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AAAI
2010

Online Learning of Uneven Terrain for Humanoid Bipedal Walking

10 years 1 months ago
Online Learning of Uneven Terrain for Humanoid Bipedal Walking
We present a novel method to control a biped humanoid robot to walk on unknown inclined terrains, using an online learning algorithm to estimate in real-time the local terrain from proprioceptive and inertial sensors. Compliant controllers for the ankle joints are used to actively probe the surrounding surface, and the measured sensor data are combined to explicitly learn the global inclination and local disturbances of the terrain. These estimates are then used to adaptively modify the robot locomotion and control parameters. Results from both a physically-realistic computer simulation and experiments on a commercially available small humanoid robot show that our method can rapidly adapt to changing surface conditions to ensure stable walking on uneven surfaces.
Seung-Joon Yi, Byoung-Tak Zhang, Daniel D. Lee
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where AAAI
Authors Seung-Joon Yi, Byoung-Tak Zhang, Daniel D. Lee
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