Vision-Guided Humanoid Footstep Planning for Dynamic Environments

Philipp Michel, Joel Chestnutt, James Kuffner and Takeo Kanade
Conference Paper, Proceedings of the IEEE-RAS Conference on Humanoid Robots (Humanoids'05), pp. 13 - 18, December, 2005

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Abstract

Despite the stable walking capabilities of modern biped humanoid robots, their ability to autonomously and safely navigate obstacle-filled, unpredictable environments has so far been limited. We present an approach to autonomous humanoid walking that combines vision-based sensing with a footstep planner, allowing the robot to navigate toward a desired goal position while avoiding obstacles. An environment map including the robot, goal, and obstacle locations is built in real-time from vision. The footstep planner then computes an optimal sequence of footstep locations within a time-limited planning horizon. Footstep plans are reused and only partially recomputed as the environment changes during the walking sequence. In our experiments, combining real-time vision with plan reuse has allowed a Honda ASIMO humanoid robot to autonomously traverse dynamic environments containing unpredictably moving obstacles.


@conference{Michel-2005-9358,
author = {Philipp Michel and Joel Chestnutt and James Kuffner and Takeo Kanade},
title = {Vision-Guided Humanoid Footstep Planning for Dynamic Environments},
booktitle = {Proceedings of the IEEE-RAS Conference on Humanoid Robots (Humanoids'05)},
year = {2005},
month = {December},
pages = {13 - 18},
keywords = {Humanoid Robot, Vision, Footstep Planning, Obstacle Avoidance, Dynamic Replanning},
} 2017-09-13T10:43:04-04:00