Robotics Research Internship-Locomotion & Planning (Fall 2026)
Tasks
- Analyze experiment results
- Build GPU accelerated simulation environments
- Debug issues across simulation software hardware and learning
- Design experimental setups for data collection
- Design reinforcement learning pipelines
- Develop sim to real transfer strategies
- Evaluate policies in simulation
- Integrate locomotion control with learning based planning
- Test policies on legged robot platforms
- Validate policies on real hardware
Perks/Benefits
Skills/Tech-stack
C++ | Contact dynamics | Control Theory | Domain Randomization | GPU Acceleration | Isaac Lab | Isaac-Gym | Kinematics | Learning Based Planning | Locomotion control | Motion Planning | Mujoco | Network controllers | Neural Network | Neural Network Controllers | Physics-based Simulation | PyBullet | Python | ROS | ROS2 | Reinforcement Learning | Sim-to-Real | System Identification
Education
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