Waseda University · Neuroscience
Professor Masaki Kuribayashi's research lab specializes in developing assistive technologies for blind individuals, focusing on indoor navigation, social interaction support, and environmental exploration using robotics and smartphone-based systems. The lab pioneers map-less navigation solutions, such as PathFinder and Corridor-Walker, which leverage LiDAR, RGB-D sensors, and real-time environmental sensing to guide users through unfamiliar buildings. Another key direction is social navigation, exemplified by LineChaser, which helps blind users navigate standing lines in public spaces. The lab also explores human-centered AI for visual language navigation, creating benchmarks like Memory-Ma to improve robot understanding of natural, memory-based route instructions.
Figures are computed from collected data and may differ slightly.
Standing in line is one of the most common social behaviors in public spaces but can be challenging for blind people. We propose an assistive system named LineChaser, which navigates a blind user to the end of a line and continuously reports the distance and direction to the last person in the line so that they can be followed. LineChaser uses the RGB camera in a smartphone to detect nearby pedestrians, and the built-in infrared depth sensor to estimate their position. Via pedestrian position es
Indoor navigation systems with prebuilt maps have shown great potential in navigating blind people even in unfamiliar buildings. However, blind people cannot always benefit from them in every building, as prebuilt maps are expensive to build. This paper explores a map-less navigation system for blind people to reach destinations in unfamiliar buildings, which is implemented on a robot. We first conducted a participatory design with five blind people, which revealed that intersections and signs a
Navigating in an indoor corridor can be challenging for blind people as they have to be aware of obstacles while also having to recognize the intersections that lead to the destination. To aid blind people in such tasks, we propose Corridor-Walker, a smartphone-based system that assists blind people to avoid obstacles and recognize intersections. The system uses a LiDAR sensor equipped with a smartphone to construct a 2D occupancy grid map of the surrounding environment. Then, the system generat
assists users in recreational exploration by explaining the surrounding environment through images obtained from the robot's camera.Users can adjust the level of detail and ask questions about their surroundings.Additionally, the system can guide users to locations they have visited before.
Visual Language Navigation (VLN) powered robots have the potential to guide blind people by understanding route instructions provided by sighted passersby. This capability allows robots to operate in environments often unknown a prior. Existing VLN models are insufficient for the scenario of navigation guidance for blind people, as they need to understand routes described from human memory, which frequently contains stutters, errors, and omissions of details, as opposed to those obtained by thin
Visual Language Navigation (VLN) powered robots have the potential to guide blind people by understanding route instructions provided by sighted passersby. This capability allows robots to operate in environments often unknown a prior. Existing VLN models are insufficient for the scenario of navigation guidance for blind people, as they need to understand routes described from human memory, which frequently contains stutters, errors, and omissions of details, as opposed to those obtained by thin
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