Embodied AI

Embodied AI refers to agent-based AI systems that can manipulate objects and communicate with people, assisting us in physical tasks. These agents learn interactively from users in their environment, adapting quickly, and continuously expanding their capabilities. CRL’s research will strive to yield technologies capable of natural interaction with the physical environment and human operators, building a dynamic catalog of skills that encompasses perception, reasoning, and action.

The classical paradigm of perception and manipulation systems is to understand to act – e.g. segmentation is used to detect pedestrians so that ADAS can operate. In the new framework of Embodied AI, we instead act to understand. Specifically, Embodied AI has fast adaptation and continuous learning through task execution at its core. The system interacts to improve perception, reasoning, and its action towards future task completion. Human interaction will enable seamless reprogramming (teaching) of physical systems, while autonomous actions in physical space enable us to learn about new environments. The need for expert knowledge to redeploy classical AI to new tasks is eliminated.

Embodied AI is critical to addressing the real-world challenges of the next generation industry. Adaptation and resilience is at the core of embodied AI as it ensuring a workforce that can truly leverage the power of AI through simple human and machine interaction in ever changing tasks and deployments. Adaptation and learning also ensures sustainability as we constantly improve the applicability of existing hardware through ever learning software algorithms. CRL’s Embodied AI will enable a versatile assistive system for a multitude of tasks. Since Embodied AI focuses on the software, we can learn from many modalities and deployments ensuring a seamless integration of disparate systems.