Online Trajectory Optimization for Dynamic Aerial Motions of a Quadruped Robot
This work addresses the challenge of real-time dynamic motion control for quadruped robots, enabling complex aerial behaviors that could enhance agility in applications like search and rescue or entertainment, though it is incremental as it builds on existing optimization and control methods.
The authors tackled the problem of enabling quadruped robots to perform dynamic aerial motions online by developing a two-part framework that plans motions via centroidal momentum-based nonlinear optimization and tracks them with a variational-based optimal controller, achieving reliable execution of jumps, spins, flips, and other maneuvers on the MIT Mini Cheetah with planning times of 0.05-0.15 seconds and control at 500 Hz.
This work presents a two part framework for online planning and execution of dynamic aerial motions on a quadruped robot. Motions are planned via a centroidal momentum-based nonlinear optimization that is general enough to produce rich sets of novel dynamic motions based solely on the user-specified contact schedule and desired launch velocity of the robot. Since this nonlinear optimization is not tractable for real-time receding horizon control, motions are planned once via nonlinear optimization in preparation of an aerial motion and then tracked continuously using a variational-based optimal controller that offers robustness to the uncertainties that exist in the real hardware such as modeling error or disturbances. Motion planning typically takes between 0.05-0.15 seconds, while the optimal controller finds stabilizing feedback inputs at 500 Hz. Experimental results on the MIT Mini Cheetah demonstrate that the framework can reliably produce successful aerial motions such as jumps onto and off of platforms, spins, flips, barrel rolls, and running jumps over obstacles.