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- W1969172238 abstract "To solve the rebalance problem of a full-body humanoid walking, an adaptive foot positioning compensation approach is proposed. To obtain a more precise initial policy, a constrained dynamics model is used to generate the offline policy. A heteroscedastic sparse Gaussian process is applied for online calculation of the foot positioning policy. In order to make the generated policy to adapt with the full-body dynamics, a sample-efficient MAP-like updating method for the heteroscedastic sparse Gaussian process model is also proposed. Experiments on both simulation and a real full-body humanoid are developed to show the performance of the final foot positioning policy. With the help of proposed method, the full-body humanoid robot succeeded walking down an elastic deformable platform and several obvious compensation foot steps can be observed for the robot to retrieve its balance." @default.
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- W1969172238 date "2011-05-01" @default.
- W1969172238 modified "2023-10-17" @default.
- W1969172238 title "Rebalance strategies for humanoids walking by foot positioning compensator based on adaptive heteroscedastic SpGPs" @default.
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- W1969172238 doi "https://doi.org/10.1109/icra.2011.5979889" @default.
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