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Computational Visual Media 2020, 6(3): 225-245 https://doi.org/10.1007/s41095-020-0179-3
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View planning in robot active vision: A survey of systems, algorithms, and applications

Show Author's Information Rui Zeng1,  Yuhui Wen1,  Wang Zhao1,  Yong-Jin Liu1( )
BNRist, Department of Computer Science and Technology, Tsinghua University, Beijing, China
Keywords:
robotic, view planning, active vision, next-best view, sensor planning
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Zeng R, Wen Y, Zhao W, et al. View planning in robot active vision: A survey of systems, algorithms, and applications. Computational Visual Media, 2020, 6(3): 225-245. https://doi.org/10.1007/s41095-020-0179-3
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Abstract Full text About this article

Rapid development of artificial intelligence motivates researchers to expand the capabilities of intelligent and autonomous robots. In many robotic applications, robots are required to make planning decisions based on perceptual information to achieve diverse goals in an efficient and effective way. The planning problem has been investigated in active robot vision, in which a robot analyzes its environment and its own state in order to move sensors to obtain more useful information under certain constraints. View planning, which aims to find the best view sequence for a sensor, is one of the most challenging issues in active robot vision. The quality and efficiency of view planning are critical for many robot systems and are influenced by the nature of their tasks, hardware conditions, scanning states, and planning strategies. In this paper, we first summarize some basic concepts of active robot vision, and then review representative work on systems, algorithms and applications from four perspectives: object reconstruction, scene reconstruction, object recognition, and pose estimation. Finally, some potential directions are outlined for future work.


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About this article

View planning in robot active vision: A survey of systems, algorithms, and applications

Show Author's information Rui Zeng1, Yuhui Wen1, Wang Zhao1, Yong-Jin Liu1( )
BNRist, Department of Computer Science and Technology, Tsinghua University, Beijing, China

Abstract

Rapid development of artificial intelligence motivates researchers to expand the capabilities of intelligent and autonomous robots. In many robotic applications, robots are required to make planning decisions based on perceptual information to achieve diverse goals in an efficient and effective way. The planning problem has been investigated in active robot vision, in which a robot analyzes its environment and its own state in order to move sensors to obtain more useful information under certain constraints. View planning, which aims to find the best view sequence for a sensor, is one of the most challenging issues in active robot vision. The quality and efficiency of view planning are critical for many robot systems and are influenced by the nature of their tasks, hardware conditions, scanning states, and planning strategies. In this paper, we first summarize some basic concepts of active robot vision, and then review representative work on systems, algorithms and applications from four perspectives: object reconstruction, scene reconstruction, object recognition, and pose estimation. Finally, some potential directions are outlined for future work.

Keywords: robotic, view planning, active vision, next-best view, sensor planning

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Received: 18 March 2020
Accepted: 01 May 2020
Published: 01 August 2020
Issue date: September 2020

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© The Author(s) 2020

Acknowledgements

The authors would like to thank Dr. Shihao Wu of Shenzhen VisuCA Key Laboratory/SIAT for providing Fig. 8, Dr. Vasquez-Gomez of the Instituto Nacional de Astrofísica Óptica y Electrónica (INAOE) for providing Fig. 3, Prof. Kai Xu of the National University of Defense Technology and AICFVE Beijing Film Academy for providing Fig. 12, Dr. Xi Xia of the University of Science and Technology of China for providing Fig. 11, and Dr. Delmerico of the Robotics and Perception Group, University of Zurich for providing Fig. 9. This work was partially supported by a grant from the Science and Technology Department of Jiangsu Province, China.

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