Natural person-following behavior for social robots
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Design patterns for sociality in human-robot interaction
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
How to approach humans?: strategies for social robots to initiate interaction
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
Influences on proxemic behaviors in human-robot interaction
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Attractor dynamics approach to formation control: theory and application
Autonomous Robots
Modeling environments from a route perspective
Proceedings of the 6th international conference on Human-robot interaction
Do elderly people prefer a conversational humanoid as a shopping assistant partner in supermarkets?
Proceedings of the 6th international conference on Human-robot interaction
Robotic wheelchair moving with caregiver collaboratively depending on circumstances
CHI '11 Extended Abstracts on Human Factors in Computing Systems
How do people walk side-by-side?: using a computational model of human behavior for a social robot
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
A Human Aware Mobile Robot Motion Planner
IEEE Transactions on Robotics
The influence of height in robot-mediated communication
Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction
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Walking side by side is a common situation when we go from one place to another with another person while talking. Our previous study reported a basic mechanism for side-by-side walking, but in the previous model it was crucial that each agent knew where he or she was going, i.e. the route to the destination. However, we have recognized the need to model the situation where one of the agents does not know the destination. The extended model presented in this work has two states: leader-follower state and collaborative state. Depending on whether the follower agent has obtained a reliable estimate of the route to follow, the walking agents transition between the two states. The model is calibrated with trajectories acquired from pairs of people walking side by side, and then it is tested in a human-robot interaction scenario. The results demonstrate that the new extended model achieves better side-by-side performance than a standard method without knowledge of the subgoal.