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Task and Motion Planning has made great progress in solving hard sequentialmanipulation problems. However, a gap between such planning formulations andcontrol methods for reactive execution remains. In this paper we propose amodel predictive control approach dedicated to robustly execute a singlesequence of constraints, which corresponds to a discrete decision sequence of aTAMP plan. We decompose the overall control problem into three sub-problems(solving for sequential waypoints, their timing, and a short receding horizonpath) that each is a non-linear program solved online in each MPC cycle. Theresulting control strategy can account for long-term interdependencies ofconstraints and reactively plan for a timing-optimal transition through allconstraints. We additionally propose phase backtracking when runningconstraints of the current phase cannot be fulfilled, leading to a fluentre-initiation behavior that is robust to perturbations and interferences by anexperimenter.

Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation