Optimal Integrated Task and Path Planning and Its Application to
Multi-Robot Pickup and Delivery
- URL: http://arxiv.org/abs/2403.01277v1
- Date: Sat, 2 Mar 2024 17:48:40 GMT
- Title: Optimal Integrated Task and Path Planning and Its Application to
Multi-Robot Pickup and Delivery
- Authors: Aman Aryan, Manan Modi, Indranil Saha, Rupak Majumdar and Swarup
Mohalik
- Abstract summary: We propose a generic multi-robot planning mechanism that combines an optimal task planner and an optimal path planner.
The Integrated planner, through the interaction of the task planner and the path planner, produces optimal collision-free trajectories for the robots.
- Score: 10.530860023128406
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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