Kinematic gait synthesis for snake robots
Kinematic gait synthesis for snake robots
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DOI：
10.1177/0278364915593793
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发表时间：
2016-01-01
影响因子：
9.2
通讯作者：
Choset, Howie
中科院分区：
文献类型：
--
作者：
Gong, Chaohui;Travers, Matthew J.;Choset, Howie
蛇形机器人是一种高度关节的机构，可以执行传统机器人无法完成的各种运动。尽管蛇机器人取得了许多成功的证明，但这些机制还无法实现它们的生物同行所表现出的敏捷性。我们认为，研究生物蛇如何协调全身运动以实现灵活的行为，有助于提高蛇机器人的性能。这项工作的基础是假设，对于近似运动学的蛇运动，重放从生物蛇收集的参数化形状轨迹数据可以在蛇机器人中产生等价的运动。为了验证这一假设，我们收集了执行各种不同行为的响尾蛇的形状轨迹数据。然后，我们使用一种新的算法，称为条件基数组因式分解，将高维数据数组投影到低维表示上，以简洁而有意义的方式分析形状轨迹数据。记录的蛇运动的低维表示能够再现蛇机器人上记录的生物蛇运动的基本特征，从而提高了敏捷性和机动性，证实了我们的假设。这种参数化表示允许我们搜索低维参数空间来生成行为，从而进一步提高蛇机器人的性能。
Snake robots are highly articulated mechanisms that can perform a variety of motions that conventional robots cannot. Despite many demonstrated successes of snake robots, these mechanisms have not been able to achieve the agility displayed by their biological counterparts. We suggest that studying how biological snakes coordinate whole-body motion to achieve agile behaviors can help improve the performance of snake robots. The foundation of this work is based on the hypothesis that, for snake locomotion that is approximately kinematic, replaying parameterized shape trajectory data collected from biological snakes can generate equivalent motions in snake robots. To test this hypothesis, we collected shape trajectory data from sidewinder rattlesnakes executing a variety of different behaviors. We then analyze the shape trajectory data in a concise and meaningful way by using a new algorithm, called conditioned basis array factorization, which projects high-dimensional data arrays onto a low-dimensional representation. The low-dimensional representation of the recorded snake motion is able to reproduce the essential features of the recorded biological snake motion on a snake robot, leading to improved agility and maneuverability, confirming our hypothesis. This parameterized representation allows us to search the low-dimensional parameter space to generate behaviors that further improve the performance of snake robots.