Yuan Chen, Meng YuanWu, Yong JianHe, Hongmei2019-01-092019-01-092018-12-31Chen M.Y., Wu Y.J., He H. (2019) A Comprehensive Obstacle Avoidance System of Mobile Robots Using an Adaptive Threshold Clustering and the Morphin Algorithm. In: Advances in Computational Intelligence Systems. UKCI 2018. Advances in Intelligent Systems and Computing, Vol. 840978-3-319-97981-6https://doi.org/10.1007/978-3-319-97982-3_26https://dspace.lib.cranfield.ac.uk/handle/1826/13801To solve the problem of obstacle avoidance for a mobile robot in unknown environment, a comprehensive obstacle avoidance system (called ATCM system) is developed. It integrates obstacle detection, obstacle classification, collision prediction and obstacle avoidance. Especially, an Adaptive-Threshold Clustering algorithm is developed to detect obstacles, and the Morphin algorithm is applied for path planning when the robot predicts a collision ahead. A dynamic circular window is set to continuously scan the surrounding environment of the robot during the task period. The simulation results show that the obstacle avoidance system enables robot to avoid any static and dynamic obstacles effectively.enAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/Adaptive threshold clusteringMorphin algorithmObstacle detectionObstacle classificationCollision predictionCollision avoidanceConference paper