Prioritized SIPP for Multi-Agent Path Finding With Kinematic Constraints

TL;DR

This paper introduces a prioritized planning method based on Safe Interval Path Planning that explicitly incorporates kinematic constraints like speed and acceleration for multi-agent pathfinding.

Contribution

It extends SIPP to consider kinematic constraints, enabling more realistic path planning for robots in shared environments.

Findings

The proposed method effectively accounts for kinematic constraints.

Empirical evaluation shows improved path feasibility.

Heuristic functions enhance planning efficiency.

Abstract

Multi-Agent Path Finding (MAPF) is a long-standing problem in Robotics and Artificial Intelligence in which one needs to find a set of collision-free paths for a group of mobile agents (robots) operating in the shared workspace. Due to its importance, the problem is well-studied and multiple optimal and approximate algorithms are known. However, many of them abstract away from the kinematic constraints and assume that the agents can accelerate/decelerate instantaneously. This complicates the application of the algorithms on the real robots. In this paper, we present a method that mitigates this issue to a certain extent. The suggested solver is essentially, a prioritized planner based on the well-known Safe Interval Path Planning (SIPP) algorithm. Within SIPP we explicitly reason about the speed and the acceleration thus the constructed plans directly take kinematic constraints of agents into account. We suggest a range of heuristic functions for that setting and conduct a thorough empirical evaluation of the suggested algorithm.