Evaluation of snake robot's behavior using randomized EARLI in crowded obstacles

T. Kamegawa, Ryoma Kuroki, A. Gofuku
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引用次数: 10

Abstract

We have proposed EARLI (Extended Asymmetrical Reverse Lateral Inhibition) which is a behavior of snake robot's obstacle aided locomotion. The idea of EARLI starts with an original idea of lateral inhibition. Joints rotate in reverse direction compared with the original lateral inhibition. Information of contact affects not only adjacent joints but also a couple of neighboring joints away from the contacting link. Distribution of torque are empirically set asymmetrically in order to propel a snake robot forward. The algorithm of EARLI is implemented to a model of snake robot in ODE (Open Dynamics Engine) to see its behavior and to verify its effectiveness. In this paper, we introduce randomized EARLI to avoid getting stuck in crowded obstacles when the snake robot uses only one pattern of EARLI. In addition, efficiency of the snake robot's locomotion is evaluated by measuring power of snake robot's joints. It is verified that the snake robot can move in crowded obstacles effectively by using random EARLI behavior.
基于随机EARLI的蛇形机器人在拥挤障碍物中的行为评价
提出了扩展不对称反向侧向抑制(EARLI),即蛇形机器人的障碍物辅助运动行为。EARLI的想法始于一个关于侧抑制的原始想法。关节旋转方向与原来的外侧抑制相反。接触信息不仅影响相邻关节,而且影响远离接触连杆的几个相邻关节。为了使蛇形机器人向前运动,经验地设置了非对称的力矩分布。在ODE (Open Dynamics Engine)中对蛇形机器人模型实施EARLI算法,观察其行为并验证其有效性。为了避免在蛇形机器人只使用一种EARLI模式时陷入拥挤的障碍物,本文引入了随机EARLI模式。此外,通过测量蛇形机器人关节的功率来评价蛇形机器人的运动效率。实验验证了采用随机EARLI行为的蛇形机器人可以有效地在拥挤的障碍物中移动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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