Embodied Intelligent Driving: Key Technologies and Applications
Embodied intelligence emphasizes direct interaction between machines and the physical world, enabling intelligent agents to exhibit intelligent behaviors and autonomous evolution through the interplay of the brain, body, and environment. This paper discusses key technologies involved in embodied intelligent driving, based on the core requirements of embodied intelligence and autonomous driving, focusing on two core aspects: embodied perception and execution, and embodied learning and evolution. The development status and existing issues of these technologies are analyzed. Additionally, the paper elaborates on datasets and practical system applications related to embodied intelligent driving. Subsequently, it presents reflections and prospects for this field, considering the significant role and application potential of parallel robot, aiming to promote the application of embodied intelligent driving in highly dynamic real-world scenes.
Authors
- Yadong Wang (ORCID: https://orcid.org/0000-0002-2093-026X)
- Tianyu Shen (ORCID: https://orcid.org/0000-0001-7614-7015)
- Kunfeng Wang (ORCID: https://orcid.org/0000-0003-2744-1191)
- Sihan Chen (ORCID: https://orcid.org/0000-0003-1216-6422)
- Zhiwei Li (ORCID: https://orcid.org/0000-0001-7071-199X)
Institutions
- Beijing University of Chemical Technology (CN)
Publication Details
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1109/dtpi61353.2024.10778821
- Citations
- 2
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.53
Funders
- National Natural Science Foundation of China