At the NEAR Lab, our research centers on neuro-embodied adaptive robotics, robotic systems in which intelligence emerges from the interaction between neural mechanisms, physical bodies, and the environment.
We pursue an integrated approach spanning robot design, modeling, control, and learning, with an emphasis on real-world embodiment and lifelong adaptation.
Bio-Inspired Flapping-Wing Robotics
Uncover principles of embodied intelligence from flapping insects and vertebrate flyers.
- Flapping-wing and morphologically adaptive robots
- Aerodynamic–structural coupling
- Highly dynamic, underactuated platforms
Neuro-Embodied & Neuromorphic Systems
Neural principles of control and learning grounded in physical robotic systems.
- Neurorobotics integrating sensing and actuation
- Neuromorphic and neural-inspired control
- Energy-efficient neural hardware
Adaptive & Lifelong Learning
Robots that learn continuously through interaction, not static datasets.
- Lifelong and online learning
- Co-adaptation of body, control, and behavior
- Long-term autonomy under changing environments
Modeling, Dynamics & Control
Theories and models that support understanding and design of complex robots.
- Hybrid modeling and physical simulator
- Nonlinear dynamics and reduced-order models
- Data-driven control
Ongoing & Future Directions
Our research continues to expand toward:
- tight integration of neuromorphic hardware and robotic platforms
- co-design of morphology, control, and learning mechanisms
- experimental studies of development, adaptation, and evolution in robots
