The project concentrates on obstacle detection for visually impaired people using IR, Ultrasonic sensors and TSOP receiver which is of less cost, fast and efficient. Shortest distance algorithm is the method used to find the obstacles at each region sent from the TSOP receiver mounted on each angles. This works in environments such as indoor and outdoor. Experience comes from learning and the important requirements for learning will be the sense of vision of what normal human being sees and observes in the real world. But in the case of VI people, sense of vision will not help them in learning where other senses like ears, touch, smell helps them in various situations. The whole setup is wearable and lightweight mounted on a belt to make the VI people to walk into any situation like pits, steps by providing haptic feedback as the output. The project uses Arduino mega which helps us to program ease and also helps in testing various parameters with the available open source library routines. Since the targeted user is VI people, navigational guidance can be done through Augmented Reality domain as the technology is growing wide and can give more reliable to the user. © 2018, Springer International Publishing AG.
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S. Ramachandran, Prashant R. Nair, and Vasudevan, S. K., “Cane free obstacle detection using sensors and navigational guidance using augmented reality for visually challenged people”, Lecture Notes in Computational Vision and Biomechanics, vol. 28. Springer Netherlands, pp. 324-334, 2018.