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

Meng Ding, Xianjie Zheng, Liaoxue Liu, Jian Guo, Yu Guo

Year
2024
Citations
23

Abstract

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

Motion planningCollisionRobotPath (computing)Field (mathematics)Potential fieldComputer scienceEngineeringSimulationArtificial intelligence

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