Human-robot Interactive Collision Prevention: improved navigation in home environments
It is generally envisaged that in the near future, personal assistance robots will aid people in and around their homes. One of the requirements of these robots it that they can are able to navigate autonomously such that it is safe and comfortable for their users and at the same time effi cient for the robot. Path planning and obstacle avoidance are crucial in these contexts. Current obstacle avoidance algorithms are not effi cient when people cross the path of the robot. In this thesis four types of obstacle avoidance are compared by efficiency and user preference: static obstacle avoidance, two types of dynamic obstacle avoidance and interactive collision prevention(ICP). The efficiency is measured in terms of navigation time, amount of detour and the number of successful trials (without collisions). The results suggest that both dynamic obstacle avoidance algorithms are more efficient than static obstacle avoidance. Furthermore, first explorations in ICP indicate that users can safely and comfortably guide the robot and that ICP is preferred over the other algorithms.
Faculteit der Sociale Wetenschappen