Dynamical System-Based Motion Planning for Multi-Arm Systems: Reaching for Moving Objects

Dynamical System-Based Motion Planning for Multi-Arm Systems: Reaching for Moving Objects

Seyed Sina Mirrazavi Salehian, Nadia Figueroa, Aude Billard

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Best Sister Conferences. Pages 4914-4918. https://doi.org/10.24963/ijcai.2017/693

The use of coordinated multi-arm robotic systems allows to preform manipulations of heavy or bulky objects that would otherwise be infeasible for a single-arm robot. This paper concisely introduces our work on coordinated multi-arm control [Salehian et al., 2016a], where we proposed a virtual object based dynamical systems (DS) control law to generate autonomous and synchronized motions for a multi-arm robot system. We show theoretically and empirically that the multi-arm + virtual object system converges asymptotically to a moving object. The proposed framework is validated on a dual-arm robotic system. We demonstrate that it can re-synchronize and adapt the motion of each arm in a fraction of a second, even when the object’s motion is fast and not accurately predictable.
Keywords:
Artificial Intelligence: robotics
Artificial Intelligence: automated planning