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基于贝塞尔曲线的蠕虫状机器人避障路径规划

Obstacle Avoidance Path Planning for Worm-like Robot Using Bézier Curve.

作者信息

Wang Yifan, Liu Zehao, Kandhari Akhil, Daltorio Kathryn A

机构信息

Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.

出版信息

Biomimetics (Basel). 2021 Sep 30;6(4):57. doi: 10.3390/biomimetics6040057.

DOI:10.3390/biomimetics6040057
PMID:34698058
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8544220/
Abstract

Worm-like robots have demonstrated great potential in navigating through environments requiring body shape deformation. Some examples include navigating within a network of pipes, crawling through rubble for search and rescue operations, and medical applications such as endoscopy and colonoscopy. In this work, we developed path planning optimization techniques and obstacle avoidance algorithms for the peristaltic method of locomotion of worm-like robots. Based on our previous path generation study using a modified rapidly exploring random tree (RRT), we have further introduced the Bézier curve to allow more path optimization flexibility. Using Bézier curves, the path planner can explore more areas and gain more flexibility to make the path smoother. We have calculated the obstacle avoidance limitations during turning tests for a six-segment robot with the developed path planning algorithm. Based on the results of our robot simulation, we determined a safe turning clearance distance with a six-body diameter between the robot and the obstacles. When the clearance is less than this value, additional methods such as backward locomotion may need to be applied for paths with high obstacle offset. Furthermore, for a worm-like robot, the paths of subsequent segments will be slightly different than the path of the head segment. Here, we show that as the number of segments increases, the differences between the head path and tail path increase, necessitating greater lateral clearance margins.

摘要

蠕虫状机器人在需要身体形状变形的环境中导航已展现出巨大潜力。一些例子包括在管道网络中导航、在废墟中爬行以进行搜索和救援行动,以及诸如内窥镜检查和结肠镜检查等医学应用。在这项工作中,我们针对蠕虫状机器人的蠕动运动方式开发了路径规划优化技术和避障算法。基于我们之前使用改进的快速扩展随机树(RRT)进行的路径生成研究,我们进一步引入了贝塞尔曲线,以提供更大的路径优化灵活性。使用贝塞尔曲线,路径规划器可以探索更多区域,并获得更大的灵活性以使路径更平滑。我们使用所开发的路径规划算法计算了六段式机器人转弯测试期间的避障限制。基于我们的机器人模拟结果,我们确定了机器人与障碍物之间具有六个身体直径的安全转弯间隙距离。当间隙小于此值时,对于具有高障碍物偏移的路径,可能需要应用诸如向后移动等额外方法。此外,对于蠕虫状机器人,后续节段的路径将与头部节段的路径略有不同。在此,我们表明随着节段数量的增加,头部路径和尾部路径之间的差异会增大,这就需要更大水平间隙余量。

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本文引用的文献

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Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning.基于三角不等式的改进RRT-Connect算法用于机器人路径规划
Sensors (Basel). 2021 Jan 6;21(2):333. doi: 10.3390/s21020333.
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An Analysis of Peristaltic Locomotion for Maximizing Velocity or Minimizing Cost of Transport of Earthworm-Like Robots.用于使类蚯蚓机器人速度最大化或运输成本最小化的蠕动运动分析。
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Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot.
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基于快速扩展随机树算法的蠕虫状机器人路径规划
Biomimetics (Basel). 2020 Jun 5;5(2):26. doi: 10.3390/biomimetics5020026.
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