Dynamic Legged Manipulation of a Ball Through Multi-Contact Optimization
This addresses the problem of expanding robotic manipulation capabilities beyond traditional arms for researchers in legged robotics, though it is incremental as it applies known MPC methods to a new task.
The paper tackles the problem of using a quadrupedal robot's feet for dynamic manipulation tasks, specifically balancing on and controlling a ball to follow various trajectories. The result is a model predictive control framework validated numerically on the Mini Cheetah robot with different gaits, achieving trajectory following for straight lines, sinusoids, circles, and in-place turning.
The feet of robots are typically used to design locomotion strategies, such as balancing, walking, and running. However, they also have great potential to perform manipulation tasks. In this paper, we propose a model predictive control (MPC) framework for a quadrupedal robot to dynamically balance on a ball and simultaneously manipulate it to follow various trajectories such as straight lines, sinusoids, circles and in-place turning. We numerically validate our controller on the Mini Cheetah robot using different gaits including trotting, bounding, and pronking on the ball.