ICRA 2011 Paper Abstract


Paper WeP203.5

Stephens, Benjamin (Carnegie Mellon University)

State Estimation for Force-Controlled Humanoid Balance Using Simple Models in the Presence of Modeling Error

Scheduled for presentation during the Regular Sessions "Humanoid Robots IV" (WeP203), Wednesday, May 11, 2011, 16:25−16:40, Room 3D

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on July 14, 2020

Keywords Humanoid Robots, Sensor Fusion, Robust/Adaptive Control of Robotic Systems


This paper considers the design of state estimators for dynamic balancing systems using a Linear Inverted Pendulum model with unknown modeling errors such as a center of mass measurement offset or an external force. A variety of process and output models are constructed and compared. For a system containing modeling error, it is shown that a naive estimator (one that doesn't account for this error) will result in inaccurate state estimates. These state estimators are evaluated on a force-controlled humanoid robot for a sinusoidal swaying task and a forward push recovery task.



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