Real-time path planning module for autonomous vehicles in cluttered environment using a 3D camera

This paper is concerned with the real-time path planning of AGVs in a cluttered environment. In order to perform real-time operations with limited processing resources, an efficient path-planning algorithm and identification of the obstacles by a single sensor are presented. For an AGV, path planning in a cluttered environment is a challenging task owing to its lack of information about the surroundings and its need to re-plan its path quickly whenever it senses obstacles nearby. Therefore, an efficient path-planning algorithm that offers an AGV sufficient time to re-plan its path to avoid moving obstacles is proposed and, to measure its computational efficacy, its time complexity is considered. In real-time experimentation of autonomous path-planning, AGV relies completely on perception system to sense the immediate environment and avoid obstacles when it traverses towards the goal. As the Time-of-Flight (ToF)-based PMD (Photonic Mixer Device) three dimensional (3D) sensor can provide range and intensity data at low computational cost, it is utilised as a single proprioceptive sensor to detect static and dynamic obstacles.