Enhancing the obstacle avoidance capabilities of a smart wheelchair

Abstract

Smart Wheelchairs (SWC) are vehicles designed specifically for people with certain mobility impairments to alleviate their difficulties in movement and interaction with their surroundings. In this paper, we focus on enhancing the obstacle avoidance capabilities of a SWC previously built at the University of Malta and also propose novel algorithms that can be employed on any other autonomous mobile robot. The improvements include the design, implementation and experimental validation of a novel path planner developed specifically for semi-autonomous movement. In this control mode, the only user input is the desired direction of movement. Our approach combines and improves elements of the Vector Field Histogram + (VFH+) and Dynamic Window Approach (DWA) algorithms. Simulations and physical experiments are used to validate and compare the proposed algorithm. To complement the obstacle avoidance capabilities of the local path planner, a new geometrical method is also presented for the detection of negative obstacles, such as holes and stairs.