Task assignment and trajectory planning in dynamic environments for multiple vehicles
2015 (English)In: Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389, E-ISSN 1879-8314, Vol. 278, p. 179-181Article in journal (Refereed) Published
Abstract [en]
We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost over all vehicle trajectories using the classical Hungarian algorithm. To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonian optimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance. © 2015 The authors and IOS Press. All rights reserved.
Place, publisher, year, edition, pages
Washington, DC: IOS Press, 2015. Vol. 278, p. 179-181
Keywords [en]
Artificial intelligence, Collision avoidance, Economic and social effects, Fleet operations, Motion planning, Redundant manipulators, Trajectories, Vehicles, Automated guided vehicles, Collision-free trajectory, Dynamic environments, Dynamic obstacle avoidance, Integrated frameworks, Multirobots, Path planners, Task assignment, Automatic guided vehicles
National Category
Robotics
Identifiers
URN: urn:nbn:se:hh:diva-36556DOI: 10.3233/978-1-61499-589-0-179ISI: 000455950400020Scopus ID: 2-s2.0-84963701453OAI: oai:DiVA.org:hh-36556DiVA, id: diva2:1231387
Conference
The Thirteenth Scandinavian Conference on Artificial Intelligence, Halmstad, Sweden, 4-5 November, 2015
2018-07-062018-07-062020-01-31Bibliographically approved