Motion Planning, Trajectory Prediction, and Control for Robotics—2nd Edition

A Special Issue of Actuators (ISSN 2076-0825) belonging to the section "Control Systems".

Deadline for manuscript submissions: 20 March 2027 | Viewed by 1055

Editors


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Guest Editor
Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China
Interests: motion planning and control; mobile robots; teleoperated robots
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E-Mail Website
Guest Editor
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Interests: hydraulic transmission and control; robotics; mechatronics; nonlinear control; adaptive and robust control
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China
Interests: networked robots; teleoperation; human–robot interaction; safety-critical control of robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are delighted to invite you to participate in the second edition of this Special Issue, entitled “Motion Planning, Trajectory Prediction, and Control for Robotics—2nd Edition”.

Motion planning and control are fundamental techniques for intelligent robotic systems, thus becoming hotspots in the robotics field. Practical robotic systems, including manipulators and ground/aerial/underwater/legged mobile robots, are activated by a variety of actuators such as electrical motors and electro-hydraulic units. These actuators, in practice, are subject to various modeling uncertainties and a number of physical constraints including kinematic and dynamic constraints, which pose significant challenges on the motion planning and control of a robotic system. Therefore, it is crucial to develop advanced motion planning and control strategies considering these modeling uncertainties and physical constraints, inspiring this Special Issue.

This Special Issue invites relevant robotic researchers to share their most recent achievements in motion planning, trajectory prediction, and control for robotic systems. Original papers reporting novel approaches and significant results are welcome.

This Special Issue focuses on topics including but not limited to the following:

Collision-avoidance path planning; optimal trajectory planning; trajectory prediction in human/environment/robot interactions; system modeling and identification; advanced robotic motion/force control; and human–robot interaction control.

Dr. Mingxing Yuan
Dr. Wenxiang Deng
Dr. Yuling Li
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators 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

  • motion planning
  • motion/force control
  • human–robot interaction
  • trajectory prediction

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Published Papers (1 paper)

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Research

17 pages, 8475 KB  
Article
Asymptotic Stabilization Control Based on Trajectory Optimization for Vertical Underactuated Manipulators with the First Joint Actuator
by Yufei Chen, Lejun Wang, Bin He, Lei Qin and Yu Gao
Actuators 2026, 15(4), 221; https://doi.org/10.3390/act15040221 - 16 Apr 2026
Viewed by 579
Abstract
Underactuated system control is a central topic in nonlinear system control. For the three-link vertical underactuated manipulator with only the first joint actuated (APP manipulator), the control objective of swing-up and balancing is challenging. The advantages of this paper are as follows: (i) [...] Read more.
Underactuated system control is a central topic in nonlinear system control. For the three-link vertical underactuated manipulator with only the first joint actuated (APP manipulator), the control objective of swing-up and balancing is challenging. The advantages of this paper are as follows: (i) The proposed method avoids balancing region division in common partitioned control, preventing failure to stabilize at the target position due to improper partitioning. (ii) The time-based switching condition optimized via parameter tuning is easier to satisfy than the state-based condition. (iii) The proposed controller effectively suppresses state fluctuations caused by switching, yielding a smoother transition. (iv) The proposed controller avoids the singularity problem. The main procedures are as follows. First, the dynamic model of the APP manipulator is established. Then, a trajectory is designed to guide the active link from the initial position to the vicinity of the target position. On this basis, to ensure that all links can simultaneously reach the vicinity of the target position, the trajectory parameters are optimized according to the coupling relationship between the links. Next, an NFTSM-based tracking controller is developed to steer the links along the optimized trajectory. After that, an LQR-based stabilization controller is further employed to lock the system at the target position. Finally, the effectiveness of the proposed method is verified through simulations. Full article
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