Special Issue "Advances in the Fabrication, Sensing, Modelling, and Control of Soft Robots"
Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 901
Interests: nonlinear optimization; metaheuristic algorithms; and machine learning
Interests: AI; machine learning; control algorithms; robotics; nonlinear optimization; control
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Topics: Intelligent Systems and Robotics
Interests: nonlinear and robust control; Anti-windup design and implementation
Interests: unmanned system control; machine vision; robotics; data mining; intelligent optimization algorithms
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In recent decades, research on soft robots has gained substantial attention from researchers across the field. Because of their inherent flexibility, soft robots present a natural solution for several problems posed by traditional rigid robots. For example, in human–robot interactions, the safety of the human user is of the utmost importance; soft robots have an inherent advantage in terms of safety, reliability, and user experience compared with rigid metallic robots. Even in the case of a malfunction, soft robots pose no critical concern. Reaching the same level of safety and reliability with traditional rigid robots requires complex sensing and control mechanisms. Additionally, soft robots offer a “human-like” experience to the user, an essential feature for developing friendly human–robot interactions. These features make soft robots ideal for medical rehabilitation robots and an industrial gripper for manipulating delicate objects. Despite their benefits, soft robots have proven to be extremely challenging for accurate analytical modeling and dynamic control. Their flexible structure imparts an infinite degree of freedom, making it challenging to develop a rigorous theoretical framework to study their behavior. They are usually modeled using some degree of approximation, such as finite element methods (FEM). However, the FEM-based technique is not helpful for real-time control. Model-free control techniques avoid the issues of modeling altogether, but they suffer when it comes to regulating the dynamic response and avoiding undesirable transients. Recently, some works have been proposed that leverage model-identification techniques to fit the experimental data from the robot. Such methods have the advantage of capturing specific characteristics of soft robotic systems not utilized by model-free techniques. Developing resilient, long-lasting, and self-healing fabrication materials along with novel actuation and sensing mechanisms is also an important research direction for soft robotics. Because of their structure, soft robots cannot use traditional robotic components, e.g., motors and rigid links. They are usually actuated using a pneumatic setup using air pressure regulation. The current actuation mechanisms are quite bulky, resulting in reduced portability of soft robots. Developing portable actuation mechanisms requires research attention.
This Special Issue is proposed to review the state-of-the-art development of recent years, introduce the current progress, and present a future roadmap for research related to soft robots. Topics of interest include, but are not limited to, the following:
- Dynamic response regulation for pneumatically actuated soft robots.
- Dynamic model estimation for soft robotic systems.
- Model-free techniques for the control of soft robots.
- Analysis of the stability and robustness of dynamic control laws for soft robots.
- Novel actuation mechanisms for soft robots.
- Soft electronics-based sensing mechanisms for soft robots.
- Adaptive control for real-time model estimation and control of soft robots.
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Dr. Ameer Hamza Khan
Prof. Dr. Shuai Li
Prof. Dr. Muhammad Rehan
Prof. Dr. Dechao Chen
Manuscript Submission Information
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- soft robotics
- control theory
- nonlinear models
- 3D modeling
- flexible robots