Papers
2
Total Citations
6
H-Index
2
About
My Ha Le’s research bridges the gap between autonomous robotics and surgical precision, focusing on two critical challenges: safe navigation in dynamic environments and force sensing in minimally invasive procedures. In their 2024 work on model predictive control (MPC) for mobile robots, Le developed a real-time obstacle avoidance system integrated with the Robot Operating System (ROS) and Gazebo simulation, enabling wheeled mobile robots to navigate cluttered indoor spaces with dynamic obstacles—a foundational contribution to autonomous navigation. Complementing this, Le’s vision-based force estimation for telesurgery introduces a novel method that uses contact detection and local stiffness models to infer force without direct sensors, overcoming a key barrier to haptic feedback in robotic surgery. Both papers, each garnering 3 citations, demonstrate Le’s ability to tackle practical, high-impact problems with elegant computational solutions. Their work not only advances the state of the art in mobile robotics and surgical assistance but also offers scalable, cost-effective approaches for real-world deployment. Le’s dual focus on autonomy and medical robotics positions them as a rising contributor to intelligent systems that enhance safety and precision in human-centered applications.
Research Focus
Key Achievements
Top Papers
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- 2