optimization of Topology and Geometry
by Hannes Gamper, Adrien Luthi, Hubert Gattringer, Andreas Mueller and Mario Di Castro
Robotics 2022, 11(2), 31; https://doi.org/10.3390/robotics11020031 - 4 Mar 2022
Viewed by 2488
Abstract
This paper presents a method of optimizing the design of robotic manipulators using a novel kinematic model pruning technique. The optimization departs from an predefined candidate linkage consisting of a initial topology and geometry. It allows simultaneously optimizing the degree of freedom, the [...] Read more.
This paper presents a method of optimizing the design of robotic manipulators using a novel kinematic model pruning technique. The optimization departs from an predefined candidate linkage consisting of a initial topology and geometry. It allows simultaneously optimizing the degree of freedom, the link lengths and other kinematic or dynamic performance criteria, while enabling the manipulator to follow the desired end-effector position and avoid collisions with the environment or itself. Current methods for design optimization rely on dedicated and complex frameworks, and solve the design optimization only as decoupled from each other in separate optimization problems. The proposed method only requires the introduction of a simple function, called a pruning function, as an objective function of an optimization problem. The introduced pruning function transforms a discrete topology optimization problem into a continuous problem that then can be solved simultaneously with other continuous objectives, using readily available optimization schemes. Two applications are presented: the optimization of a manipulator for the inspection of radio frequency cavities and a manipulator for maintenance within the future circular collider (FCC). Full article
(This article belongs to the Special Issue Kinematics and Robot Design IV, KaRD2021)
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13 pages, 2652 KiB  
Article
Novel Reconfigurable Spherical Parallel Mechanisms with a Circular Rail
by Pavel Laryushkin, Anton Antonov, Alexey Fomin and Victor Glazunov
Robotics 2022, 11(2), 30; https://doi.org/10.3390/robotics11020030 - 22 Feb 2022
Cited by 7 | Viewed by 3354
Abstract
The COVID-19 pandemic has placed unprecedented stress on the world healthcare system and demonstrated the need for modern automated robotic solutions for numerous medical applications. Often, robots that provide spherical motion of the end-effector are used in this area. In this paper, we [...] Read more.
The COVID-19 pandemic has placed unprecedented stress on the world healthcare system and demonstrated the need for modern automated robotic solutions for numerous medical applications. Often, robots that provide spherical motion of the end-effector are used in this area. In this paper, we discuss a spherical mechanism with a circular rail and provide several possible variations of the design: spherical robots with three or four legs and 4-DOF robots with an additional translational DOF, including a decoupled mechanism. The screw theory is used to analyze the mobility of the discussed mechanisms, and their advantages and drawbacks are discussed. Full article
(This article belongs to the Special Issue Service Robotics against COVID-2019 Pandemic)
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