Abstract
In various domains, e.g. robotics or autonomous driving, automated path planning for conflict-free movements of the participating vehicles, i.e. robots, cars or other mobile units is an essential task on the navigation level. Especially in crowded scenarios in which many vehicles share a common operation area together with other static or dynamic obstacles, finding a set of conflict-free paths for all vehicles is a challenging navigation task that is crucial for fully autonomous vehicles. In this work we propose a decentralized path planning algorithm for such scenarios which focuses on the cooperative negotiation of conflict-free paths. The path planning on navigation level is realized with an innovative graph search algorithm based on A* that incorporates dynamic obstacles (e.g. manually operated vehicles and other autonomous mobile units) and enables the autonomous vehicles to change speed. Furthermore, the framework suggests a decentralized approach, in which each vehicle performs its own path planning locally. Communication between the mobile units allows them to cooperatively negotiate conflict-free paths for all autonomous vehicles participating in the framework. The resulting iterative process of calculating new paths and negotiating a feasible solution set for all vehicles is designed to yield a deterministic solution within a finite number of iterations. We furthermore provide promising simulation results for this framework with test scenarios involving many autonomous vehicles and challenging obstacle formations.
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