Generative Simulation for Embodied AI in Urban (Micro)mobility

Generative Simulation for Embodied AI in Urban (Micro)mobility

Abstract: Public urban spaces like streetscapes and plazas accommodate human social life in all vibrant variations. Advances in micromobility make public urban spaces no longer exclusive to humans: Food delivery bots and electric wheelchairs are sharing sidewalks with pedestrians, while robot dogs and humanoids have recently emerged in the street. Embodied AI plays a transformative role in shaping the future of urban micromobility, by assisting human operator of these mobile machines to navigate through the unpredictable sidewalks safely. In this talk, I will introduce our effort of building MetaDriverse, a simulation platform that facilitates the computer vision and autonomy research for urban mobility and micromobility. It incorporates generative AI capabilities to simulates diverse urban environments, encompassing a wide range of visual appearances, behavioral dynamics, and terrain structures. It enables the scalable training of embodied AI agents and safety evaluation before real-world deployment. Relevant projects are available at https://metadriverse.github.io/. 

Bio: Bolei Zhou is an Assistant Professor in the Computer Science Department at the UCLA. He earned his Ph.D. from MIT. His research lies at the intersection of computer vision and machine autonomy. He has developed the widely used neural network interpretation method CAM and computer vision benchmarks Places and ADE20K. His current research focuses on data-driven simulation and human-in-the-loop methods for enabling safe and generalizable embodied AI. He has earned multiple recognitions, including NSF CAREER Award, ONR Young Investigator Award, Intel’s Rising Star Faculty Award, and MIT Tech Review's Innovators under 35 in Asia-Pacific.