Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot
Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot
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DOI：
10.3390/biomimetics5020026
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发表时间：
2020-06-01
期刊：
影响因子：
4.5
通讯作者：
Daltorio, Kathryn A.
中科院分区：
文献类型：
--
作者：
Wang, Yifan;Pandit, Prathamesh;Daltorio, Kathryn A.
受蚯蚓的启发，蠕虫状机器人利用蠕动波移动。虽然已经有关于产生和优化螺旋波的研究，但这种蠕虫状机器人的路径规划还没有得到很好的探索。在本文中，我们评估快速探索随机树（RRT）算法的蠕虫状机器人的路径规划。蠕动运动的运动学约束的潜力，以非完整的方式，如果避免滑动转向。在这里，我们表明，添加一个椭圆形的路径生成算法，特别是两步增强算法，同时向前和向后搜索路径，可以使规划这样的波可行和有效的减少所需的迭代约2个数量级。有了这个路径规划器，就有可能计算波的数量，以达到空间中位置和方向的任意组合。这揭示了位形空间中的边界，可以用来确定在机动之前是继续前进还是后退，就像平行停车的蠕虫一样。横向移动身体所需的大量波浪，即使是一个单一的身体宽度，表明横向运动的策略，围绕障碍物的规划和响应行为将是未来蠕虫状机器人的重要。
Inspired by earthworms, worm-like robots use peristaltic waves to locomote. While there has been research on generating and optimizing the peristalsis wave, path planning for such worm-like robots has not been well explored. In this paper, we evaluate rapidly exploring random tree (RRT) algorithms for path planning in worm-like robots. The kinematics of peristaltic locomotion constrain the potential for turning in a non-holonomic way if slip is avoided. Here we show that adding an elliptical path generating algorithm, especially a two-step enhanced algorithm that searches path both forward and backward simultaneously, can make planning such waves feasible and efficient by reducing required iterations by up around 2 orders of magnitude. With this path planner, it is possible to calculate the number of waves to get to arbitrary combinations of position and orientation in a space. This reveals boundaries in configuration space that can be used to determine whether to continue forward or back-up before maneuvering, as in the worm-like equivalent of parallel parking. The high number of waves required to shift the body laterally by even a single body width suggests that strategies for lateral motion, planning around obstacles and responsive behaviors will be important for future worm-like robots.