Robust Trajectory Optimization for Safe Locomotion over Uncertain Terrain

Luke Drnach, Ye Zhao, Ye Zhao

Abstract: Safe and autonomous locomotion for legged robots in real-world environments requires generating motion strategies that are robust to uncertainty in the terrain. Current trajectory optimization methods rely on specifying the geometry and friction properties of the terrain; however, errors in the terrain model can lead to failure through slipping and falling. Here we develop a trajectory optimization approach that explicitly incorporates parametric uncertainty in the terrain model. We demonstrate that our method produces a spectrum of robust trajectories: the method produces robust trajectories when uncertainty is large and the nominal optimal trajectories when uncertainty is small. Our study represents a step towards generating safe locomotion behaviors which are robust against uncertainty in the terrain.

TL;DR: We present a method for reasoning about robustness to uncertainty in the terrain during trajectory optimization for robot locomotion.

Keywords: Safety, Robust Trajectory Optimization, Legged Robotics