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A predictive online path planning and optimization approach for cooperative mobile service robot navigation in industrial applications

: Garcia Lopez, Felipe; Abbenseth, Jannik; Henkel, Christian; Dörr, Stefan

Postprint urn:nbn:de:0011-n-4772916 (632 KByte PDF)
MD5 Fingerprint: 3ced9ff9f3e11d667bd50efaa75d8641
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Erstellt am: 3.1.2018

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Robotics and Automation Society; Ecole Nationale Supérieure de Techniques Avancées -ENSTA-:
European Conference on Mobile Robots, ECMR 2017 : September 6-8, 2017, Paris, France
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5386-1096-1
ISBN: 978-1-5386-1097-8
European Conference on Mobile Robots (ECMR) <2017, Paris>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
Wegplansteuerung; Robotersteuerung; mobiler Roboter; Serviceroboter; Navigation; Autonomer Mobiler Roboter; Cloud Navigation

In this paper we address the problem of online trajectory optimization and cooperative collision avoidance when multiple mobile service robots are operating in close proximity to each other. Using cooperative trajectory optimization to obtain smooth transitions in multi-agent path crossing scenarios applies to the demand for more flexibility and efficiency in industrial autonomous guided vehicle (AGV) systems.
We introduce a general approach for online trajectory optimization in dynamic environments. It involves an elastic-band based method for time-dependent obstacle avoidance combined with a model predictive trajectory planner that takes into account the robot’s kinematic and kinodynamic constraints. We augment that planning approach to be able to cope with shared trajectories of other agents and perform an potential field based cooperative trajectory optimization.
Performance and practical feasibility of the proposed approach are demonstrated in simulation as well as in real world experiments carried out on a representative set of path crossing scenarios with two industrial mobile service robots.