Efficient Multi-Contact Pattern Generation with Sequential Convex Approximations of the Centroidal Dynamics
This work addresses the challenge of fast and reliable motion planning for legged robots in multi-contact scenarios, which is incremental but improves computational speed for potential real-time control.
The paper tackles the problem of efficiently generating physically consistent multi-contact behaviors for robots by proposing a convex relaxation of centroidal dynamics, leading to two algorithms that optimize trajectories, forces, and motion timing. It demonstrates computational efficiency in simulations and real-world tests on humanoids and quadrupeds.
This paper investigates the problem of efficient computation of physically consistent multi-contact behaviors. Recent work showed that under mild assumptions, the problem could be decomposed into simpler kinematic and centroidal dynamic optimization problems. Based on this approach, we propose a general convex relaxation of the centroidal dynamics leading to two computationally efficient algorithms based on iterative resolutions of second order cone programs. They optimize centroidal trajectories, contact forces and, importantly, the timing of the motions. We include the approach in a kino-dynamic optimization method to generate full-body movements. Finally, the approach is embedded in a mixed-integer solver to further find dynamically consistent contact sequences. Extensive numerical experiments demonstrate the computational efficiency of the approach, suggesting that it could be used in a fast receding horizon control loop. Executions of the planned motions on simulated humanoids and quadrupeds and on a real quadruped robot further show the quality of the optimized motions.