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Planning Socially Expressive Mobile Robot Trajectories.

Philip Scales1,2, Olivier Aycard1, Véronique Aubergé2

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Summary

Robots navigating around people can be perceived socially. This study links robot motion features to human social perceptions and develops a planning method to control these perceptions for better robot acceptance.

Keywords:
human–robot interactionlogistic regressionperception experimenttrajectory planning

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Area of Science:

  • Robotics
  • Human-Robot Interaction
  • Artificial Intelligence

Background:

  • Mobile robots navigating human environments require understanding human social perceptions of robot motion.
  • Existing social navigation algorithms lack configurability to control specific social interpretations.
  • Human perception of robot motion is linked to social attitudes and intentions.

Purpose of the Study:

  • To identify key robot motion features influencing human social perception.
  • To develop a trajectory planning method for controlling social perceptions in robot navigation.
  • To enhance robot acceptability by tailoring motion to context and role.

Main Methods:

  • Developed logistic regression models based on human perception experiments and robot velocity profiles.
  • Formulated a constrained optimization problem for trajectory planning.
  • Introduced novel constraints to shape robot trajectories for desired social perceptions.

Main Results:

  • Established that specific trajectory features significantly impact human social perception of robots.
  • Demonstrated the algorithm's ability to accurately modify trajectory features based on selected constraints.
  • Showcased consistent application of subtle motion variations to induce specific social perceptions.

Conclusions:

  • Robot motion significantly influences human social perception, affecting acceptability.
  • The proposed trajectory planning method allows for controlled generation of social perceptions.
  • This approach offers a tool to enhance robot integration into human environments by tailoring motion.