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2019
Papenmeier, Frank; Uhrig, Meike; Kirsch, Alexandra (2019): Human Understanding of Robot Motion: The Role of Velocity and Orientation. In: International Journal of Social Robotics 11 (1), S. 75-88. DOI: 10.1007/s12369-018-0493-4

DOI: https://doi.org/10.1007/s12369-018-0493-4

Abstract: A general problem in human–robot interaction is how to test the quality of single robot behavior, in order to develop robust and human-acceptable skills. The most typical approach are user tests with subjective measures (questionnaires). We propose a new experimental paradigm that combines subjective measures with an objective behavioral measure, namely viewing times of images viewed as self-paced slide show. We applied this paradigm to human-aware robot navigation. With three experiments, we studied the influence of two aspects of robot motion: velocity profiles and the robot’s orientation. A decreasing velocity profile influenced the predictability of the observed motion, and robot orientations diverting from the robot’s motion vector caused reduced perceived autonomy ratings. We conclude that the viewing time paradigm is a promising tool for studying human-aware robot behavior and that the design of human-aware robot navigation needs to consider both the velocity and the orientation of robots.

Keywords: comfort, naturaleness and sociability, human-aware, human-aware navigation, Intentionserkennung (Mensch erkennt Roboterintention), Mobile Roboter, ORIENTATION, Robotics, sociability, socially aware robot navigation, socially-aware, velocity
2016
Talebpour, Z.; Viswanathan, D.; Ventura, R.; Englebienne, G.; Martinoli, A. (2016) : Incorporating perception uncertainty in human-aware navigation: A comparative study: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): New York City, USA: IEEE, S. 570-577

DOI: https://doi.org/10.1109/ROMAN.2016.7745175

Abstract: In this work, we present a novel approach to human-aware navigation by probabilistically modelling the uncertainty of perception for a social robotic system and investigating its effect on the overall social navigation performance. The model of the social costmap around a person has been extended to consider this new uncertainty factor, which has been widely neglected despite playing an important role in situations with noisy perception. A social path planner based on the fast marching method has been augmented to account for the uncertainty in the positions of people. The effectiveness of the proposed approach has been tested in extensive experiments carried out with real robots and in simulation. Real experiments have been conducted, given noisy perception, in the presence of single/multiple, static/dynamic humans. Results show how this approach has been able to achieve trajectories that are able to keep a more appropriate social distance to the people, compared to those of the basic navigation approach, and the human-aware navigation approach which relies solely on perfect perception, when the complexity of the environment increases. Accounting for uncertainty of perception is shown to result in smoother trajectories with lower jerk that are more natural from the point of view of humans.

Keywords: Angemessen(heit) (von Technik), Computational modeling, Detectors, dynamic humans, fast marching method, human-aware navigation, human-robot interaction, ieee xplore, Mobile robots, Navigation, noisy perception, path planning, perception uncertainty, Probabilistic logic, probabilistic modelling, Probability, Proposals, Robots, social costmap, social navigation performance, social path planner, social robotic system, static humans, trajectories, trajectory control, uncertain systems, uncertainty, uncertainty factor

2019

2016

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