Humanoid robots (humanoids) are highly capable of assisting humans and working with them in cluttered and confined environments. However, they are not completely ready to work in close proximity with humans while not risking the safety of themselves and the objects and people around them. Current methods have not been fully successful in preparing humanoid for safe Human Robot Interaction (HRI) because they rely on expensive and fragile equipment, and erroneous techniques.

This thesis presents a novel real-time methodology that enables the safe close proximity HRI for all types of humanoids (controlling systems, etc.). The proposed approach employs signals from robots’ motor joints and data from the computers running the robot to develop a collision detection algorithm. Using this algorithm, humanoids will be able to speedily identify impacted joints during a collision. Experimental results for the humanoid robot Taiko are presented to demonstrate the applicability of the proposed approach.