Abstract
The autonomous vehicle technology has recently been developed rapidly in a wide variety of applications. However, coordinating a team of autonomous vehicles to complete missions in an unknown and changing environment has been a challenging and complicated task. We modify the consensus-based auction algorithm (CBAA) so that it can dynamically reallocate tasks among autonomous vehicles that can flexibly find a path to reach multiple dynamic targets while avoiding unexpected obstacles and staying close as a group as possible simultaneously. We propose the core algorithms and simulate with many scenarios empirically to illustrate how the proposed framework works. Specifically, we show that how autonomous vehicles could reallocate the tasks among each other in finding dynamically changing paths while certain targets may appear and disappear during the movement mission. We also discuss some challenging problems as a future work.
Highlights
The global market of using autonomous vehicles has grown substantially in recent years and has become an important tool for commercial, government and consumer applications
We proposed a method of using distributed multi-agent systems to achieve the autonomous path planning, obstacle avoidance and dynamic task allocation with minimum cost and maximal reward
Based on Min et al [37], we propose a virtual center of gravity as a virtual leader that we can flexibly adjust the positions for every autonomous vehicle
Summary
The global market of using autonomous vehicles has grown substantially in recent years and has become an important tool for commercial, government and consumer applications. It can support solutions in many fields and is widely used in construction, oil, natural gas, energy, agriculture, military and other fields. Potential applications for autonomous vehicle systems include space-based interferometers, military mission execution [1] (i.e., combat, surveillance and reconnaissance systems), hazardous material handling, distributed re-configurable sensor networks [2]. The coordination between autonomous vehicles becomes a challenging issue for multi-vehicle systems during operation. In the autonomous vehicle operations, there are tasks in controlling the movement situation such as dynamic path planning, mission planning, multiple obstacle avoidance and task coordination among vehicles in response to the state and environmental changes
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