Research on the Mechanism and Path of Augmented Reality Empowering Robot 2D Image Perception
DOI: https://doi.org/10.62517/jike.202604212
Author(s)
Benbo Cao
Affiliation(s)
School of Waterford, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Abstract
This article focuses on the mechanisms and paths by which augmented reality empowers 2D image perception in robots. Firstly, the significant meaning of 2D image perception for robots and the current challenges they face are expounded, and then the necessity of empowering it with augmented reality technology is introduced. An in-depth analysis was conducted on the internal mechanisms by which augmented reality empowers 2D image perception in robots, including information fusion mechanisms, spatial mapping mechanisms, etc. On this basis, specific paths to achieve this empowerment were explored, covering paths such as technology integration and application scenario expansion. It aims to provide theoretical support and direction guidance for promoting the improvement of 2D image perception capabilities of robots and the wide application of augmented reality technology in the field of robotics.
Keywords
Augmented Reality; Robot; 2D Image Perception; Mechanism; Path
References
[1] Dzedzickis, A., Subačiūtė-Žemaitienė, J., Šutinys, E., Samukaitė-Bubnienė, U., & Bučinskas, V. (2021). Advanced applications of industrial robotics: New trends and possibilities. Applied Sciences, 12(1), 135.
[2] Ji, T., Sivakumar, A. N., Chowdhary, G., & Driggs-Campbell, K. (2022). Proactive anomaly detection for robot navigation with multi-sensor fusion. IEEE Robotics and Automation Letters, 7(2), 4975-4982.
[3] Martin-Martin, R., Patel, M., Rezatofighi, H., Shenoi, A., Gwak, J., Frankel, E., ... & Savarese, S. (2021). Jrdb: A dataset and benchmark of egocentric robot visual perception of humans in built environments. IEEE transactions on pattern analysis and machine intelligence, 45(6), 6748-6765.
[4] Hua, C. (2022, October). A Review of Visual Perception for Mobile Robot Navigation: Methods, Limitation, and Applications. In 2022 2nd International Conference on Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI) (pp. 729-737). IEEE.
[5] Makhataeva, Z., & Varol, H. A. (2020). Augmented reality for robotics: A review. Robotics, 9(2), 21.
[6] Bonci, A., Cen Cheng, P. D., Indri, M., Nabissi, G., & Sibona, F. (2021). Human-robot perception in industrial environments: A survey. Sensors, 21(5), 1571.
[7] Wu, J., Gao, J., Yi, J., Liu, P., & Xu, C. (2022, November). Environment perception technology for intelligent robots in complex environments: A Review. In 2022 7th International Conference on Communication, Image and Signal Processing (CCISP) (pp. 479-485). IEEE.
[8] Wang, S., Nikolić, M. N., Lam, T. L., Gao, Q., Ding, R., & Zhang, T. (2025). Robot Manipulation Based on Embodied Visual Perception: A Survey. CAAI Transactions on Intelligence Technology.