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.
Zusammenfassung
In vielen Domänen wie der Robotik oder dem autonomen Fahren ist die automatisierte Planung von konfliktfreien Pfaden der teilnehmenden mobilen Einheiten, wie zum Beispiel Roboter oder Autos, ein essentieller Arbeitsschritt der Navigationsebene. Vor allem in dichtem Gedränge, wenn sich viele Fahrzeuge einen gemeinsamen Arbeitsbereich mit anderen statischen oder dynamischen Hindernissen teilen, ist die Bestimmung von konfliktfreien Pfaden für alle Fahrzeuge eine herausfordernde aber notwendige Navigationsaufgabe für vollautonome Fahrzeuge. In dieser Arbeit stellen wir einen dezentralen Pfadplanungsalgorithmus für solche Szenarien vor und konzentrieren uns auf die kooperative Verhandlung der konfliktfreien Pfade. Die Pfadsuche auf Navigationsniveau erfolgt mithilfe eines innovativen Graphen-Suchalgorithmus basierend auf A*, der dynamische Hindernisse, bspw. manuell gesteuerte Fahrzeuge oder andere autonome Fahrzeuge, und auch Geschwindigkeitsänderungen der Fahrzeuge berücksichtigt. Für die Verhandlung der konfliktfreien Pfade schlägt das Framework einen dezentralen Ansatz mit lokaler Pfadplanung jedes Fahrzeugs vor. Durch Kommunikation zwischen den mobilen Einheiten wird das kooperative Verhandeln von konfliktfreien Pfaden aller teilnehmenden Fahrzeugen ermöglicht. Der resultierende Prozess aus der Berechnung neuer Pfade und der Verhandlung einer zulässigen Lösungsmenge für alle Fahrzeuge wurde so entwickelt, dass eine deterministische Lösung mit einer endlichen Iterationsanzahl gefunden wird. Außerdem präsentieren wir vielversprechende Simulationsergebnisse des Frameworks in Testszenarien, die viele autonome Fahrzeuge und herausfordernde Hindernisformationen umfassen.
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This publication was written in the framework of the “Profilregion Mobilitätssysteme Karlsruhe” funded by the Ministry of Science, Research and the Arts and the Ministry of Economic Affairs, Labour and Housing of Baden-Württemberg, Germany.
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Rothfuß, S., Prezdnyakov, R., Flad, M. et al. Decentralized path planning for cooperating autonomous mobile units. Forsch Ingenieurwes 83, 137–147 (2019). https://doi.org/10.1007/s10010-019-00339-4
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DOI: https://doi.org/10.1007/s10010-019-00339-4