Motion Control of Soft Robots
- 1st Edition - August 8, 2025
- Latest edition
- Authors: Wenyu Liang, Jiawei Cao, Qinyuan Ren, Wenxin Zhu
- Language: English
Motion Control of Soft Robots provides an overview of the general concepts and most recent technological updates in soft robot motion control. The book provides systemati… Read more
Motion Control of Soft Robots provides an overview of the general concepts and most recent technological updates in soft robot motion control. The book provides systematic coverage of theoretical and practical aspects in system modeling and motion control strategies, presenting novel ideas, methods, and future outlook related to motion control of soft actuators and robots, including model-based control, model-free control, and bioinspired control. This book is useful for researchers, engineers, and students of robotics who can expect to learn how to design and implement various techniques to obtain solutions to control problems in soft robot control and nonlinear system control.
- Gives an overview of soft robotics, the modeling approaches for soft robots, as well as motion control techniques for soft robots like model-based control, model-free control, and bioinspired control
- Investigates recent novel ideas and methods for the design and implantation of motion control for soft actuators/robots
- Presents several soft robot designs, using them as examples to illustrate the controller design for soft robots where detailed simulation or/and experimental results are given
Researchers and robotics engineers in Biomedical Engineering, Control Engineering, Robotics and Automation, Soft Robots, and Motion Control, also postgraduate students studying Robotics and Mechatronics
1. Introduction
1.1 Overview
1.2 Soft Robots
1.3 Modelling
1.3.1 Analytical Modelling Approaches
1.3.2 Empirical Modelling Approaches
1.4 Motion Control
1.4.1 Feedforward Control
1.4.2 Feedback Control
1.5 Organization of the Book
Reference
2. Soft Actuator Motion Control
2.1 Model-Based Control
2.2 Model-Free Control
2.3 Bioinspired Control
2.4 Chapter Summary
References
3. Robust Motion Control of a Soft Inchworm Robot
3.1 Introduction
3.2 System Description
3.2.1 Robot Design
3.2.2 Robot-Motion Kinematics Analysis
3.2.3 Robot Modelling
3.3 Controller Design
3.3.1 Model-Based Forward Controller
3.3.2 PID-Based Feedback Controller
3.3.3 Disturbance Observer-Based Compensation
3.4 Experiments and Results
3.4.1 Experimental System Setup
3.4.2 Experimental Results
3.5 Chapter Summary
References
4. Bioinspired Approach for Motion Control of a Soft Actuator
4.1 Introduction
4.2 Problem Formulation
4.3 Controller Design
4.3.1 Cerebellum-Inspired Controller
4.3.2 Stability Analysis
4.4 Experiments and Results
4.4.1 Experimental Results without Disturbance
4.4.2 Experimental Results with Disturbance
4.4.3 Discussions
4.5 Chapter Summary
References
5. Motion Control of a Circular Soft Robot via Iterative Learning Control
5.1 Introduction
5.2 System Description
5.2.1 Robot Design
5.2.2 Locomotion Analysis
5.2.3 Knowledge-Based Modelling
5.3 Controller Design
5.4 Numerical Study
5.5 Experiments and Results
5.5.1 Experimental System Setup
5.5.2 Experimental Results
5.6 Chapter Summary
References
6. Motion Control of a Manipulator Based on Dielectric Elastomer Actuators in Antagonistic Pairs
6.1 Introduction
6.2 System Description
6.2.1 Mechanical Design
6.2.2 Kinetics Analysis
6.3 Controller Design
6.3.1 Cerebellar Model Articulation Controller
6.3.2 Compensation Controller
6.3.3 Stability Analysis
6.3.4 Overall Controller
6.4 Experiments and Results
6.4.1 Prototype
6.4.2 Experimental Results
6.5 Chapter Summary
References
7. Intelligent Motion Control of Antagonistic McKibben Muscles
7.1 Introduction
7.2 System Description
7.2.1 Mechanical Design
7.2.2 System Modelling
7.3 Controller Design
7.3.1 Cerebellar Control Loop
7.3.2 Cerebellum‑Like Controller Based on Spiking Neural Network
7.4 Numerical Study
7.4.1 Simulation Setup
7.4.2 Simulation Results
7.5 Experiments and Results
7.5.1 Experimental System Setup
7.5.2 Experimental Results
7.6 Chapter Summary
References
8. Learning-Based Motion Control of a Dielectric Elastomer Actuator-Driven Mobile Robot
8.1 Introduction
8.2 System Description
8.2.1 Robot Design
8.2.2 Morphology Analysis
8.3 Controller Design
8.3.1 Learning-Based Motion Control of a Soft Actuator
8.3.2 Reinforcement Learning-Based Robot Motion Planning
8.3.3 Overall Framework
8.4 Numerical Study
8.5 Experiments and Results
8.5.1 Experimental System Setup
8.5.2 Experimental Results
8.6 Chapter Summary
References
Conclusion
1.1 Overview
1.2 Soft Robots
1.3 Modelling
1.3.1 Analytical Modelling Approaches
1.3.2 Empirical Modelling Approaches
1.4 Motion Control
1.4.1 Feedforward Control
1.4.2 Feedback Control
1.5 Organization of the Book
Reference
2. Soft Actuator Motion Control
2.1 Model-Based Control
2.2 Model-Free Control
2.3 Bioinspired Control
2.4 Chapter Summary
References
3. Robust Motion Control of a Soft Inchworm Robot
3.1 Introduction
3.2 System Description
3.2.1 Robot Design
3.2.2 Robot-Motion Kinematics Analysis
3.2.3 Robot Modelling
3.3 Controller Design
3.3.1 Model-Based Forward Controller
