When to make a step? Tackling the timing problem in multi-contact locomotion by TOPP-MPC

TL;DR

This paper introduces a TOPP-MPC controller for multi-contact locomotion that computes optimal contact timings dynamically, improving adaptability to terrain without relying on heuristics, demonstrated on a humanoid robot model.

Contribution

It presents a novel approach combining TOPP with MPC to automatically determine contact timings in multi-contact locomotion, unlike traditional methods that require predefined timings.

Findings

Effective in simulation with HRP-4 humanoid model

Automatically computes contact timings based on terrain

Outperforms heuristic-based timing methods

Abstract

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.