Robot Manipulation Based on Embodied Visual Perception: A Survey
ABSTRACT Visual perception is critical in robotic operations, particularly in collaborative and autonomous robot systems. Through efficient visual systems, robots can acquire and process environmental information in real‐time, recognise objects, assess spatial relationships, and make adaptive decisions. This review aims to provide a comprehensive overview of the latest advancements in the field of vision as applied to robotic perception, focusing primarily on visual applications in the areas of object perception, self‐perception, human–robot collaboration, and multi‐robot collaboration. By summarising the current state of development and analysing the challenges and opportunities that remain in these areas, this paper offers a thorough examination of the integration of visual perception with operational robotics. It further inspires future research and drives the application and development of visual perception across various robotic domains, enabling operational robots to better adapt to complex environments and reliably accomplish tasks.
Authors
- Runwei Ding (ORCID: https://orcid.org/0000-0003-4987-0405)
- Qing Hong Gao (ORCID: https://orcid.org/0000-0002-5395-6175)
- Tin Lun Lam (ORCID: https://orcid.org/0000-0002-6363-1446)
- Sicheng Wang (ORCID: https://orcid.org/0000-0002-5224-5697)
- Tianwei Zhang (ORCID: https://orcid.org/0000-0002-1462-5402)
- Milutin N. Nikolić
Institutions
- Sun Yat-sen University (CN)
- University of Novi Sad (RS)
- Shenzhen Academy of Robotics (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- Peng Cheng Laboratory (CN)
Publication Details
- Journal
- CAAI Transactions on Intelligence Technology
- Published
- 2025-06-21
- DOI
- https://doi.org/10.1049/cit2.70022
- Citations
- 4
- Primary Topic
- Robot Manipulation and Learning
- Type
- article
- Field-Weighted Citation Impact
- 4.86
Funders
- National Natural Science Foundation of China
- Basic and Applied Basic Research Foundation of Guangdong Province