Papers
27
Total Citations
221
H-Index
9
About
Minh Nhat Vu is a robotics and AI researcher whose work bridges the gap between language-driven perception and robotic manipulation, with additional contributions to motion planning and medical robotics. His research spans several interconnected domains, including inverse kinematics optimization, affordance detection, grasp detection, and trajectory planning for serial manipulators. Vu has made particularly significant contributions to open-vocabulary robotic perception, pioneering methods that enable robots to understand and act upon natural language instructions in 3D environments. His work on language-driven grasp detection and affordance-pose estimation — accumulating over 50 citations across related publications — represents a meaningful shift away from closed-set robotic systems toward more adaptable, language-conditioned intelligent agents. His 2023 paper on machine learning-based inverse kinematics for redundant manipulators has garnered 37 citations, reflecting strong community interest in real-time, optimal IK solutions. Beyond perception, Vu has addressed core motion planning challenges, including singularity avoidance and model predictive trajectory optimization. His work on CathSim, an open-source endovascular simulation platform, demonstrates a commitment to safe, autonomous medical robotics. Collectively, his research reflects a cohesive vision: building robots that are linguistically aware, kinematically robust, and deployable in complex real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Open-Vocabulary Affordance Detection in 3D Point Clouds27 citations · 2023
- 3Language-driven Grasp Detection25 citations · 2024
- 4Language-Conditioned Affordance-Pose Detection in 3D Point Clouds18 citations · 2024
- 5
- 6CathSim: An Open-Source Simulator for Endovascular Intervention15 citations · 2024
- 7
- 8Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidance9 citations · 2024
- 9
- 10