RESEARCH & EDUCATION FIELDS
Quantum computing R&E field
Quantum computers are expected to be the next-generation ultra-high–speed supercomputers based on quantum mechanics. Manipulating qubits on a large-scale will enable massive parallel supercomputing. Our research on potential applications is also underway and should contribute to solving the information processing issues required for a super smart society.
Quantum sensor R&E field
A sensor is defined as a device that converts a physical phenomenon and the state of an object into an electric signal. A quantum sensor is a type of sensor that uses the quantum effect (a phenomenon in quantum mechanics). Because quantum sensors are more sensitive than conventional sensors, they are expected to contribute to a super smart society. We are working on the development of such sensors with an emphasis on SQUID, which is a quantum sensor capable of detecting minute magnetic fields.
Smart robotics(Robot Zoo Aqua, Robot Zoo Sky) R&E field
Smart robotics (Robot Zoo Sky)
Robot Zoo Sky is the robotics experimental platform for simultaneous coordinated control of multiple robots such as drones. Utilizing cutting-edge distributed control technology, we develop environmental monitoring technologies to realize a reliable and safe society. Furthermore, we offer students opportunities to learn about technology that securely controls multiple components and systems connected in networks, which is a fundamental technical skill in the era of IoT.
Smart robotics (Robot Zoo Aqua)
The oceans –that is, water –account for approximately 70% of the Earth’s surface. However, much of this aquatic environment remains unknown. To resolve this shortcoming, Robot Zoo Aqua employs approaches from the standpoint of robotics to social issues related to the aquatic environment. We conduct controlled experiments of underwater robots using real water surface drones. Such a practicum environment is unparalleled within and outside Japan.
Smart robotics(Robot Land, Smart Manufacturing) R&E field
Smart robotics (Robot Land)
This research and education field is related to ground robots. We offer a smart robotics education research environment utilizing 5G, IoT, and AI. We promote practical education research to tackle social issues such as disaster response, infrastructure maintenance, and an aging society. The University created a quadruped hydraulic-driven robot for an outdoor environment, which can perform tasks in dusty or rainy conditions.
Smart robotics (Smart Manufacturing)
This field offers an experiential learning environment through practicums by seamlessly connecting digital manufacturing flow from parts design to processing. We offer cutting-edge education and research in smart manufacturing by combining cameras to obtain 3D data of the shape, location, and position of a manufactured article or tool.
Smart robotics R&E field
Smart mobility R&E field
This research platform is related to automated driving and mobility services utilizing it. We create new mobility services using electric vehicles controlled by open-source software and cutting-edge wireless systems (5G, millimeter-wave band wireless LAN) to process the sensor information delivered through cameras and LiDAR (a type of laser sensor).
Artificial Intelligence R&E field
Tokyo Tech started “Data Science & Artificial Intelligence Research Group for Social Good” (DSAI), and began preparing for artificial intelligence education for graduate students. As part of this initiative, we retrofitted four lecture rooms with Wi-Fi 6 wireless LAN, which allow students to access the high-speed network for machine learning services in the cloud from their own PCs and tablets.
Smart workplace R&E field
We are determining what is the best way to work in offices and at home, and how to manage health. We have built a wireless sensor network for indoor environments and for the vital signs of workers at the Otemachi office. Here, by smart air-conditioning using AI based on the sensing results, the goal is to create a more human-centered, comfortable, and highly productive environment. We hope to propose infection control measures for the post COVID-19 era by visualizing the behavior of droplet nuclei using signage and MR (Mixed Reality).