Human Motion Behaviour Aware Planner (HMBAP) for path planning in dynamic human environments

For a robot navigating in a human inhabited dynamic environment, the knowledge of how the robot's movement can influence the trajectory of people around it can be very valuable. In this work we present a Human Motion Behaviour Aware Planner (HMBAP) which incorporates a Human Motion Behaviour Model (HMBM) in its planning stage to take advantage of this. HMBM is an obstacle avoidance model for people based on social forces which gives the robot an understanding of how people would react to its planned path. This information is useful for the robot to avoid imminent collisions with people in constricted spaces. The resulting robot behaviour is similar to how a human would move (in terms of avoidance behaviour) in a similar situation. We believe that this is a desirable feature for a robot navigating in a human inhabited environment. Our method shows good human-like navigation behaviour in situations where past methods fail to find a solution.