Mixed-Integer Motion Planning for Nonholonomic Robots Under Visible Light Communication Constraints

Abstract

This work is concerned with the problem of motion planning for a group of nonholonomic robots under Visible Light Communication (VLC) connectivity requirements. Recently, multi-robot systems operating with VLC networks have been demonstrated as an attractive solution for inspection tasks in pipelines and underground facilities. However, there are still no established methodologies to automate their operation. We address this problem with an optimization framework based on Mixed-Integer Linear Programming (MILP) to design a motion planner that safely coordinates the robot team while jointly addressing the nonlinearity of the robots' dynamics, the directed line-of-sight requirement for VLC connections, and the connectivity maintenance of the ensuing directed networks. We propose a novel method to encode the nonlinear dynamics of nonholonomic robots into the MILP formulation and demonstrate through comparative trials that, although the resulting optimization search space is more restricted, the approach still outperforms mixed-integer nonlinear programming in terms of optimization time and solution quality. The efficacy of the proposal is also demonstrated through realistic simulations of the Turtlebot3 robot platform.