Road following for blindBike: an assistive bike navigation system for low vision persons

Author(s):  
Lynne Grewe ◽  
William Overell
2018 ◽  
Vol 30 (4) ◽  
pp. 552-562 ◽  
Author(s):  
Yuki Hosoda ◽  
◽  
Ryota Sawahashi ◽  
Noriaki Machinaka ◽  
Ryota Yamazaki ◽  
...  

This paper presents a novel autonomous navigation system. Our proposed system is based on a simple map (an Edge-Node Graph, which is created from an electronic map). This system consists of “Localization,” which estimates which edge is on the Edge-Node Graph, “Environmental Recognition,” which recognizes the environment around the robot, and “Path Planning,” which avoids objects. Since the robot travels using the Edge-Node Graph, there is no need to prepare an environmental map in advance. In addition, the system is quite robust, since it relies less on prior information. To show the effectiveness of our system, we conducted experiments on each elemental technology as well as some traveling tests.


2019 ◽  
Vol 9 (5) ◽  
pp. 989 ◽  
Author(s):  
Xiaochen Zhang ◽  
Xiaoyu Yao ◽  
Yi Zhu ◽  
Fei Hu

In this work, we propose an assistive navigation system for visually impaired people (ANSVIP) that takes advantage of ARCore to acquire robust computer vision-based localization. To complete the system, we propose adaptive artificial potential field (AAPF) path planning that considers both efficiency and safety. We also propose a dual-channel human–machine interaction mechanism, which delivers accurate and continuous directional micro-instruction via a haptic interface and macro-long-term planning and situational awareness via audio. Our system user-centrically incorporates haptic interfaces to provide fluent and continuous guidance superior to the conventional turn-by-turn audio-guiding method; moreover, the continuous guidance makes the path under complete control in avoiding obstacles and risky places. The system prototype is implemented with full functionality. Unit tests and simulations are conducted to evaluate the localization, path planning, and human–machine interactions, and the results show that the proposed solutions are superior to those of the present state-of-the-art solutions. Finally, integrated tests are carried out with low-vision and blind subjects to verify the proposed system.


2012 ◽  
Vol 73 (S 02) ◽  
Author(s):  
L. Volpi ◽  
A. Pistochini ◽  
M. Turri-Zanoni ◽  
F. Meloni ◽  
M. Bignami ◽  
...  

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