Chris Paxton
Wuhu Hit Robot Technology Research Institute(CN)
Publications by Year
Research Areas
Robot Manipulation and Learning, Multimodal Machine Learning Applications, Robotic Path Planning Algorithms, Reinforcement Learning in Robotics, AI-based Problem Solving and Planning
Most-Cited Works
- → CoSTAR: Instructing collaborative robots with behavior trees and vision(2017)168 cited
- → Task and Motion Planning with Large Language Models for Object Rearrangement(2023)121 cited
- → Combining neural networks and tree search for task and motion planning in challenging environments(2017)103 cited
- → A framework for end-user instruction of a robot assistant for manufacturing(2015)97 cited
- → Reactive Human-to-Robot Handovers of Arbitrary Objects(2021)81 cited
- → CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory(2023)66 cited
- → Correcting Robot Plans with Natural Language Feedback(2022)63 cited
- → Real-world robot applications of foundation models: a review(2024)55 cited
- → StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objects(2022)54 cited
- → Pre-Trained Language Models for Interactive Decision-Making(2022)53 cited