Optimal Motion Planning for Two Square Robots in a Rectilinear Environment

TL;DR

This paper presents the first polynomial-time algorithm for optimally planning collision-free paths for two square robots in a polygonal environment, focusing on minimizing total path length, and proves NP-hardness for minimizing maximum completion time.

Contribution

It introduces a novel polynomial-time algorithm for the min-sum problem and establishes NP-hardness for the min-makespan variant in planar environments.

Findings

Polynomial-time algorithm for min-sum problem

NP-hardness proof for min-makespan problem

Optimal collision-free paths for two robots in polygonal environments

Abstract

Let $\mathcal{W} \subset \mathbb{R}^2$ be a rectilinear polygonal environment (that is, a rectilinear polygon potentially with holes) with a total of $n$ vertices, and let $A,B$ be two robots, each modeled as an axis-aligned unit square, that can move rectilinearly inside $\mathcal{W}$. The goal is to compute a collision-free motion plan $\boldsymbol{\pi}$, that is, a motion plan that continuously moves $A$ from $s_A$ to $t_A$ and $B$ from $s_B$ to $t_B$ so that $A$ and $B$ remain inside $\mathcal{W}$ and do not collide with each other during the motion. We study two variants of this problem which are focused additionally on the optimality of $\boldsymbol{\pi}$, and obtain the following results. 1. Min-Sum: Here the goal is to compute a motion plan that minimizes the sum of the lengths of the paths of the robots. We present an $O(n^4\log{n})$-time algorithm for computing an optimal solution to the min-sum problem. This is the first polynomial-time algorithm to compute an optimal, collision-free motion of two robots amid obstacles in a planar polygonal environment. 2. Min-Makespan: Here the robots can move with at most unit speed, and the goal is to compute a motion plan that minimizes the maximum time taken by a robot to reach its target location. We prove that the min-makespan variant is NP-hard.