基于改进型人工势场的缆索驱动连续机器人无碰撞路径规划

IF 1.9 4区 计算机科学 Q3 ROBOTICS Robotica Pub Date : 2024-03-05 DOI:10.1017/s026357472400016x
Meng Ding, Xianjie Zheng, Liaoxue Liu, Jian Guo, Yu Guo
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引用次数: 0

摘要

连续机器人因其卓越的灵巧性、灵活性和对受限环境的适用性而成为研究热点。然而,如何有效、安全、准确地规划连续体机器人的路径仍然是一个具有挑战性的问题,由于其在受限环境中的冗余性,很难选择合适的逆运动学解决方案。本文提出了一种基于改进人工势场(APF)的电缆驱动连续体机器人无碰撞路径规划方法,其中采用甲虫触角搜索算法来处理 APF 的最优问题,而无需速度运动学。此外,传统 APF 的局部最优问题是通过天线方向矢量的随机性来解决的,这使得算法很容易跳出局部最小值。仿真和实验结果验证了所提路径规划方法的高效性。
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Collision-free path planning for cable-driven continuum robot based on improved artificial potential field

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.

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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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