Within the paradigm of Physical AI, we bring intelligence into the physical world through robots that can perceive, reason, and act alongside humans. It combines sensing, embodied intelligence, and AI-driven decision-making to enable flexible, adaptive automation in real-world, unstructured environments.

The goal is not just automation, but the ability to handle complex, variable tasks that traditionally require human judgment and adaptability.Through our work, we aim to advance Physical AI systems that make human–robot collaboration practical, scalable, and genuinely useful across domains:

• Autonomous and adaptive cobotic systems
• Perception-driven intelligence 
• Embodied AI for real-world decision-making and control
• Human–robot interaction and collaboration strategies
• Soft and compliant robotics for safe interaction
• Healthcare-oriented collaborative robotic systems
• Lifecycle frameworks for evaluating, deploying, and managing robotic systems in practice