Jane Wu

ICRA Conference 2025 Conference Paper

Hand-Object Interaction Pretraining from Videos

• Himanshu Singh 0002
• Antonio Loquercio
• Carmelo Sferrazza
• Jane Wu
• Haozhi Qi
• Pieter Abbeel
• Jitendra Malik

We present an approach to learn general robot manipulation priors from 3D hand-object interaction trajectories. We build a framework to use in-the-wild videos to generate sensorimotor robot trajectories. We do so by lifting both the human hand and the manipulated object in a shared 3D space and retargeting human motions to robot actions. Generative modeling on this data gives us a task-agnostic base policy. This policy captures a general yet flexible manipulation prior. We empirically demonstrate that finetuning this policy, with both reinforcement learning (RL) and behavior cloning (BC), enables sample-efficient adaptation to downstream tasks and simultaneously improves robustness and generalizability compared to prior approaches. Qualitative experiments are available at: https://hgaurav2k.github.io/hop/.

ICRA Conference 2018 Conference Paper

Intelligent Shipwreck Search Using Autonomous Underwater Vehicles

• Jeffrey Rutledge
• Wentao Yuan
• Jane Wu
• Sam Freed
• Amy Lewis
• Zoë J. Wood
• Timmy Gambin
• Christopher M. Clark

This paper presents an autonomous robot system that is designed to autonomously search for and geo-localize potential underwater archaeological sites. The system, based on Autonomous Underwater Vehicles, invokes a multi-step pipeline. First, the AUV constructs a high altitude scan over a large area to collect low-resolution side scan sonar data. Second, image processing software is employed to automatically detect and identify potential sites of interest. Third, a ranking algorithm assigns importance scores to each site. Fourth, an AUV path planner is used to plan a time-limited path that visits sites with a high importance at a low altitude to acquire high-resolution sonar data. Last, the AUV is deployed to follow this path. This system was implemented and evaluated during an archaeological survey located along the coast of Malta. These experiments demonstrated that the system is able to identify valuable archaeological sites accurately and efficiently in a large previously unsurveyed area. Also, the planned missions led to the discovery of a historical plane wreck whose location was previously unknown.

AAAI Conference 2016 Conference Paper

Human-Robot Trust and Cooperation Through a Game Theoretic Framework

• Erin Paeng
• Jane Wu
• James Boerkoel