When to make a step? Tackling the timing problem in multi-contact locomotion by TOPP-MPC
This addresses the timing challenge in multi-contact locomotion for legged robots, where existing methods rely on heuristic inputs, but it appears incremental as it builds on MPC and TOPP techniques.
The paper tackled the problem of determining optimal step timings in multi-contact locomotion for legged robots, by developing a TOPP-MPC controller that computes timings as outputs of nonlinear optimization, and demonstrated its behavior in simulations with an HRP-4 humanoid robot model.
We present a model predictive controller (MPC) for multi-contact locomotion where predictive optimizations are realized by time-optimal path parameterization (TOPP). A key feature of this solution is that, contrary to existing planners where step timings are provided as inputs, here the timing between contact switches is computed as output of a fast nonlinear optimization. This is particularly appealing to multi-contact locomotion, where proper timings depend on terrain topology and suitable heuristics are unknown. We show how to formulate legged locomotion as a TOPP problem and demonstrate the behavior of the resulting TOPP-MPC controller in simulations with a model of the HRP-4 humanoid robot.