Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Supervised semantic labeling of places using information extracted from sensor data
Robotics and Autonomous Systems
Planning-based prediction for pedestrians
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Robots asking for directions: the willingness of passers-by to support robots
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Following directions using statistical machine translation
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Toward understanding natural language directions
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Pointing to space: modeling of deictic interaction referring to regions
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Detecting region transitions for human-augmented mapping
IEEE Transactions on Robotics
Do elderly people prefer a conversational humanoid as a shopping assistant partner in supermarkets?
Proceedings of the 6th international conference on Human-robot interaction
Do you remember that shop?: computational model of spatial memory for shopping companion robots
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
Abstracting People's Trajectories for Social Robots to Proactively Approach Customers
IEEE Transactions on Robotics
May i talk about other shops here?: modeling territory and invasion in front of shops
Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
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This study addresses the robot that waits for users while they shop. In order to wait, the robot needs to understand which locations are appropriate for waiting. We investigated how people choose locations for waiting, and revealed that they are concerned with "disturbing pedestrians" and "disturbing shop activities". Using these criteria, we developed a classifier of waiting locations. "Disturbing pedestrians" are estimated from statistics of pedestrian trajectories, which is observed with a human-tracking system based on laser range finders. "Disturbing shop activities" are estimated based on shop visibility. We evaluated this autonomous waiting behavior in a shopping-assist scenario. The experimental results revealed that users found the autonomous waiting robot chose appropriate waiting locations for waiting more than a robot with random choice or one controlled manually by the user him or herself.