Conference Paper

How to Approach Humans?-Strategies for Social Robots to Initiate Interaction-

DOI: 10.1145/1514095.1514117 Conference: Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction, HRI 2009, La Jolla, California, USA, March 9-13, 2009
Source: DBLP

ABSTRACT ABSTRACT This paper proposes a model,of approach,behavior with which a robot can initiate conversation with people who,are walking. We developed,the model by learning,from the failures in a simplistic approach,behavior ,used in a ,real shopping ,mall. Sometimes people were unaware of the robot’s presence, even when it spoke tothem. Sometimes, people were not sure whether the robot was really trying to start a conversation, and they did not start talking with it even ,though ,they displayed interest. To prevent ,such failures, our model includes the following functions: predicting the walking behavior of people, choosing a target person, planning its approaching path, and nonverbally indicating its intention to initiate ,a conversation. ,The approach ,model ,was implemented,and ,used in a ,real shopping ,mall. The field trial demonstrated,that our model ,significantly improves ,the robot’s performance,in initiating conversations. Categories and Subject Descriptors H.5.2 [Information Interfaces and Presentation]: User Interfaces-Interaction styles General Terms

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Available from: Dylan F. Glas, Aug 15, 2015
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    • "Sisbot and his colleagues developed a path-planning algorithm that considers people's comfort [23]. Satake and his colleagues developed an approaching behavior, in which anticipation of the target person's motion was indispensable [22] "
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    ABSTRACT: 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.
    Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction; 03/2014
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    • "For example, motion patterns learned from observations of humans can be used to make the navigation among people more effective [6], [7]. In addition, knowledge of people's behavior can support devising ways for robots to approach people [8], find appropriate places to offer services [9] or chose a place for waiting [10]. It is not clear if models of behavior based on data collected at one specific point of time apply at some different time. "
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    ABSTRACT: Knowledge about space usage from variables such as density and walking speed could support a variety of service applications. However, there is not much knowledge on how the usage of space changes during extended periods of time and what affects the changes. We have installed a person tracking system in a large area of a shopping center and collected pedestrian data over a year. In this paper, we analyze the collected data to find the changes in pedestrian density and speed, percentage of children, and pedestrian trajectories. The changes from day to day, as well as during the day are examined, and a number of factors that affect them are identified. This is in turn used in the prediction of the state of the space using a Gaussian process model.
    01/2014; 45(2):1-10. DOI:10.1109/THMS.2014.2374172
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    • "The reactions of the subjects confirm that navigation behavior conveys messages and can be used for non-verbal communication, and must be considered to avoid misunderstandings. Similar ideas were tested for robots to be deployed in shopping malls, by Hayashi [35] and Satake [81], investigating how the trajectory of the robot can adapt to that of walking humans, to catch their attention without disturbing them. Both found they could improve the acceptability by making the robot approach from the front. "
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    ABSTRACT: Navigation is a basic skill for autonomous robots. In the last years human–robot interaction has become an important research field that spans all of the robot capabilities including perception, reasoning, learning, manipulation and navigation. For navigation, the presence of humans requires novel approaches that take into account the constraints of human comfort as well as social rules. Besides these constraints, putting robots among humans opens new interaction possibilities for robots, also for navigation tasks, such as robot guides. This paper provides a survey of existing approaches to human-aware navigation and offers a general classification scheme for the presented methods.
    Robotics and Autonomous Systems 12/2013; 61(12):1726–1743. DOI:10.1016/j.robot.2013.05.007 · 1.11 Impact Factor
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