Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

A Mixed-Integer Approach for Motion Planning of Nonholonomic Robots under Visible Light Communication Constraints

Angelo Caregnato-Neto, Marcos Ricardo Omena de Albuquerque Maximo, Rubens Junqueira Magalhães Afonso

TL;DR

The paper addresses motion planning for a Robot Chain Control System (RCCS) of nonholonomic robots connected through Visible Light Communication (VLC) under directed LOS constraints. It introduces a MILP framework that discretizes orientations and embeds nonlinear kinematics, while encoding network connectivity and conic LOS constraints to ensure a base-to-leader path via relays. Novel contributions include directed-LOS constraints, sufficient connectivity conditions for directed networks, and rotation-dynamics compensation within a single MILP, demonstrated on Gazebo with Turtlebot3 showing successful target visitation and collision avoidance. The results indicate practical viability of MILP-based RCCS planning under VLC constraints and point to future work on adaptive cone sizing and real-robot validation.

Abstract

This work addresses the problem of motion planning for a group of nonholonomic robots under Visible Light Communication (VLC) connectivity requirements. In particular, we consider an inspection task performed by a Robot Chain Control System (RCCS), where a leader must visit relevant regions of an environment while the remaining robots operate as relays, maintaining the connectivity between the leader and a base station. We leverage Mixed-Integer Linear Programming (MILP) to design a trajectory planner that can coordinate the RCCS, minimizing time and control effort while also handling the issues of directed Line-Of-Sight (LOS), connectivity over directed networks, and the nonlinearity of the robots' dynamics. The efficacy of the proposal is demonstrated with realistic simulations in the Gazebo environment using the Turtlebot3 robot platform.

A Mixed-Integer Approach for Motion Planning of Nonholonomic Robots under Visible Light Communication Constraints

TL;DR

The paper addresses motion planning for a Robot Chain Control System (RCCS) of nonholonomic robots connected through Visible Light Communication (VLC) under directed LOS constraints. It introduces a MILP framework that discretizes orientations and embeds nonlinear kinematics, while encoding network connectivity and conic LOS constraints to ensure a base-to-leader path via relays. Novel contributions include directed-LOS constraints, sufficient connectivity conditions for directed networks, and rotation-dynamics compensation within a single MILP, demonstrated on Gazebo with Turtlebot3 showing successful target visitation and collision avoidance. The results indicate practical viability of MILP-based RCCS planning under VLC constraints and point to future work on adaptive cone sizing and real-robot validation.

Abstract

This work addresses the problem of motion planning for a group of nonholonomic robots under Visible Light Communication (VLC) connectivity requirements. In particular, we consider an inspection task performed by a Robot Chain Control System (RCCS), where a leader must visit relevant regions of an environment while the remaining robots operate as relays, maintaining the connectivity between the leader and a base station. We leverage Mixed-Integer Linear Programming (MILP) to design a trajectory planner that can coordinate the RCCS, minimizing time and control effort while also handling the issues of directed Line-Of-Sight (LOS), connectivity over directed networks, and the nonlinearity of the robots' dynamics. The efficacy of the proposal is demonstrated with realistic simulations in the Gazebo environment using the Turtlebot3 robot platform.
Paper Structure (10 sections, 3 theorems, 17 equations, 5 figures)

This paper contains 10 sections, 3 theorems, 17 equations, 5 figures.

Table of Contents

  1. INTRODUCTION
  2. Problem Description
  3. MILP motion planning
  4. Dynamics constraints
  5. Network connectivity
  6. Directed conic LOS
  7. Rotation dynamics compensation
  8. Optimization problem
  9. Results
  10. Conclusion

Key Result

Theorem 1

Satisfaction of constraints (const:base_indeg)-(const:gen_outdeg) guarantees that the RCCS is connected.

Figures (5)

  • Figure 1: Illustration of RCCS as devised in VLC_application1. a) A base station with two relay robots and a leader connected under VLC communication. b) Corresponding chained communication network.
  • Figure 2: Original and polytopic approximation of RCCS's conic light beams.
  • Figure 3: a) Trajectories computed by the MILP algorithm and tracking performance of the Turtlebots3 during the Gazebo simulation depicted in b) Final pose of the robots in the simulator. Green squares with white x markers are the targets. Simulation video available at: https://www.youtube.com/watch?v=xDju9YRVrtg
  • Figure 4: Snapshots of the Turtlebots' position during Gazebo simulation at critical time steps. Green and black polygons are targets and obstacles, respectively.
  • Figure 5: Orientation of each robot during the maneuver and corresponding commands.

Theorems & Definitions (7)

  • Definition 1
  • Theorem 1
  • proof
  • Lemma 1
  • proof
  • Proposition 1
  • proof