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Machines
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Motion Planning and Advanced Control for Robotics
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Motion Planning and Advanced Control for Robotics

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 10487

Special Issue Editors

Dr. Jonathan Crespo

E-Mail Website
Guest Editor
Higher Technical School of Computer Engineering, UniversityRey Juan Carlos, 28933 Móstoles, Spain
Interests: mobile robots; ontologies; path planning; cognitive robotics
Prof. Dr. Ramon Barber

E-Mail Website
Guest Editor
System Engineering and Automation Division, Carlos III University, C/ Butarque 15, 28911 Leganés, Spain
Interests: mobile robotics; environment modelling; environment sensing; robot navigation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Motion planning and control are problems that need to be solved in robotics applications that involve movement, displacement, or some physical interaction with elements of the environment. Achieving optimal solutions for all tasks involved is a daunting challenge, but it entails making machines more efficient, more autonomous, and more prepared to be integrated into human environments.

 Therefore, new technologies or methods are required for developing tasks such as designing models of the robot and the environment for trajectory, path and task planning, for dynamic control, for gripping, for perceiving information from the environment useful for movement, and for the control of actuators.

This Special Issue aims to cover topics related to path planning, machine learning, task planning, mechanics and control, robotic gripping, mobile robot navigation, and position estimation. Contributions related to machine vision for environment classification are of particular interest.

These are interesting topics for all robots that move through the environment or need to interact with elements of the environment. In addition, due to the multidisciplinary nature of robotics, these topics fit into other areas within the scope of mechanics, such as mechanical engineering, computer engineering, and systems and control engineering.

Dr. Jonathan Crespo
Dr. Ramon Barber
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • path prediction
  • mobile robot
  • motion planning
  • robotic gripper
  • actuators and transmissions
  • autonomous robot
  • robot kinematics
  • path planning

Published Papers (7 papers)

