Intelligent Scanning Collision Avoidance Device with Risk Assessment

This paper presents an Intelligent Scanning Collision Avoidance Device (Intelligent-SCAD) which is used to detect obstacles in a powered wheelchair surroundings to avoid related risk consequences. The Intelligent-SCAD provides a safe direction for the wheelchair. Inputs to the Intelligent-SCAD originate from a single rotating ultrasonic transducer fixed to the wheelchair. Readings from the ultrasonic transducer are used to train and test different Artificial Intelligence (AI) algorithms. The AI algorithms used were: Artificial Neural Network, Decision Tree, optimised Tree and optimised K-Nearest Neighbour. An algorithm is selected based on a compromise between accuracy and complexity. The optimised K-Nearest Neighbour algorithm provided the highest testing accuracy and relatively straightforward operation when compared with the other algorithms used. The new device applies optimised K-Nearest Neighbour to predict a safe direction for a wheelchair. The user can override the new system if necessary.