Adaptive Human-Aware Robot Navigation in Close Proximity to Humans

For robots to be able coexist with people in future everyday human environments, they must be able to act in a safe, natural and comfortable way. This work addresses the motion of a mobile robot in an environment, where humans potentially want to interact with it. The designed system consists of three main components: a Kalman filter‐ based algorithm that derives a personʹs state information (position, velocity and orientation) relative to the robot; another algorithm that uses a Case‐Based Reasoning approach to estimate if a person wants to interact with the robot; and, finally, a navigation system that uses a potential field to derive motion that respects the personʹs social zones and perceived interest in interaction