Abstract-Respecting people's social spaces is an important prerequisite for acceptable and natural robot navigation in human environments. In this paper, we describe an adaptive system for mobile robot navigation based on estimates of whether a person seeks to interact with the robot or not. The estimates are based on run-time motion pattern analysis compared to stored experience in a database. Using a potential field centered around the person, the robot positions itself at the most appropriate place relative to the person and the interaction status. The system is validated through qualitative tests in a real world setting. The results demonstrate that the system is able to learn to navigate based on past interaction experiences, and to adapt to different behaviors over time.
Tranberg Hansen et al. REF used a learn-based method to estimate if a person wants to interact with the robot.
Adaptive human aware navigation based on motion pattern analysis
RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication
RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication
Computer Science