Yilin Wu

	Learning Generalizable Tool-use Skills through Trajectory Generation Carl Qi , Yilin Wu , Lifan Yu, Haoyue Liu, Bowen Jiang, Xingyu Lin , David Held Under review, 2024 project page / paper / video In this work, we propose to learn a generative model of the tool-use trajectories as a sequence of point clouds, which generalizes to different tool shapes. We train a single model for four different challenging deformable object manipulation tasks, including cutting, rolling, large scooping, small scooping.
	Spatially-Grounded Motion Primitives for Manipulation Bowen Jiang, Yilin Wu, Wenxuan Zhou, Chris Paxton, David Held Under review, 2024 project page / Preprint / video In this work, we introduce spatially-grounded parameterized motion primitives to improve policy generalization for robotic manipulation tasks. By grounding the primitives on a spatial location in the environment, our proposed method is able to effectively generalize across object shape and pose variations.
	DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset DROID Dataset Team In submission to RSS, 2024 project page / paper / video In this work, we introduce DROID (Distributed Robot Interaction Dataset), a diverse robot manipulation dataset with 76k demonstration trajectories or 350h of interaction data, collected across 564 scenes and 86 tasks by 50 data collectors in North America, Asia, and Europe over the course of 12 months. We demonstrate that training with DROID leads to policies with higher performance, greater robustness, and improved generalization ability.
	Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment Collaboration Team ICRA, 2024 project page / paper / video We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks).
	Stabilize to Act: Learning to Coordinate for Bimanual Manipulation Jennifer Grannen, Yilin Wu, Brandon Vu, Dorsa Sadigh CoRL, 2023, Oral Presentation project page / paper / video We present a system for bimanual manipulation that coordinates by assigning roles to arms: a stabilizing arm holds an object stationary while an acting arm acts in this simplified environment.
	In-Mouth Robotic Bite Transfer With Visual and Haptic Sensing Lorenzo Shaikewitz, Yilin Wu, Suneel Belkhale, Jennifer Grannen, Priya Sundaresan, Dorsa Sadigh ICRA*, 2023 project page / blog post / paper / video We build a semi autonomous robotic system to do in-mouth transfer of food safely and comfortably for disabled people. The system is composed of a force-reactive controller to safely accommodate the user’s motions throughout the transfer, a novel dexterous wrist-like end effector to reduce the discomfort and a visual sensor to identify the user mouth.
	Learning Bimanual Scooping Policies for Food Acquisition Jennifer Grannen, Yilin Wu, Suneel Belkhale, Dorsa Sadigh Corl, 2022 project page / blog post / paper / video We propose a general bimanual scooping primitive and an adaptive stabilization strategy that enables successful acquisition of a diverse set of food geometries and physical properties with close-loop visual feedback.
	Solving Compositional Reinforcement Learning Problems via Task Reduction Yunfei Li, Yilin Wu, Huazhe Xu, Xiaolong Wang, Yi Wu ICLR, 2021 project page / arXiv / video With task reduction and self-imitation, our RL agent is able to progressively tackle challenging sparse-reward and continuous control tasks with high efficiency.
	Learning to Manipulate Deformable Objects without Demonstrations Yilin Wu, Wilson Yan, Thanard Kurutach, Lerrel Pinto, Pieter Abbeel RSS, 2020 project page / blog post / arXiv / video / code Our work is to train a RL agent to acquire rope-spreading and cloth-spreading skills without any human demonstrations and the method applies to real robots after domain adaptation.

	Carnegie Mello University Doctor of Philosophy in Robotics Aug '23 - Now Research: Working as a Research Assistant at CMU Robots Perceiving and Doing Lab (RPAD)
	Stanford University Master of Science in Computer Science Sept '21 - Jun '23 Research: Worked as a Research Assistant at Stanford ILIAD Lab Worked on Assistive Feeding Project Teaching Experience: CA for CS 148 Introduction to Computer Graphics and Imaging \| Fall 2022 CA for CS 221: Artificial Intelligence: Principles and Techniques \| Spring 2023, Spring 2022 and Fall 2021 CA for CS 182 Ethics, Public Policy, and Technological Change \| Winter 2023, Winter 2022
	Shanghai Jiao Tong University Bachelor of Science in Information Security Sept '16 - June '20 Awards: Graduated with honor: Outstanding Graduate of Shanghai \| 2020 Hongyi Scholarship (Top 10 Summer Research among Undergraduates) \| 2019 Academic Excellence Scholarship(Second-Class) of SJTU \| 2017 & 2018 National Scholarship (<1%) \| 2017
	University of California, Berkeley Exchange Student in Computer Science Jan '19 - Sept '19 Research: Worked as a Research Assistant at UC Berkeley BAIR Lab Worked on Deformable Object Manipulation Project