Chao Tang

About

Chao Tang is an emerging robotics researcher whose work sits at the intersection of robot manipulation, scene understanding, and human-robot interaction. His research focuses primarily on task-oriented grasping, assistive robotics, and vision-language integration — areas critical to enabling robots to operate meaningfully in everyday household environments. Tang's most significant contribution is his pioneering work on task-oriented grasp prediction using visual-language inputs, which has garnered 38 citations since 2023, establishing him as a notable voice in this rapidly evolving field. By bridging natural language instructions with robotic grasping behavior, his research addresses a fundamental challenge: enabling robots to not only identify objects but grasp them in contextually appropriate ways for specific tasks. His subsequent work, including RTAGrasp and FoundationGrasp, extends this vision by leveraging foundation models and human video demonstrations to reduce costly manual annotations. Beyond grasping, Tang has contributed to object search using commonsense scene graphs, multi-view object rearrangement, and relationship-oriented scene understanding — collectively advancing the cognitive capabilities of assistive robots. His earlier work on robotic fish monitoring systems demonstrates a broader curiosity about autonomous systems across environments. With a research portfolio rapidly accumulating citations, Tang represents a promising contributor to the future of intelligent, task-aware robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Task-Oriented Grasp Prediction with Visual-Language Inputs

   38 citations · 2023
2. 2
   Efficient Object Rearrangement via Multi-view Fusion

   6 citations · 2024
3. 3
   Commonsense Scene Graph-based Target Localization for Object Search

   5 citations · 2024
4. 4
   RTAGrasp: Learning Task-Oriented Grasping from Human Videos via Retrieval, Transfer, and Alignment

   5 citations · 2025
5. 5
   Relationship Oriented Semantic Scene Understanding for Daily Manipulation Tasks

   4 citations · 2022
6. 6
   Primitive Shape Recognition for Object Grasping

   4 citations · 2022
7. 7
   Design of a monitoring system for robotic fish in underwater environment

   2 citations · 2018
8. 8
   Task-Oriented Grasp Prediction with Visual-Language Inputs

   2 citations · 2023
9. 9
   FoundationGrasp: Generalizable Task-Oriented Grasping with Foundation Models

   2 citations · 2024

Key Collaborators

Contact & Links