Event
Bayesian-optimization study tunes walking controllers on ATRIAS hardware
Key points
- The paper applies Bayesian optimization with a domain-informed feature transform to bipedal locomotion controller tuning.
- The method is evaluated on the ATRIAS biped in simulation and on hardware, including two walking controllers on the real robot.
- It gives ATRIAS a concrete learning-on-hardware research record for sample-efficient bipedal gait optimization.
Company context
US robotics company focused on humanoid systems for logistics and warehouse automation. Digit is designed for real-world material handling tasks in structured environments.
Context
- Company
- Agility Robotics
- Segment
- Humanoid
- Event type
- Research Publication
- Geography
- Salem · United States