A Versatile Co-Design Approach For Dynamic Legged Robots

Understand

We present a versatile framework for the computational co-design of legged robots and dynamic maneuvers.

• Current state-of-the-art approaches are typically based on random sampling or concurrent optimization.
• We propose a novel bilevel optimization approach that exploits the derivatives of the motion planning sub-problem (i.e., the lower level).
• These motion-planning derivatives allow us to incorporate arbitrary design constraints and costs in an general-purpose nonlinear program (i.e., the upper level).