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Title: Tough Cyber-Physical AI
Keywords: Field robotics, disaster response robot, autonomous navigation, retrofit technology, cyber-enhanced rescue canine
Abstract: Cyber-physical AI—intelligent systems that interact with the physical world—is becoming increasingly important in addressing urgent global challenges such as disaster response and the Sustainable Development Goals (SDGs). In particular, “Tough Cyber-physical AI” focuses on enabling systems to operate reliably under harsh and uncertain conditions, with an emphasis on robustness, flexibility, adaptability, and broad applicability.
This talk presents current research initiatives to systematically develop advanced tough cyber-physical AI technologies that can lead progress in the field. By integrating resilient system design with strategies for real-world implementation, we aim to contribute to solving complex societal issues and enhancing industrial competitiveness.
Related Papers
Disaster response robot
A. U Shamsudin et al. (2018). Consistent map building in petrochemical complexes for firefighter robots using SLAM based on GPS and LIDAR, ROBOMECH Journal, 5, 7. DOI: 10.1186/s40648-018-0104-z.
N. Mizuno et al. (2019). Enhanced path smoothing based on conjugate gradient descent for firefighting robots in petrochemical complexes, Advanced Robotics, 33, 14, 687-698. DOI: 10.1080/01691864.2019.1632221.
Retrofit technology for autonomous driving
T. Komatsu et al. (2021). Autonomous Driving of Six-Wheeled Dump Truck with a Retrofitted Robot, Field and Service Robotics. Springer Proceedings in Advanced Robotics, vol 16. Springer, Singapore. https://doi.org/10.1007/978-981-15-9460-1_5
Cyber-enhanced rescue canine
Kazunori Ohno et al.(2019). Cyber-Enhanced Rescue Canine, Disaster Robotics - Results from the ImPACT Tough Robotics Challenge Springer Tracts in Advanced Robotics 128, pp. 143-193, DOI: 10.1007/978-3-030-05321-5_4