3.3.2 PID-Based Feedback Controller
3.3.3 Disturbance Observer-Based Compensation
3.4 Experiments and Results
3.4.1 Experimental System Setup
3.4.2 Experimental Results
3.5 Chapter Summary
References
4. Bioinspired Approach for Motion Control of a Soft Actuator
4.1 Introduction
4.2 Problem Formulation
4.3 Controller Design
4.3.1 Cerebellum-Inspired Controller
4.3.2 Stability Analysis
4.4 Experiments and Results
4.4.1 Experimental Results without Disturbance
4.4.2 Experimental Results with Disturbance
4.4.3 Discussions
4.5 Chapter Summary
References
5. Motion Control of a Circular Soft Robot via Iterative Learning Control
5.1 Introduction
5.2 System Description
5.2.1 Robot Design
5.2.2 Locomotion Analysis
5.2.3 Knowledge-Based Modelling
5.3 Controller Design
5.4 Numerical Study
5.5 Experiments and Results
5.5.1 Experimental System Setup
5.5.2 Experimental Results
5.6 Chapter Summary
References
6. Motion Control of a Manipulator Based on Dielectric Elastomer Actuators in Antagonistic Pairs
6.1 Introduction
6.2 System Description
6.2.1 Mechanical Design
6.2.2 Kinetics Analysis
6.3 Controller Design
6.3.1 Cerebellar Model Articulation Controller
6.3.2 Compensation Controller
6.3.3 Stability Analysis
6.3.4 Overall Controller
6.4 Experiments and Results
6.4.1 Prototype
6.4.2 Experimental Results
6.5 Chapter Summary
References
7. Intelligent Motion Control of Antagonistic McKibben Muscles
7.1 Introduction
7.2 System Description
7.2.1 Mechanical Design
7.2.2 System Modelling
7.3 Controller Design
7.3.1 Cerebellar Control Loop
7.3.2 Cerebellum‑Like Controller Based on Spiking Neural Network
7.4 Numerical Study
7.4.1 Simulation Setup
7.4.2 Simulation Results
7.5 Experiments and Results
7.5.1 Experimental System Setup
7.5.2 Experimental Results
7.6 Chapter Summary
References
8. Learning-Based Motion Control of a Dielectric Elastomer Actuator-Driven Mobile Robot
8.1 Introduction
8.2 System Description
8.2.1 Robot Design
8.2.2 Morphology Analysis
8.3 Controller Design
8.3.1 Learning-Based Motion Control of a Soft Actuator
8.3.2 Reinforcement Learning-Based Robot Motion Planning
8.3.3 Overall Framework
8.4 Numerical Study
8.5 Experiments and Results
8.5.1 Experimental System Setup
8.5.2 Experimental Results
8.6 Chapter Summary
References
Conclusion
- Edition: 1
- Latest edition
- Published: August 8, 2025
- Language: English
WL
Wenyu Liang
Wenyu Liang is a scientist at the Institute for Infocomm Research, A*STAR, Singapore, and an adjunct assistant professor in the Department of Electrical and Computer Engineering, National University of Singapore. He has authored or co-authored over 90 publications, including one book, two book chapters and more than 40 published journal papers. He has also received several awards related to innovation such as Merit Award, Tan Kah Kee Young Inventors’ Award 2016: Open Section, etc. His research interests mainly include robotics, precision motion control, and force/tactile control with applications in industrial, medical, and agricultural technology.
Affiliations and expertise
Scientist, Institute for Infocomm Research, Fusionopolis Way, Connexis North Tower, Singapore. Adjunct Assistant Professor, Department of Electrical and Computer Engineering, National University of Singapore (NUS), Engineering Drive, SingaporeJC
Jiawei Cao
Jiawei Cao is a research scientist at Temasek Laboratories, National University of Singapore. He has authored and co-authored more than 20 publications on robotics, including highly ranked journal papers and top conference papers. He also serves as reviewers for several international journals and top conferences. His research interests include soft robotics, bioinspired motion control, multi-robot systems, multi-agent reinforcement learning and autonomous navigation.
Affiliations and expertise
Research Scientist, Temasek Laboratories, National University of Singapore (NUS), SingaporeQR
Qinyuan Ren
Qinyuan Ren is a robotics scientist at the Institute for Infocomm Research (I2R), A*STAR, in Singapore, and professor at the College of Control Science and Engineering, Zhejiang University, in China. He is a principal investigator (PI) of several national Mega-fund projects and serves as the editorial member for two international journals. He is a Senior IEEE Member now and his research interests include nonlinear systems, bioinspired and biomimetic robotics, motion control and artificial nervous system.
Affiliations and expertise
Scientist, Institute for Infocomm Research (I2R), Fusionopolis Way, Connexis North Tower, Singapore.Professor, College of Control Science and Engineering, Zhejiang University (Yuquan Campus), Hangzhou, Zhejiang, P. R. ChinaWZ
Wenxin Zhu
Wenxin Zhu is a PhD candidate at the College of Control Science and Engineering, Zhejiang University, China. She served as a research assistant at the Institute for Infocomm Research, A*STAR, Singapore from 2023 to 2024 and was involved in organizing several international conferences. Her research interests include motion control, human-robot interaction, and soft robotics.
Affiliations and expertise
PhD candidate at the College of Control Science and Engineering, Zhejiang University, ChinaRead Motion Control of Soft Robots on ScienceDirect