YOUR NAME
Graduate Student in Embodied AI
Quadrupedal LocomotionReinforcement LearningRobot Navigation
I develop learning-based control and perception systems for robust quadrupedal locomotion and agile navigation in complex environments.
Selected Work
Featured Projects
A selection of robotics projects from simulation training to real-robot deployment.
Projects are being documented and will be added soon.
Research
Research Focus
Learning-based locomotion and navigation for legged robots, with an emphasis on visual perception, robust control, and sim-to-real deployment.
Robust Quadrupedal Locomotion
Learning robust locomotion policies for legged robots operating across diverse terrains and disturbances.
Visual Locomotion and Navigation
Integrating exteroceptive perception with control for obstacle traversal and agile navigation.
Sim-to-Real Deployment
Bridging simulation and physical robots through system validation, deployment tooling, and real-world experimentation.
Approach
Workflow
How I take a locomotion skill from training to the real robot.
- 1
Isaac Gym Training
Massively parallel policy training in simulation.
- 2
Independent Simulation Validation
Robustness checks in held-out environments beyond the training distribution.
- 3
Real-Robot Deployment
Transfer to physical hardware with a real-time control stack.
A representative workflow used across my robotics projects. Individual projects may cover different stages of this pipeline.
Media
Selected Media
Simulation videos, real-robot demos, and system diagrams will appear here as projects are documented.
Media will be added soon.
Contact
Contact
I am interested in research and engineering opportunities in robot learning, quadrupedal locomotion, visual navigation, and embodied intelligence.