Fast Nonprehensile Object Transportation on a Mobile Manipulator

Adam Heins, Angela P. Schoellig

Keywords: nonprehensile manipulation, mobile manipulation, whole-body motion planning and control, waiter's problem

TL;DR: We use model predictive control to make a mobile manipulator balance objects on a tray while moving from one location to another and avoiding obstacles, like a restaurant waiter.

Abstract:

We consider a nonprehensile manipulation task in which a mobile manipulator
must balance objects on its end effector without grasping them---known as the
waiter's problem---while moving to a desired location. In contrast to existing
approaches, our focus is on fast online planning in response to new and
changing environments. Our main contribution is a whole-body constrained model
predictive controller (MPC) for a mobile manipulator that balances objects and
avoids collisions. Furthermore, we propose planning using the minimum
statically-feasible friction coefficients, which provides robustness to
frictional uncertainty and other force disturbances while also substantially
reducing the compute time required to update the MPC policy. Notably, we
demonstrate a projectile avoidance task in which our mobile manipulator avoids
a thrown ball while balancing a tall bottle.

Submission Number: 11