Papers
8
Total Citations
68
H-Index
4
About
Biao Jia is a robotics researcher whose work focuses on the autonomous manipulation of deformable objects, bridging the gap between high-level instructions and low-level robot control. His primary research areas include deformable object manipulation, motion planning for high-degree-of-freedom (DOF) systems, and the integration of natural language processing with robotic control. Jia’s major contribution is a novel visual feedback dictionary-based method for manipulating highly deformable materials like clothes, enabling robots to achieve desired configurations despite complex physical properties—a paper that has garnered 39 citations. He has also developed efficient algorithms for motion planning in high-DOF soft robots and articulated systems interacting with deformable environments, as well as a sim-to-real framework for robotic sketching using behavior cloning and reinforcement learning. His work on learning-based feedback controllers for deformable object manipulation and dynamic constraint mapping for natural language-driven motion planning further demonstrates his impact. With over 60 total citations, Jia’s research advances practical robotic systems capable of handling real-world challenges, from household tasks to artistic applications.
Research Focus
Key Achievements
Top Papers
- 1Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary39 citations · 2018
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- 4Learning-based Feedback Controller for Deformable Object Manipulation6 citations · 2018
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- 7Multi-Robot Path Planning Using Medial-Axis-Based Pebble-Graph Embedding2 citations · 2022
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