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Research

24 pages, 9473 KiB  
Article
Trajectory Generator System for a UR5 Collaborative Robot in 2D and 3D Surfaces
by Alberto Adrián Toledano-García, Hugo René Pérez-Cabrera, Danya Ortega-Cabrera, David Navarro-Durán and Erick Mauricio Pérez-Hernández
Machines 2023, 11(9), 916; https://doi.org/10.3390/machines11090916 - 20 Sep 2023
Cited by 1 | Viewed by 1371
Abstract
In Industry 4.0., robots are regarded as one of the key components. In recent years, collaborative robots (cobots) have risen in relevance and have been included in the industry to perform tasks alongside humans. Robots have been used in many applications in manufacturing [...] Read more.
In Industry 4.0., robots are regarded as one of the key components. In recent years, collaborative robots (cobots) have risen in relevance and have been included in the industry to perform tasks alongside humans. Robots have been used in many applications in manufacturing processes; for the scope of this paper, the emphasis on these applications is centered on welding and gluing. These applications need to be performed with specific speed, efficiency, and accuracy to attain optimal welding or bonding to the pieces. An operator cannot maintain such conditions consistently, with minimum variations, for an extended period; hence, robots are a more suitable option to perform those tasks. The robots used for these applications need to be instructed to follow a trajectory to either weld or apply the glue. This path must be programmed on the robot by an operator, and depending on the complexity of the trajectory, it can take up to extended periods of time to set all the required waypoints. There are specialized software environments that contribute to the automation of these tasks; however, the overall cost of the licenses is not affordable if the scale of the project only requires developing and programming trajectories a few times. This paper contains a proposal for an open-source Computer Aided Manufacturing (CAM) software to automatically generate the trajectories needed for the aforementioned welding and gluing applications. The procedure to develop the software starts by selecting the surface that will be welded or to which glue will be applied. The surface determines the model of the trajectory to be followed. Next, a processing system is fed with the individual points that make up the trajectory provided by their selection over the Computer Aided Drawing (CAD) model. This system then creates a program based on URScript® that can be directly uploaded to and executed on the robot. A set of tests is presented to validate the applications and to demonstrate the versatility of the developed trajectory generation system. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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20 pages, 2086 KiB  
Article
Advanced System for Enhancing Location Identification through Human Pose and Object Detection
by Medrano A. Kevin, Jonathan Crespo, Javier Gomez and César Alfaro
Machines 2023, 11(8), 843; https://doi.org/10.3390/machines11080843 - 18 Aug 2023
Viewed by 1042
Abstract
Location identification is a fundamental aspect of advanced mobile robot navigation systems, as it enables establishing meaningful connections between objects, spaces, and actions. Understanding human actions and accurately recognizing their corresponding poses play pivotal roles in this context. In this paper, we present [...] Read more.
Location identification is a fundamental aspect of advanced mobile robot navigation systems, as it enables establishing meaningful connections between objects, spaces, and actions. Understanding human actions and accurately recognizing their corresponding poses play pivotal roles in this context. In this paper, we present an observation-based approach that seamlessly integrates object detection algorithms, human pose detection, and machine learning techniques to effectively learn and recognize human actions in household settings. Our method entails training machine learning models to identify the common actions, utilizing a dataset derived from the interaction between human pose and object detection. To validate our approach, we assess its effectiveness using a diverse dataset encompassing typical household actions. The results demonstrate a significant improvement over existing techniques, with our method achieving an accuracy of over 95% in classifying eight different actions within household environments.. Furthermore, we ascertain the robustness of our approach through rigorous testing in real-world environments, demonstrating its ability to perform well despite the various challenges of data collection in such settings. The implications of our method for robotic applications are significant, as a comprehensive understanding of human actions is essential for tasks such as semantic navigation. Moreover, our findings unveil promising opportunities for future research, as our approach can be extended to learn and recognize a wide range of other human actions. This perspective, which highlights the potential leverage of these techniques, provides an encouraging path for future investigations in this field. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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34 pages, 4400 KiB  
Article
Design and Stability Analysis of Sliding Mode Controller for Non-Holonomic Differential Drive Mobile Robots
by Ahmad Taher Azar, Azher M. Abed, Farah Ayad Abdul-Majeed, Ibrahim A. Hameed, Anwar Ja’afar Mohamad Jawad, Wameedh Riyadh Abdul-Adheem, Ibraheem Kasim Ibraheem and Nashwa Ahmad Kamal
Machines 2023, 11(4), 470; https://doi.org/10.3390/machines11040470 - 11 Apr 2023
Cited by 4 | Viewed by 1353
Abstract
This paper presents a novel extended state observer (ESO) approach for a class of plants with nonlinear dynamics. The proposed observer estimates both the state variables and the total disturbance, which includes both exogenous and endogenous disturbance. The study’s changes can be summarized [...] Read more.
This paper presents a novel extended state observer (ESO) approach for a class of plants with nonlinear dynamics. The proposed observer estimates both the state variables and the total disturbance, which includes both exogenous and endogenous disturbance. The study’s changes can be summarized by developing a sliding mode higher-order extended state observer with a higher-order augmented state and a nonlinear function for the estimation error correction terms (SMHOESO). By including multiple enhanced states, the proposed observer can monitor total disturbances asymptotically, with the second derivative of the total disturbance serving as an upper constraint on the estimation error. This feature improves the observer’s ability to estimate higher-order disturbances and uncertainty. To extend the concept of the linear extended state observer (LESO), a nonlinear function can modify the estimation error in such a way that the proposed observer can provide faster and more accurate estimations of the state and total disturbance. The proposed nonlinearity also reduces the chattering issue with LESOs. This research thoroughly examines and analyzes the proposed SMHOESO’s convergence using the Lyapunov technique. According to this analysis, the SMHOESO is asymptotically stable, and the estimation error can be significantly reduced under real-world conditions. In addition to the SMHOESO, a modified Active Disturbance Rejection Control (ADRC) scheme is built, which includes a nonlinear state error feedback (NLSEF) controller and a nonlinear tracking differentiator (TD). Several nonlinear models, including the Differential Drive Mobile Robot (DDMR), are numerically simulated, and the proposed SMHOESO is compared to several alternative types, demonstrating a significant reduction in controller energy, increased control signal smoothness, and accurate tracking of the reference signal. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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16 pages, 2059 KiB  
