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学术讲座Spatial Intelligence for Human–Robot Interaction: From SLAM to Cooperation and Contention

浏览量:时间:2025-10-13

活动主题:Spatial Intelligence for Human–Robot Interaction: From SLAM to Cooperation and Contention

活动类型:学术交流

举办单位:智能系统与人形机器人国际研究中心

活动时间:2025-10-20 09:00-10:00

活动地点:会议中心2003

面向群体:全院师生

主讲嘉宾:

Shenghai Yuan is a Senior Research Fellow at the Centre for Advanced Robotics Technology Innovation (CARTIN), Nanyang Technological University, Singapore. His work spans SLAM, sensor fusion, navigation, and human–robot interaction. He has authored over a hundred papers and holds more than ten technology disclosures and patents. Actively engaged in the robotics community, he serves as Associate Editor for WSPC Unmanned Systems and organizes focused expert workshops within the IEEE Robotics and Automation Society. He has also participated in and won several international competitions, such as the Barn Challenge (ICRA), Hilti SLAM Challenge (ICRA/IROS), and ICCV SLAM Challenge, and has organized major global events including the Anti-UAV Challenge (CVPR) and the CARIC Mission (IROS). He received Outstanding Reviewer Awards at ICRA and CVPR, and actively serves as a reviewer for all major robotics and computer vision conferences.

内容摘要:

Robots operating in GPS-denied, cluttered, and human-mixed environments must not only perceive and localize but also interact. This talk presents a systems perspective that connects robust SLAM and state estimation to real-world human–robot interaction. We outline an engineering substrate for dependable perception—combining visual/LiDAR odometry, multi-robot localizability, and radio–vision fusion—before exploring cooperative interaction that fuses voice, gaze, and gesture with foundation models, enabling crowd-aware navigation that blends naturally with human flow. We then move to adversarial contexts, including multi-modal anti-UAV sensing and range-only interception under uncertainty, and conclude with see-through-wall AR for restoring shared situational awareness in occluded or high-risk spaces. Field results on UAVs and mobile robots highlight a practical recipe for human-centric, safety-constrained autonomy.

联系人:智能系统与人形机器人国际研究中心,潘婷婷

编辑:袁晓慧