#artificialintelligence #embodied #robot #robotics

Abstract:
Having a humanoid robot operating like a human has been a long-standing goal in robotics. The applications go much beyond moving boxes in the factory. The humanoid robot provides a generalized purpose platform to conduct diverse tasks we do in our daily lives. In this talk, we study learning-based approaches for both the mobility and manipulation skills of the humanoid robot, with the goal of generalization to diverse tasks, objects and scenes. We will first discuss how to perform whole-body control in humanoids to generate rich, diverse, and expressive motions. We then discuss what will be the foundation model for the robot to perceive the visual world and perform mobile manipulation in the wild. Finally, we will dive into the humanoid’s manipulator, the hands, and study tactile sensing for flexible manipulations.

Bio:
Xiaolong Wang is an Assistant Professor in the ECE department at the University of California, San Diego. He received his Ph.D. in Robotics at Carnegie Mellon University. His postdoctoral training was at the University of California, Berkeley. His research focuses on the intersection between computer vision and robotics. His specific interest lies in learning 3D and dynamics representations from videos and physical robotic interaction data. These comprehensive representations are utilized to facilitate the learning of robot skills, with the goal of generalizing the robot to interact effectively with a wide range of objects and environments in the real physical world. He is the recipient of the NSF CAREER Award, Intel Rising Star Faculty Award, and Research Awards from Sony, Amazon, Adobe, and Cisco.