News & Media Global R&D Careers Get in Touch Europe © 2025 Toshiba Europe Limited, All Rights Reserved This website uses JavaScript. You will need to enable JavaScript to use the full functionality of this site. We use cookies to ensure that we give you the best experience on our website. If you continue to browse without changing your settings, we’ll assume that you’re happy to receive all the cookies on this Toshiba website. You can also click the “Continue” button to accept our policy in your browser so this message does not appear in the future. You can, of course, change your cookie preferences at any time via your browser settings. Details of our cookies and cookie policy are accessible under the link “Find out more”. 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. The Langauge & Interaction Group (LIG) focuses on learning from interaction with natural language. Dialogue driven deployment-specific interaction with human operators allow for long-horizon planning, refinement and learning with human in the loop. Fast adaptation utilizes local knowledge bases to refine the execution. The Vision & Learning Group (VLG) focuses on learning from interaction in physical environments. Complex and safe manipulation and navigation technology leverage precise 3D geometry and scene understanding in conjunction with strong world-aware action selection frameworks. Learned concepts are effectively transfered to new domains. ReCoRe: Regularized Contrastive Representation Learning of World Model dra P.K. Poudel, Harit Pandya, Stephan Liwick, Roberto Cipolla DiaLoc: An Iterative Approach to Embodied Dialog Localization Chao Zhang, Mohan Li, Ignas Budvytis, Stephan Liwicki Cumulative Attention based streaming transformer ASR with internal language model joint training and rescoring M. Li, C-T Do and R. Doddipatla / Accepted at the 2023 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes Island, Greece, June 2023