DEVELOPMENT OF CONTROL SOFTWARE FOR STAIR DETECTION IN A MOBILE ROBOT USING ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING

In this paper our main aim is to design and develop the control software for the detection and alignment of stairs by a stair climbing and manually operated robot. The robot platform is a differential drive, with skid steering system. The system is mounted on a rugged chassis. Vision sensors are mounted on the robot. These are cameras which will provide motion images of the robot’s surroundings. The application software will apply image processing and artificial intelligence techniques to detect stairs at Real-time and align the robot at an appropriate distance from the stair. Use of canny edge detection method to detect the edges of the stairs, smoothen the image and removing noise from the image. Neural networking will be used to detect stairs and faults. Machine learning technology to overcome faults in stairs and act accordingly from the saved experiences. This will be Linux based application which will have support of OpenCV API.