题  目：Robot Control, Learning and Teleoperation

内容简介：Nowadays robots are expected to be of increasing intelligence to deal with a large range of tasks. Especially, robots are supposed to be able to learn skills from our humans and perform dexterous manipulation in a human-like manner. A number of learning algorithms and techniques have been developed and successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform new tasks. This talk will present my recent research progress on human-in-the-loop learning for robots to acquire and generalize manipulation skills. It will also introduce my studies on human-like control design inspired by human motor behaviors from more than a decade ago. The control and learning technologies I developed have been particularly applied to robot teleoperation, for which I have also extensively investigated human robot interaction interface. This talk will also cover my recent work on teleoperation for minimum invasive surgery and ultrasound scanning.

报告人：杨辰光

报告人简介：华南理工大学教授、博导，广东省智能系统控制工程技术研究中心主任，

美国电气与电子工程师学会（IEEE）Fellow。他是IEEE协作自动化柔性制造（CAFΜ）技术委员的联合主席、Robot Learning期刊的主编、Frontiers on Robotics and AI计算智能领域主编、IEEE Transactions on Systems, Man and Cybernetics: Systems的高级编委。作为第一作者，他获得过机器人学顶刊IEEE Transactions on Robotics最佳论文奖（2012）和计算智能领域顶刊IEEE Transactions on Neural Networks and Learning Systems杰出论文奖（2022）。以第一完成人获得过自动化学会自然科学一等奖，广东省自然科学二等奖以及教育部自然科学二等奖，并多次入选科睿唯安全球高被引学者。

时  间：2024年7月29日（周一）下午15：30开始

地  点：南海楼407室

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信息科学技术学院

2024年7月28日