Distributed Drone Traffic Coordination Using Triggered Communication

Abstract

This paper proposes a low complexity distributed multi-agent coordination algorithm for agents to reach their target positions in dense traffic under limited communication. Each single-integrator agent is limited to communicating with only one other agent at a time in consideration of limited bandwidth. We adapt the Velocity Obstacle collision avoidance method from literature to the limited communication problem by incorporating Voronoi Cells and repulsion in our hybrid algorithm. We also introduce a priority system for distributed coordination to avoid deadlocks and livelocks by having agent pairs make mutual decisions based on each agent’s conditional priority. An event trigger-based communication protocol is designed to determine when and to whom to communicate. Our method’s effectiveness is demonstrated in simulations including 100 randomized scenarios of 50 agents. The simulations show that our proposed algorithm enables agents to reach their assigned target positions without deadlock and collision while requiring an average communication rate that is significantly lower than the control frequency.

Distributed stochastic proximal algorithm with random reshuffling for non-smooth finite-sum optimization

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Energy-efficient trajectory planning for a multi-UAV-assisted mobile edge computing system

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Motion planning for non-holonomic mobile robots in obstacle-rich environments

“…Hence, in practice, the algorithm should be designed to require less frequent communication while still guaranteeing non-collision. For example, [163] presented a low-complexity distributed multi-agent coordination algorithm for agents using event-triggered communication. Motivated by this work, it is worth investing the extension of current study to consider the limited communication.…”