Optimal Multi-Robot Communication-Aware Trajectory Planning by Constraining the Fiedler Value

TL;DR

This paper introduces a novel optimization framework for multi-robot trajectory planning that ensures continuous communication connectivity by constraining the Fiedler value, demonstrated through simulations and experiments.

Contribution

It presents a new method that incorporates Fiedler value constraints into trajectory planning, improving communication reliability and computational efficiency.

Findings

Fiedler value constraints maintain network connectivity.

The method computes feasible and near-optimal trajectories.

Approximate constraints significantly reduce computation time.

Abstract

The paper present a novel approach for the solution of the Multi-Robot Communication-Aware Trajectory Planning, which builds on a general optimisation framework where the changes in robots positions are used as decision variable, and linear constraints on the trajectories of the robots are introduced to ensure communication performance and collision avoidance. The Fiedler value is adopted as communication performance metric. The validity of the method in computing both feasible and optimal trajectories for the robots is demonstrated both in simulation and experimentally. Results show that the constraint on the Fiedler value ensures that the robot network fulfils its objective while maintaining communication connectivity at all times. Further, the paper shows that the introduction of approximations for the constraints enables a significant improvement in the computational time of the solution, which remain very close to the optimal solution.