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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robot Manipulation Based on Embodied Visual Perception: A Survey

Runwei Ding, Qing Hong Gao, Tin Lun Lam, Sicheng Wang et al.
4 citations
CAAI Transactions on Intelligence Technology
Robot Manipulation and Learning
4.86
article

Robot Manipulation Based on Embodied Visual Perception: A Survey

Runwei Ding, Qing Hong Gao, Tin Lun Lam, Sicheng Wang, Tianwei Zhang, Milutin N. Nikolić
article en
4 citations

Abstract

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.

CAAI Transactions on Intelligence TechnologyVol. 10(4)
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)
National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 5%
Robot Manipulation and Learning
4.86
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Robot Manipulation Based on Embodied Visual Perception: A Survey — Runwei Ding, Qing Hong Gao, et al. · CAAI Transactions on Intelligence Technology (2025) | TGRS Research Map | TGRS