iLQR for Piecewise-Smooth Hybrid Dynamical Systems

TL;DR

This paper extends the iLQR algorithm to handle hybrid dynamical systems with changing contact modes, enabling trajectory optimization for complex robotic tasks involving mode switches.

Contribution

It introduces a novel approach to incorporate hybrid mode changes into iLQR using saltation matrices and reference extensions, advancing trajectory optimization for hybrid systems.

Findings

Successfully applied to various hybrid systems

Improved gradient computation strategies demonstrated

Enhanced trajectory planning for robotic contact tasks

Abstract

Trajectory optimization is a popular strategy for planning trajectories for robotic systems. However, many robotic tasks require changing contact conditions, which is difficult due to the hybrid nature of the dynamics. The optimal sequence and timing of these modes are typically not known ahead of time. In this work, we extend the Iterative Linear Quadratic Regulator (iLQR) method to a class of piecewise smooth hybrid dynamical systems by allowing for changing hybrid modes in the forward pass, using the saltation matrix to update the gradient information in the backwards pass, and using a reference extension to account for mode mismatch. We demonstrate these changes on a variety of hybrid systems and compare the different strategies for computing the gradients.