Abstract:
Continuum robots, characterized by their high flexibility and infinite degrees of freedom (DoFs), have gained prominence in applications such as minimally invasive surger...Show MoreMetadata
Abstract:
Continuum robots, characterized by their high flexibility and infinite degrees of freedom (DoFs), have gained prominence in applications such as minimally invasive surgery and hazardous environment exploration. However, the intrinsic complexity of continuum robots requires a significant amount of time for their motion planning, posing a hurdle to their practical implementation. To tackle these challenges, efficient motion planning methods such as Rapidly Exploring Random Trees (RRT) and its variant, RRT*, have been employed. This paper introduces a unique RRT*-based motion control method tailored for continuum robots. Our approach embeds safety constraints derived from the robots’ posture states, facilitating autonomous navigation and obstacle avoidance in rapidly changing environments. Simulation results show efficient trajectory planning amidst multiple dynamic obstacles and provide a robust performance evaluation based on the generated postures. Finally, preliminary tests were conducted on a two-segment cable-driven continuum robot prototype, confirming the effectiveness of the proposed planning approach. This method is versatile and can be adapted and deployed for various types of continuum robots through parameter adjustments.
Date of Conference: 13-17 May 2024
Date Added to IEEE Xplore: 08 August 2024
ISBN Information:
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Jiaxing Research Institute, Southern University of Science and Technology, Jiaxing, China
Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Contents Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
Jiaxing Research Institute, Southern University of Science and Technology, Jiaxing, China
Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China
