Trajectory generation for dynamic bipedal walking through qualitative model based manifold learning

— Legged robots represent great promise for transport in unstructured environments. However, it has been difficult to devise motion planning strategies that achieve a combination of energy efficiency, safety and flexibility comparable to legged animals. In this paper, we address this issue by presenting a trajectory generation strategy for dynamic bipedal walking robots using a factored approach to motion planning - combining a low-dimensional plan (based on intermittently actuated passive walking in a compass-gait biped) with a manifold learning algorithm that solves the problem of embedding this plan in the high-dimensional phase space of the robot. This allows us to achieve task level control (over step length) in an energy efficient way - starting with only a coarse qualitative model of the system dynamics and performing a data-driven approximation of the dynamics in order to synthesize families of dynamically realizable trajectories. We demonstrate the utility of this approa...

• Type: Conference
• Year: 2008
• Where: ICRA
• Authors: Subramanian Ramamoorthy, Benjamin Kuipers
• Keywords: ICRA 2008, Legged Robot, Motion Planning, Multi-link Legged Robot, Robotics