ICRA'09 Paper Abstract


Paper FrB1.5

Iida, Fumiya (Massachusetts Institute of Technology), Tedrake, Russ (Massachusetts Institute of Technology)

Minimalistic Control of a Compass Gait Robot in Rough Terrain

Scheduled for presentation during the Regular Sessions "Legged Robots and Humanoid Locomotion - II" (FrB1), Friday, May 15, 2009, 11:50−12:10, MainHall

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 21, 2022

Keywords Legged Robots and Humanoid Locomotion, Dynamics, Motion Control


Although there has been an increasing interest in dynamic bipedal locomotion for significant improvement of energy efficiency and dexterity of mobile robots in the real world, their locomotion capabilities are still mostly restricted on flat surfaces. The difficulty of dynamic locomotion in rough terrain is mainly originated in the stability and controllability of gait patterns while exploiting the natural mechanical dynamics of the robots. For a systematic investigation of the challenging problem of dynamic locomotion in rough terrains, this paper presents a novel approach to control of a biped robot by employing the simplest control architecture for the compass gait model. Locomotion of the model is mainly achieved by an open-loop oscillator which induces self-stabilizing gait patterns, and we test the proposed control architecture in a real-world robotic platform. In addition, we also found that this controller is capable of varying stride length with a minimum change of control parameters, which enables locomotion in rough terrains. By using these basic principles of self-stability and gait variability, we extended the proposed controller with a simple sensory feedback about the location in the environment, which makes the robot possible to control gait patterns autonomously for traversing a rough terrain. We describe a set of experimental results and discuss how the proposed minimalistic control architecture can be enhanced for dynamic locomotion control in more complex



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