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Journal Article

Simulation-Based Design of Dynamic Controllers for Humanoid Balancing


Model-based trajectory optimization often fails to find a reference trajectory for under-actuated bipedal robots performing highly-dynamic, contact-rich tasks in the real world due to inaccurate physical models. In this paper, we propose a complete system that automatically designs a reference trajec- tory that succeeds on tasks in the real world with a very small number of real world experiments. We adopt existing system identification techniques and show that, with appropriate model parameterization and control optimization, an iterative system identification framework can be effective for designing reference trajectories. We focus on a set of tasks that leverage the momentum transfer strategy to rapidly change the whole- body from an initial configuration to a target configuration by generating large accelerations at the center of mass and switching contacts.

Paper   Video

Jie Tan
Zhaoming Xie
Byron Boots
C. Karen Liu
Journal Name
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016
Publication Date
October, 2016