小型四足机器人的视觉辅助非结构化地形动态探测

Donghyun Kim, D. Carballo, J. Carlo, Benjamin Katz, G. Bledt, Bryan Lim, Sangbae Kim
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引用次数: 65

摘要

有腿机器人因其在崎岖地形上的移动能力而成为灾害响应和救援场景的有前途的移动平台。在混乱的环境中,小型机器人是可取的,因为它们可以通过小缝隙、狭窄的路径或隧道。然而,小型机器人也有自己的困难,比如传感器的空间有限,障碍清除有限,以及按比例降低的行走速度。在本文中,我们通过有效的传感器集成和开发动态运动和跳跃来广泛解决这些困难。我们将两个英特尔RealSense传感器集成到麻省理工学院的迷你猎豹机器人中,这是一个0.3米高,9公斤重的四足机器人。采用了简单有效的滤波和评估算法来进行落脚点调整和避障。我们展示了探索高度不规则的地形使用动态小跑和跳跃与小型,全传感器迷你猎豹四足机器人。
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Vision Aided Dynamic Exploration of Unstructured Terrain with a Small-Scale Quadruped Robot
Legged robots have been highlighted as promising mobile platforms for disaster response and rescue scenarios because of their rough terrain locomotion capability. In cluttered environments, small robots are desirable as they can maneuver through small gaps, narrow paths, or tunnels. However small robots have their own set of difficulties such as limited space for sensors, limited obstacle clearance, and scaled-down walking speed. In this paper, we extensively address these difficulties via effective sensor integration and exploitation of dynamic locomotion and jumping. We integrate two Intel RealSense sensors into the MIT Mini-Cheetah, a 0.3 m tall, 9 kg quadruped robot. Simple and effective filtering and evaluation algorithms are used for foothold adjustment and obstacle avoidance. We showcase the exploration of highly irregular terrain using dynamic trotting and jumping with the small-scale, fully sensorized Mini-Cheetah quadruped robot.
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