This paper presents a new method to allow robots to accompany a person or a group of people imitating pedestrians behavior. Two-people groups usually walk in a side-by-side formation and three-people groups walk in a V- formation so that they can see each other. For this reason, the proposed method combines a Side-by-side and V-formation pedestrian model with the Anticipative Kinodynamic Planner (AKP). Combining these methods, the robot is able to do an anticipatory accompaniment of groups of humans, as well as to avoid static and dynamic obstacles in advance, while keeping the prescribed formations. The proposed framework allows also a dynamical re-positioning of the robot, if the physical position of the partners change in the group formation. Furthermore, people have a randomness factor that the robot has to manage, for that reason, the system was adapted to deal with changes in people’s velocity, orientation and occlusions. Finally, the method has been validated using synthetic experiments and real-life experiments with our Tibi robot. In addition, a user study has been realized to reveal the social acceptability of the method.
Repiso E, Zanlungo F, Kanda T, Garrell A, Sanfeliu A (2019). People's V-Formation and Side-by-Side Model Adapted to Accompany Groups of People by Social Robots. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) [10.1109/IROS40897.2019.8968601].
People's V-Formation and Side-by-Side Model Adapted to Accompany Groups of People by Social Robots
Zanlungo F;
2019-11-01
Abstract
This paper presents a new method to allow robots to accompany a person or a group of people imitating pedestrians behavior. Two-people groups usually walk in a side-by-side formation and three-people groups walk in a V- formation so that they can see each other. For this reason, the proposed method combines a Side-by-side and V-formation pedestrian model with the Anticipative Kinodynamic Planner (AKP). Combining these methods, the robot is able to do an anticipatory accompaniment of groups of humans, as well as to avoid static and dynamic obstacles in advance, while keeping the prescribed formations. The proposed framework allows also a dynamical re-positioning of the robot, if the physical position of the partners change in the group formation. Furthermore, people have a randomness factor that the robot has to manage, for that reason, the system was adapted to deal with changes in people’s velocity, orientation and occlusions. Finally, the method has been validated using synthetic experiments and real-life experiments with our Tibi robot. In addition, a user study has been realized to reveal the social acceptability of the method.File | Dimensione | Formato | |
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