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We develop an algorithm for the motion and task planning of a systemcomprised of multiple robots and unactuated objects under tasks expressed asLinear Temporal Logic (LTL) constraints. The robots and objects evolve subjectto uncertain dynamics in an obstacle-cluttered environment. The key part of theproposed solution is the intelligent construction of a coupled transitionsystem that encodes the motion and tasks of the robots and the objects. Weachieve such a construction by designing appropriate adaptive control protocolsin the lower level, which guarantee the safe robot navigation/objecttransportation in the environment while compensating for the dynamicuncertainties. The transition system is efficiently interfaced with thetemporal logic specification via a sampling-based algorithm to output adiscrete path as a sequence of synchronized actions of the robots; such actionssatisfy the robots' as well as the objects' specifications. The robots executethis discrete path by using the derived low level control protocol. Simulationresults verify the proposed framework.

Planning and Control of Multi-Robot-Object Systems under Temporal Logic Tasks and Uncertain Dynamics