Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics

Understand

A key ingredient to achieving intelligent behavior is physical understanding that equips robots with the ability to reason about the effects of their actions in a dynamic environment.

• Several methods have been proposed to learn dynamics models from data that inform model-based control algorithms.
• While such learning-based approaches can model locally observed behaviors, they fail to generalize to more complex dynamics and under long time horizons.
• In this work, we introduce a differentiable physics simulator for rigid body dynamics.