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Collision-free path planning for cable-driven continuum robot based on improved artificial potential field

Published online by Cambridge University Press:  05 March 2024

Meng Ding ,
Xianjie Zheng ,
Liaoxue Liu ,
Jian Guo  and
Yu Guo Open the ORCID record for Yu Guo [Opens in a new window]
Meng Ding
Affiliation:
School of Automation, Nanjing University of Science and Technology, Nanjing China
Xianjie Zheng
Affiliation:
School of Automation, Nanjing University of Science and Technology, Nanjing China
Liaoxue Liu
Affiliation:
School of Automation, Nanjing University of Science and Technology, Nanjing China
Jian Guo
Affiliation:
School of Automation, Nanjing University of Science and Technology, Nanjing China
Yu Guo*
Affiliation:
School of Automation, Nanjing University of Science and Technology, Nanjing China
*
Corresponding author: Yu Guo; Email: guoyu@njust.edu.cn
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Abstract

Continuum robot has become a research hotspot due to its excellent dexterity, flexibility and applicability to constrained environments. However, the effective, secure and accurate path planning for the continuum robot remains a challenging issue, for that it is difficult to choose a suitable inverse kinematics solution due to its redundancy in the confined environment. This paper presents a collision-free path planning method based on the improved artificial potential field (APF) for the cable-driven continuum robot, in which the beetle antennae search algorithm is adopted to deal with the optimal problem of APF without the necessary for velocity kinematics. In addition, the local optimum problem of traditional APF is solved by the randomness of the antennae’s direction vector which can make the algorithm easily jump out of local minima. The simulation and experimental results verify the efficiency of the proposed path planning method.

Keywords

continuum robotcollision-free path planningartificial potential fieldbeetle antennae search

Information

Type
Research Article
Information
Robotica , Volume 42 , Issue 5 , May 2024 , pp. 1350 - 1367
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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