A Collision Avoidance Method Based on Deep Reinforcement Learning

dc.contributor.authorFeng, Shuminen
dc.contributor.authorSebastian, Bijoen
dc.contributor.authorBen-Tzvi, Pinhasen
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2021-05-25T12:08:03Zen
dc.date.available2021-05-25T12:08:03Zen
dc.date.issued2021-05-19en
dc.date.updated2021-05-24T15:04:24Zen
dc.description.abstractThis paper set out to investigate the usefulness of solving collision avoidance problems with the help of deep reinforcement learning in an unknown environment, especially in compact spaces, such as a narrow corridor. This research aims to determine whether a deep reinforcement learning-based collision avoidance method is superior to the traditional methods, such as potential field-based methods and dynamic window approach. Besides, the proposed obstacle avoidance method was developed as one of the capabilities to enable each robot in a novel robotic system, namely the Self-reconfigurable and Transformable Omni-Directional Robotic Modules (STORM), to navigate intelligently and safely in an unknown environment. A well-conceived hardware and software architecture with features that enable further expansion and parallel development designed for the ongoing STORM projects is also presented in this work. A virtual STORM module with skid-steer kinematics was simulated in Gazebo to reduce the gap between the simulations and the real-world implementations. Moreover, comparisons among multiple training runs of the neural networks with different parameters related to balance the exploitation and exploration during the training process, as well as tests and experiments conducted in both simulation and real-world, are presented in detail. Directions for future research are also provided in the paper.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationFeng, S.; Sebastian, B.; Ben-Tzvi, P. A Collision Avoidance Method Based on Deep Reinforcement Learning. Robotics 2021, 10, 73.en
dc.identifier.doihttps://doi.org/10.3390/robotics10020073en
dc.identifier.urihttp://hdl.handle.net/10919/103481en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectcollision avoidanceen
dc.subjectneural networken
dc.subjectdeep reinforcement learningen
dc.titleA Collision Avoidance Method Based on Deep Reinforcement Learningen
dc.title.serialRoboticsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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