TU Darmstadt / ULB / TUbiblio

Equitable Workload Partitioning for Multi-Robot Exploration through Pairwise Optimization

Klodt, Lukas ; Willert, Volker :
Equitable Workload Partitioning for Multi-Robot Exploration through Pairwise Optimization.
In: IEEE International Conference on Intelligent Robots and Systems (IROS), Sep 28 - Oct 02, Hamburg, Germany. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS)
[Konferenz- oder Workshop-Beitrag], (2015)

Kurzbeschreibung (Abstract)

One of the main challenges when using multiple robots to explore unknown environments is the allocation of target points or regions to the individual units. To date, commonly used approaches produce uneven assignment of targets in situations where multiple targets have to be assigned to each robot. This imbalance can lead to increased overall exploration time and poses an interesting task for further investigation. Based on insights from Multi-Robot Routing and Traveling Salesman Problem research, we propose a specific algorithm for target point allocation that has advantageous properties in highly dynamic applications like exploration. The presented pairwise optimization procedure is suitable for application in distributed and challenging settings, not requiring central coordination or all to all communication, making our exploration strategy robust and flexible. We provide a theoretical analysis and statistical evaluations. Comparisons with representative approaches from the literature show that our algorithm is competitive with the best performing centralized approach.

Typ des Eintrags: Konferenz- oder Workshop-Beitrag (Keine Angabe)
Erschienen: 2015
Autor(en): Klodt, Lukas ; Willert, Volker
Titel: Equitable Workload Partitioning for Multi-Robot Exploration through Pairwise Optimization
Sprache: Englisch
Kurzbeschreibung (Abstract):

One of the main challenges when using multiple robots to explore unknown environments is the allocation of target points or regions to the individual units. To date, commonly used approaches produce uneven assignment of targets in situations where multiple targets have to be assigned to each robot. This imbalance can lead to increased overall exploration time and poses an interesting task for further investigation. Based on insights from Multi-Robot Routing and Traveling Salesman Problem research, we propose a specific algorithm for target point allocation that has advantageous properties in highly dynamic applications like exploration. The presented pairwise optimization procedure is suitable for application in distributed and challenging settings, not requiring central coordination or all to all communication, making our exploration strategy robust and flexible. We provide a theoretical analysis and statistical evaluations. Comparisons with representative approaches from the literature show that our algorithm is competitive with the best performing centralized approach.

Titel der Zeitschrift, Zeitung oder Schriftenreihe: Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS)
Fachbereich(e)/-gebiet(e): Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik > Regelungsmethoden und Robotik
Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik
Fachbereich Elektrotechnik und Informationstechnik
Veranstaltungstitel: IEEE International Conference on Intelligent Robots and Systems (IROS)
Veranstaltungsort: Hamburg, Germany
Veranstaltungsdatum: Sep 28 - Oct 02
Hinterlegungsdatum: 06 Okt 2015 08:17
Export:

Optionen (nur für Redakteure)

Eintrag anzeigen Eintrag anzeigen