{"id":"doi:10.1109/access.2021.3076530","kind":"review","title":"Motion Planning for Mobile Robots—Focusing on Deep Reinforcement Learning: A Systematic Review","authors":["Huihui Sun","Weijie Zhang","Runxiang Yu","Yujie Zhang"],"author_count":4,"year":2021,"published":"2021-01-01","venue":"IEEE Access","cited_by":142,"doi":"10.1109/access.2021.3076530","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1109/access.2021.3076530","archive_url":"https://space-kitty.com/papers/doi:10.1109/access.2021.3076530","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3158592412","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09419029.pdf","abstract":"Mobile robots contributed significantly to the intelligent development of human society, and the motion-planning policy is critical for mobile robots. This paper reviews the methods based on motion-planning policy, especially the ones involving Deep Reinforcement Learning (DRL) in the unstructured environment. The conventional methods of DRL are categorized to value-based, policy-based and actor-critic-based algorithms, and the corresponding theories and applications are surveyed. Furthermore, the recently-emerged methods of DRL are also surveyed, especially the ones involving the imitation learning, meta-learning and multi-robot systems. According to the surveys, the potential research directions of motion-planning algorithms serving for mobile robots are enlightened.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Reinforcement Learning in Robotics"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Motion Planning for Mobile Robots—Focusing on Deep Reinforcement Learning: A Systematic Review\" by Huihui Sun, Weijie Zhang, Runxiang Yu et al., https://doi.org/10.1109/access.2021.3076530, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"robotics-embodied","name":"Robot Learning & Embodied AI","domain_slug":"ai"}],"cited_in_dossiers":[]}