On 11 July 2026, Prof. Weisong Wen, Director of the Trustworthy AI and Autonomous Systems Laboratory (TASLAB) at The Hong Kong Polytechnic University (PolyU), received a Best Oral Presentation Award at the 2026 International Conference on Robotics and Learning (ICRL 2026). The conference was held from 10 to 14 July in Yili, Xinjiang, China.
Prof. Weisong Wen (right) receives the Best Oral Presentation Award during the ICRL 2026 award ceremony in Yili, Xinjiang.
ICRL 2026 was hosted by the editorial board of the Robot Learning journal and ELSP Publishing and organised by Yili Normal University, with Shanghai Jiao Tong University, Hunan University, Wuhan University and Westlake University as co-organisers. It gathered scholars, engineers and industry leaders working on embodied intelligence, neuro-robotics, multimodal perception, adaptive control and robot learning.
The award-winning talk
Prof. Wen’s oral presentation, “Efficient and Outlier-Aware GNSS/LiDAR/inertial Integrated Positioning for Autonomous Systems in Urban Canyons”, was selected by the conference for its Best Oral Presentation Award. The recognition highlights TASLAB’s contribution to trustworthy autonomy and robust perception, and its relevance to the robotics and learning community that ICRL 2026 brought together.
The talk connected TASLAB’s research on robust localization and multi-sensor fusion to the conference’s central themes of robot learning and embodied intelligence, showing how reliable perception and state estimation underpin autonomous systems operating in complex real-world environments. The presentation was well received by an audience of leading robotics researchers from institutions in China and abroad.
The ICRL 2026 Best Oral Presentation certificate presented to Prof. Weisong Wen.
The 2026 International Conference on Robotics and Learning (ICRL 2026), held 10–14 July in Yili, Xinjiang.
The award reflects TASLAB’s continuing commitment to advancing trustworthy AI and autonomous systems, and to academic exchange with the international robotics and learning community.