Hao Li

	Navigation and 3D Surface Reconstruction from Passive Whisker Sensing Michael A. Lin, Hao Li, Chengyi Xing, Mark Cutkosky Under Review project page / arXiv / video / code We present a method for using highly flexible, curved, passive whiskers mounted along a robot arm to gather sensory data as they brush past objects during normal robot motion.
	The ObjectFolder Benchmark: Multisensory Object-Centric Learning with Neural and Real Objects Ruohan Gao, Yiming Dou, Hao Li, Tanmay Agarwal, Jeannette Bohg, Yunzhu Li, Li Fei-Fei, Jiajun Wu (Equal Contribution) Computer Vision and Pattern Recognition (CVPR), 2023 dataset demo / project page / arXiv / video / code We introduce the OBJECTFOLDER BENCHMARK, a benchmark suite of 10 tasks for multisensory object-centric learning, and the OBJECTFOLDER REAL dataset, in- cluding the multisensory measurements for 100 real-world household objects.
	Sonicverse: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear Ruohan Gao, Hao Li*, Gokul Dharan, Zhuzhu Wang, Chengshu Li, Fei Xia, Silvio Savarese, Li Fei-Fei, Jiajun Wu (Equal Contribution, in alphabetical order) International Conference on Robotics and Automation (ICRA), 2023 project page / arXiv / video / code We introduce SONICVERSE, a multisensory simulation platform with integrated audio-visual simulation for training household agents that can both see and hear. We demonstrate SONICVERSE’s realism via sim-to-real transfer.
	See, Hear, Feel: Smart Sensory Fusion for Robotic Manipulation Hao Li, Yizhi Zhang, Junzhe Zhu, Shaoxiong Wang, Michelle A. Lee, Huazhe Xu, Edward Adelson, Li Fei-Fei, Ruohan Gao†, Jiajun Wu† (Equal Contribution) (†Equal Advising) Conference on Robot Learning (CoRL)*, 2022 project page / arXiv / video / code We build a robot system that can see with a camera, hear with a contact microphone, and feel with a vision-based tactile sensor, with all three sensory modalities fused with a self-attention model.

	Navigation and 3D Surface Reconstruction from Passive Whisker Sensing Michael A. Lin, Hao Li, Chengyi Xing, Mark Cutkosky Under Review project page / arXiv / video / code We present a method for using highly flexible, curved, passive whiskers mounted along a robot arm to gather sensory data as they brush past objects during normal robot motion.
	Grasp as You Say: Language-guided Dexterous Grasp Generation Yi-Lin Wei, Jian-Jian Jiang, Chengyi Xing, Xian-Tuo Tan, Xiao-Ming Wu, Hao Li, Mark Cutkosky Wei-Shi Zheng Under Review project page / arXiv We explores a novel task ""Dexterous Grasp as You Say"" (DexGYS), enabling robots to perform dexterous grasping based on human commands expressed in natural language.
	The Design of a Virtual Prototyping System for Authoring Interactive VR Environments from Real World Scans Ananya Ipsita, Runlin Duan, Hao Li, Subramanian Chidambaram, Yuanzhi Cao, Min Liu, Alexander J Quinn, Karthik Ramani (Equal Contribution) Journal of Computing and Information Science in Engineering (JCISE) arXiv Using our VRFromX system, we performed a usability evaluation with 20 DUs from which 12 were novices in VR programming with a welding use case.
	The ObjectFolder Benchmark: Multisensory Object-Centric Learning with Neural and Real Objects Ruohan Gao, Yiming Dou, Hao Li, Tanmay Agarwal, Jeannette Bohg, Yunzhu Li, Li Fei-Fei, Jiajun Wu (Equal Contribution) Computer Vision and Pattern Recognition (CVPR), 2023 dataset demo / project page / arXiv / video / code We introduce the OBJECTFOLDER BENCHMARK, a benchmark suite of 10 tasks for multisensory object-centric learning, and the OBJECTFOLDER REAL dataset, in- cluding the multisensory measurements for 100 real-world household objects.
	Sonicverse: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear Ruohan Gao, Hao Li*, Gokul Dharan, Zhuzhu Wang, Chengshu Li, Fei Xia, Silvio Savarese, Li Fei-Fei, Jiajun Wu (Equal Contribution, in alphabetical order) International Conference on Robotics and Automation (ICRA), 2023 project page / arXiv / video / code We introduce SONICVERSE, a multisensory simulation platform with integrated audio-visual simulation for training household agents that can both see and hear. We demonstrate SONICVERSE’s realism via sim-to-real transfer.
	See, Hear, Feel: Smart Sensory Fusion for Robotic Manipulation Hao Li, Yizhi Zhang, Junzhe Zhu, Shaoxiong Wang, Michelle A. Lee, Huazhe Xu, Edward Adelson, Li Fei-Fei, Ruohan Gao†, Jiajun Wu† (Equal Contribution) (†Equal Advising) Conference on Robot Learning (CoRL)*, 2022 project page / arXiv / video / code We build a robot system that can see with a camera, hear with a contact microphone, and feel with a vision-based tactile sensor, with all three sensory modalities fused with a self-attention model.
	VRFromX: From Scanned Reality to Interactive Virtual Experience with Human-in-the-Loop Ananya Ipsita, Hao Li, Runlin Duan, Yuanzhi Cao, Subramanian Chidambaram, Min Liu, Karthik Ramani Conference on Human Factors in Computing Systems (CHI), 2021 project page / arXiv / video Using our VRFromX system, users can select region(s) of interest (ROI) in scanned point cloud or sketch in mid-air using a brush tool to retrieve virtual models and then attach behavioral properties to them.