The problem of developing local reactive obstacle-avoidance behaviors by a mobile robot through online real-time learning is considered. The robot operated in an unknown bounded 2-D environment populated by static or moving obstacles (with slow speeds) of arbitrary shape. The sensory perception was based on a laser range finder. A learning-based approach to the problem is presented. To greatly reduce the number of training samples needed, an attentional mechanism was used. An efficient, real-time implementation of the approach was tested, demonstrating smooth obstacle-avoidance behaviors in a corridor with a crowd of moving students as well as static obstacles. Key words: Humanoid, Reactive Collision Avoidance, Range Finder, Perception Please send correspondence to Dr. Juyang Weng at the Department of Computer Science and Engineering, 3115 Engineering Building, East Lansing, MI 48824-1126, USA