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Published in 2025 IEEE International Conference on Real-time Computing and Robotics (RCAR), 2025
An adaptive prior scene-object SLAM approach designed for robust performance in dynamic environments.
Recommended citation: H. Zhang, T. N. Canh, C. Li and N. Y. Chong, "Adaptive Prior Scene-Object SLAM for Dynamic Environments," IEEE RCAR 2025, Toyama, Japan, 2025, pp. 43-48.
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Published in 2025 25th International Conference on Control, Automation and Systems (ICCAS), 2025
A dual-branch grasping and Stackelberg pushing approach for collaborative manipulation in cluttered scenes.
Recommended citation: J. Ye, C. Li, H. Zhang, P. Zhou and N. Y. Chong, "Collaborative Manipulation in Clutter Scenes Via Dual-Branch Grasping and Stackelberg Pushing," ICCAS 2025, Incheon, Korea, 2025, pp. 739-745.
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Published in Robotics and Autonomous Systems (Under Revision), 2025
A comprehensive survey on semantic visual SLAM covering state of the art, challenges, and future directions.
Recommended citation: T. N. Canh, H. Zhang, X. HoangVan and N. Y. Chong, "Semantic Visual Simultaneous Localization and Mapping: A Survey on State of the Art, Challenges, and Future Directions," Robotics and Autonomous Systems, under revision, 2025.
Published in European Conference on Mobile Robots (ECMR 2025), 2025
An illumination-robust visual SLAM front-end with adaptive feature culling for challenging environments.
Recommended citation: T. N. Canh, B. N. Quoc, H. Zhang, B. R. Veeraiah, X. HoangVan and N. Y. Chong, "IRAF-SLAM: An Illumination-Robust and Adaptive Feature-Culling Front-End for Visual SLAM in Challenging Environments," ECMR 2025, Padova, Italy, 2025, pp. 1-7.
Published in IEEE International Conference on Robotic Computing (IRC), 2025
An intelligent line-assisted SLAM approach using feature awareness for robust performance in dynamic environments.
Recommended citation: H. Zhang, T. N. Canh, C. Li, R. Yang, Y. Ji and N. Y. Chong, "IL-SLAM: Intelligent Line-assisted SLAM Based on Feature Awareness for Dynamic Environments," IEEE IRC 2025, Naples, Italy, 2025.
Published in Robotics and Autonomous Systems, 2025
A scene reliability-based RGB-D SLAM framework that adaptively guides decision-making throughout the entire SLAM pipeline for robust localization across diverse environments.
Recommended citation: H. Zhang, C. Li, T. N. Canh, L. Wang and N. Y. Chong, "SR-SLAM: Scene reliability-based RGB-D SLAM in diverse environments," Robotics and Autonomous Systems, vol. 197, 105306, 2026.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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