Article
Fixed-Time Sliding Mode-Based Active Disturbance Rejection Tracking Control Method for Robot Manipulators
by Anh Tuan Vo, Thanh Nguyen Truong, Quang Dan Le and Hee-Jun Kang
Machines 2023, 11(2), 140; https://doi.org/10.3390/machines11020140 - 19 Jan 2023
Cited by 3 | Viewed by 1296
Abstract
This work investigates the issue of a hybrid trajectory tracking control algorithm (HTCA) for robot manipulators (RMs) with uncertain dynamics and the effect of external disturbances. Following are some proposals for achieving the control target. Firstly, to achieve the active disturbance rejection, we [...] Read more.
This work investigates the issue of a hybrid trajectory tracking control algorithm (HTCA) for robot manipulators (RMs) with uncertain dynamics and the effect of external disturbances. Following are some proposals for achieving the control target. Firstly, to achieve the active disturbance rejection, we propose a uniform second-order sliding mode disturbance observer (USOSMDO) to obtain directly the lumped uncertainties without their prior upper-bound information. Secondly, a fixed-time singularity-free terminal sliding surface (FxSTSS) is proposed to obtain a fixed-time convergence of the tracking control error (TCE) without the singularity in the control input. Then, using information on the proposed USOSMDO, our HTCA is formed based on the FxSTSS and the fixed-time power rate reaching law (FxPRRL). The control proposal not only stabilizes with the global fixed-time convergence but also attains high tracking accuracy. In addition, the chattering problem also is handled almost completely. Finally, numerical simulations verify the effectiveness and advantages of applying the proposed HTCA to a FARA robot. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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15 pages, 4327 KiB  
Article
Unknown Slope-Oriented Research on Model Predictive Control for Quadruped Robot
by Zhitong Zhang, Honglei An, Xiaojian Wei and Hongxu Ma
Machines 2023, 11(2), 133; https://doi.org/10.3390/machines11020133 - 18 Jan 2023
Cited by 1 | Viewed by 1474
Abstract
There are many undulating terrains in the wild environment. In order to realize the adaptive and stable walking of quadruped robots on unknown sloped terrain, a slope-adaptability model predictive control (SAMPC) algorithm is proposed in this work. In the absence of external vision [...] Read more.
There are many undulating terrains in the wild environment. In order to realize the adaptive and stable walking of quadruped robots on unknown sloped terrain, a slope-adaptability model predictive control (SAMPC) algorithm is proposed in this work. In the absence of external vision sensors, the orientation and inclination of the slope are estimated based on the joint position sensors and inertial measurement units (IMU). In an effort to increase the stability margin, the adaptive algorithm adjusts the attitude angle and the touch-down point of the swing leg. To reduce the slipping risk, a nonlinear control law is designed to determine the friction factor of the friction cone constraint from the inclination of the slope. We validate the effectiveness of the framework through a series of simulations. The automatic smooth transition from the flat to the unknown slope is achieved, and the robot is capable of walking in all directions on the slope. Notably, with reference to the climbing modal of blue sheep, the robot successfully climbed a 42.4° slope, proving the ultimate ability of the proposed framework. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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15 pages, 2299 KiB  
Article
Path Planning of Autonomous 3-D Scanning and Reconstruction for Robotic Multi-Model Perception System
by Chongshan Fan, Hongpeng Wang, Zhongzhi Cao, Xinwei Chen and Li Xu
Machines 2023, 11(1), 26; https://doi.org/10.3390/machines11010026 - 26 Dec 2022
Cited by 2 | Viewed by 1874
Abstract
Applying a three-dimensional (3-D) reconstruction from mapping-oriented offline modeling to intelligent agent-oriented environment understanding and real-world environment construction oriented to agent autonomous behavior has important research and application value. Using a scanner to scan objects is a common way to obtain a 3-D [...] Read more.
Applying a three-dimensional (3-D) reconstruction from mapping-oriented offline modeling to intelligent agent-oriented environment understanding and real-world environment construction oriented to agent autonomous behavior has important research and application value. Using a scanner to scan objects is a common way to obtain a 3-D model. However, the existing scanning methods rely heavily on manual work, fail to meet efficiency requirements, and are not sufficiently compatible with scanning objects of different sizes. In this article, we propose a creative visual coverage path planning approach for the robotic multi-model perception system (RMMP) in a 3-D environment under photogrammetric constraints. To realize the 3-D scanning of real scenes automatically, we designed a new robotic multi-model perception system. To reduce the influence of image distortion and resolution loss in 3-D reconstruction, we set scanner-to-scene projective geometric constraints. To optimize the scanning efficiency, we proposed a novel path planning method under photogrammetric and kinematics constraints. Under the RMMP system, a constraints-satisfied coverage path could be generated, and the 3-D reconstruction from the images collected along the way was carried out. In this way, the autonomous planning of the pose of the end scanner in scanning tasks was effectively solved. Experimental results show that the RMMP-based 3-D visual coverage method can improve the efficiency and quality in 3-D reconstruction. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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27 pages, 9687 KiB  
Article
Variable Dimensional Scaling Method: A Novel Method for Path Planning and Inverse Kinematics
by Longfei Jia, Zhiyuan Yu, Haiping Zhou, Zhe Pan, Yangsheng Ou, Yaxing Guo and Yuping Huang
Machines 2022, 10(11), 1030; https://doi.org/10.3390/machines10111030 - 04 Nov 2022
Cited by 3 | Viewed by 1206
Abstract
Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse [...] Read more.
Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse kinematics of HRM is proposed in this paper: the variable dimension scaling method (VDSM), which can solve complex inverse kinematics while avoiding obstacles. Through this method, the path of the end-effector is scaled under a certain proportion and is adjusted depending on the position of the obstacle, which has good universality. The number of link angles changed is as small as possible in the process of achieving the end-effector moving along the desired path. With the redundancy of HRM, obstacle avoidance can be implemented in any environment by the proposed method. Through simulation and experiments in different environments, the above advantages of VDSM are verified. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
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