A vision-based real-time obstacle avoidance's rules utilising grid-edge-depth map

This paper presents a new rules-based of a real-time decision system for an autonomous wheeled robot with the holonomic-drive system. The robot uses decisions to avoid collisions with obstacles. The decision rules based on grid-edge-depth map. The grid-edge-depth map represents the obstacle’s position and distance in the environment. The generation process of the grid-edge-depth map presented in previous research. The decisions of the first scenario with no destination point are forward, stop, 90o right turn, and 90o left turn. The decisions of the second and third scenarios with a destination point are forward, stop, 90o right turn, 90o left turn, 45o forward to the right, 45o forward to the left, slide to the right, and slide to the left. The proposal tested in a 5x3 meter living environment. Finally, the experiment resulted in 93.3% of navigation’s success for all the scenarios