Path planning for assisting blind people in purposeful navigation

Abstract

Blind <span>people present dificulties for reaching objects of interest in the daily life. In this sense, the integration of a path planning module for assisting blind people in purposeful navigation is noteworthy. In this work, we present an algorithm that leverages the high capability of an embedded computer with graphics processing unit (GPU) NVIDIA Jetson TX2 for computing optimal paths to objects of interest. The algorithm computes the optimal path to the objective, considering changes in the environment and changes in the position of the user. The algorithm is efficient for computing new paths when the environment changes by reusing parts of previous computations. In order to compare the performance, the algorithms were implemented and evaluated in MATLAB, C++ and CUDA, for different size of the grid and percentage of unknown obstacles. We found that the implementation on GPU has a speed up of 20 times W.R.T the implementation in C++ and more than 400 times W.R.T the implementation in MATLAB. These results boost us to integrate this module to our main system based on a stereo camera and a haptic belt and so provide to the user assistance in purposeful navigation at real time.</span>

A review on object detection for autonomous mobile robot

“…In addition, a study has been done on the non-uniform and dynamic environments, delivering an optimal path. The paper [24] proposed an algorithm that leverages the high capability of an embedded computer with a graphics processing unit (GPU) NVIDIA Jetson TX2 for computing optimal paths to objects of interest to assist blind people. The system's execution times depend highly on the environment's complexity, such as the grid size and the unknown obstacle.…”