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群制御arXiv:1803.05601

低重力環境における連結ロボット群の登攀計画とナビゲーション

Planning and Navigation of Climbing Robots in Low-Gravity Environments

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低重力環境で複数の球型ロボットをテザーで連結し、棘付き把持機構で斜面を協調登攀するための自律マッピング・計画・ナビゲーション手法を提案し、高忠実度シミュレータで評価した論文。

著者: Steven Morad, Himangshu Kalita, Jekan Thangavelautham

分類: cs.RO

原文アブストラクト

Advances in planetary robotics have led to wheeled robots that have beamed back invaluable science data from the surface of the Moon and Mars. However, these large wheeled robots are unable to access rugged environments such as cliffs, canyons and crater walls that contain exposed rock-faces and are geological time-capsules into the early Moon and Mars. We have proposed the SphereX robot with a mass of 3 kg, 30 cm diameter that can hop, roll and fly short distances. A single robot may slip and fall, however, a multirobot system can work cooperatively by being interlinked using spring-tethers and work much like a team of mountaineers to systematically climb a slope. We consider a team of four or more robots that are interlinked with tethers in an 'x' configuration. Each robot secures itself to a slope using spiny gripping actuators, and one by one each robot moves upwards by crawling, rolling or hopping up the slope. In this paper, we present a human devised autonomous climbing algorithm and evaluate it using a high-fidelity dynamics simulator. The climbing surfaces contain impassable obstacles and some loosely held rocks that can dislodge. Under these conditions, the robots need to autonomously map, plan and navigate up or down these steep environments. Autonomous mapping and navigation capability is evaluated using simulated lasers, vision sensors. The human devised planning algorithm uses a new algorithm called bounded-leg A*. Our early simulation results show much promise in these techniques and our future plans include demonstration on real robots in a controlled laboratory environment and outdoors in the canyons of Arizona.

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