Optimal Distributed Multi-Robot Communication-Aware Trajectory Planning using Alternating Direction Method of Multipliers

This paper presents a distributed, optimal, communication-aware trajectory planning algorithm for multi-robot systems. Building on prior work, it addresses the multi-robot communication-aware trajectory planning problem using a general optimisation framework that imposes linear constraints on changes in robot positions to ensure communication performance and collision avoidance. In this paper, the optimisation problem is solved distributively by separating the communication performance constraint through an economic approach. Here, the current communication budget is distributed equally among the robots, and the robots are allowed to trade parts of their budgets with each other. The separated optimisation problem is then solved using the consensus alternating direction method of multipliers. The method was verified through simulation in an inspection task problem.

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

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.

Distributed Planning for Rigid Robot Formations using Consensus on the Transformation of a Base Configuration

This paper presents a novel planning method that achieves navigation of multi-robot formations in cluttered environments, while maintaining the formation throughout the robots motion. The method utilises a decentralised approach to find feasible formation parameters that guarantees formation constraints for rigid formations. The method proves to be computationally efficient, making it relevant for reactive planning and control of multi-robot systems formation. The method has been tested in a simulation environment to prove feasibility and run-time efficiency.