International Journal of Robotics Research
Applied optimal control for dynamically stable legged locomotion
Applied optimal control for dynamically stable legged locomotion
Locomotion Control of a Biped Robot Using Nonlinear Oscillators
Autonomous Robots
Optimal Mass Distribution for Passivity-Based Bipedal Robots
International Journal of Robotics Research
International Journal of Robotics Research
Minimalistic control of a compass gait robot in rough terrain
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
IEEE Transactions on Robotics
Swing-Leg Retraction for Limit Cycle Walkers Improves Disturbance Rejection
IEEE Transactions on Robotics
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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Toward our comprehensive understanding of legged locomotion in animals and machines, the compass gait model has been intensively studied for a systematic investigation of complex biped locomotion dynamics. While most of the previous studies focused only on the locomotion on flat surfaces, in this article, we tackle with the problem of bipedal locomotion in rough terrains by using a minimalistic control architecture for the compass gait walking model. This controller utilizes an open-loop sinusoidal oscillation of hip motor, which induces basic walking stability without sensory feedback. A set of simulation analyses show that the underlying mechanism lies in the "phase locking" mechanism that compensates phase delays between mechanical dynamics and the open-loop motor oscillation resulting in a relatively large basin of attraction in dynamic bipedal walking. By exploiting this mechanism, we also explain how the basin of attraction can be controlled by manipulating the parameters of oscillator not only on a flat terrain but also in various inclined slopes. Based on the simulation analysis, the proposed controller is implemented in a real-world robotic platform to confirm the plausibility of the approach. In addition, by using these basic principles of self-stability and gait variability, we demonstrate how the proposed controller can be extended with a simple sensory feedback such that the robot is able to control gait patterns autonomously for traversing a rough terrain.