Vision-based obstacle avoidance system with fuzzy logic for humanoid robots

Abstract

Abstract This study presents the algorithm for a humanoid robot to accomplish an obstacle run in the FIRA HuroCup competition. It includes the integration of image processing and robot motion. DARwIn-OP (Dynamic Anthropomorphic Robot with Intelligence–Open Platform) was used as the humanoid robot, and it is equipped with a webcam as a vision system to obtain an image of what is in front of the robot. Image processing skills such as erosion, dilation, and eight-connected component labeling are applied to reduce image noise. Moreover, we use navigation grids with filters to avoid the obstacles. Fuzzy logic rules are used to implement the robot’s motion, allowing a humanoid robot to access any routes using obstacle avoidance to perform the tasks in the obstacle-run event.