Rapid Trajectory Optimization Using C-FROST with Illustration on a Cassie-Series Dynamic Walking Biped
This addresses the problem of slow and complex trajectory optimization for robotics researchers, though it appears incremental as it builds on existing FROST methods.
The paper tackles the challenge of rapidly optimizing trajectories for high-degree-of-freedom humanoid robots without simplifying models, by introducing C-FROST and multi-threading tools, achieving efficient computation as demonstrated on a 20-DoF Cassie biped robot.
One of the big attractions of low-dimensional models for gait design has been the ability to compute solutions rapidly, whereas one of their drawbacks has been the difficulty in mapping the solutions back to the target robot. This paper presents a set of tools for rapidly determining solutions for ``humanoids'' without removing or lumping degrees of freedom. The main tools are (1) C-FROST, an open-source C++ interface for FROST, a direct collocation optimization tool; and (2) multi-threading. The results will be illustrated on a 20-DoF floating-base model for a Cassie-series bipedal robot through numerical calculations and physical experiments.