A Human-Like Robot Intelligent Navigation in Narrow Indoor Environments
Keywords:
Wheel-chair robot, navigation, indoor environment, neural networks, laser range finder, camerAbstract
Fast and automatic detection of the free pathway in
a narrow indoor environment is an important task in assistive and autonomous wheelchair robot navigation. Many studies have shown different methods to control the wheelchairs, from joystick to human brain signals. These techniques require a lot of physical or mental work to be done by the disabled people. This paper presents a human-like intelligent robot navigation
technique based on neural networks. In the proposed method, the robot has to rely on the Laser Range Finder (LRF) data and camera data to navigate in the narrow environment and to avoid the obstacles. At first, the wheelchair robot is controlled by using a joystick, where the camera and LRF data are collected. The gathered data are used to train the neural controller. The
proposed intelligent navigation method is evaluated in real indoor environments with different settings. Experimental results are presented which demonstrate an efficiency and robustness performance of neural network, resulting in a human-like robot navigation.
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