31 citations · 88 across the 23 of their papers we have counts for
9 papers · 1 filter
ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation
Enyu Zhao, Vedant Raval, Hejia Zhang +5
Vision-Language Models (VLMs) have revolutionized artificial intelligence and robotics due to their commonsense reasoning capabilities. In robotic manipulation, VLMs are used prima…
GPT-Fabric: Smoothing and Folding Fabric by Leveraging Pre-Trained Foundation Models
Vedant Raval, Enyu Zhao, Hejia Zhang +2
Fabric manipulation has applications in folding blankets, handling patient clothing, and protecting items with covers. It is challenging for robots to perform fabric manipulation s…
Multi-Robot Geometric Task-and-Motion Planning for Collaborative Manipulation Tasks
Hejia Zhang, Shao-Hung Chan, Jie Zhong +6
We address multi-robot geometric task-and-motion planning (MR-GTAMP) problems in synchronous, monotone setups. The goal of the MR-GTAMP problem is to move objects with multiple rob…
Surrogate Assisted Generation of Human-Robot Interaction Scenarios
Varun Bhatt, Heramb Nemlekar, Matthew C. Fontaine +4
As human-robot interaction (HRI) systems advance, so does the difficulty of evaluating and understanding the strengths and limitations of these systems in different environments an…
PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection
Shivin Dass, Karl Pertsch, Hejia Zhang +3
Large-scale data is an essential component of machine learning as demonstrated in recent advances in natural language processing and computer vision research. However, collecting l…
A MIP-Based Approach for Multi-Robot Geometric Task-and-Motion Planning
Hejia Zhang, Shao-Hung Chan, Jie Zhong +3
We address multi-robot geometric task-and-motion planning (MR-GTAMP) problems in synchronous, monotone setups. The goal of the MR-GTAMP problem is to move objects with multiple rob…
Zero-Shot Imitating Collaborative Manipulation Plans from YouTube Cooking Videos
Hejia Zhang, Jie Zhong, Stefanos Nikolaidis
People often watch videos on the web to learn how to cook new recipes, assemble furniture or repair a computer. We wish to enable robots with the very same capability. This is chal…
Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing
Zhanpeng He, Ryan Julian, Eric Heiden +5
Simulation-to-real transfer is an important strategy for making reinforcement learning practical with real robots. Successful sim-to-real transfer systems have difficulty producing…
Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills
Hejia Zhang, Eric Heiden, Stefanos Nikolaidis +2
Personal robots assisting humans must perform complex manipulation tasks that are typically difficult to specify in traditional motion planning pipelines, where multiple objectives…