Optimal Integrated Task and Path Planning and Its Application to Multi-Robot Pickup and Delivery
<|reference_start|>Optimal Integrated Task and Path Planning and Its Application to Multi-Robot Pickup and Delivery: We propose a generic multi-robot planning mechanism that combines an optimal task planner and an optimal path planner to provide a scalable solution for complex multi-robot planning problems. The Integrated planner, through the interaction of the task planner and the path planner, produces optimal collision-free trajectories for the robots. We illustrate our general algorithm on an object pick-and-drop planning problem in a warehouse scenario where a group of robots is entrusted with moving objects from one location to another in the workspace. We solve the task planning problem by reducing it into an SMT-solving problem and employing the highly advanced SMT solver Z3 to solve it. To generate collision-free movement of the robots, we extend the state-of-the-art algorithm Conflict Based Search with Precedence Constraints with several domain-specific constraints. We evaluate our integrated task and path planner extensively on various instances of the object pick-and-drop planning problem and compare its performance with a state-of-the-art multi-robot classical planner. Experimental results demonstrate that our planning mechanism can deal with complex planning problems and outperforms a state-of-the-art classical planner both in terms of computation time and the quality of the generated plan.<|reference_end|>
@article{aryan2024optimal,
    title={Optimal Integrated Task and Path Planning and Its Application to
  Multi-Robot Pickup and Delivery},
    author={Aman Aryan, Manan Modi, Indranil Saha, Rupak Majumdar and Swarup
  Mohalik},
    journal={arXiv preprint arXiv:2403.01277},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.01277},
    primaryClass={cs.RO cs.AI cs.MA}
}