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Updated: Oct 6, 2025

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
Published on: August 26, 2018
Impact of decision-making system in social navigation
Jonatan Ginés Clavero1, Francisco Martín Rico2, Francisco J Rodríguez-Lera3
1Escuela Internacional de Doctorado, Rey Juan Carlos University, Móstoles, Spain.
This study integrates a human representation framework into a cognitive architecture for robots. This enables robots to dynamically adapt behavior based on human interaction, culture, and social context for improved human-robot interaction.
Area of Science:
- Robotics
- Artificial Intelligence
- Human-Robot Interaction
Background:
- Integrating cognitive architectures for human activity-aware navigation presents challenges in component orchestration.
- Existing navigation systems often treat humans merely as obstacles, neglecting nuanced social dynamics.
Purpose of the Study:
- To enhance human-robot interaction (HRI) by developing a dynamic human representation framework within a cognitive architecture.
- To enable robots to modify behaviors based on human interaction, culture, and social context.
Main Methods:
- Integration of a novel human representation framework into a cognitive architecture.
- Utilizing proxemic zones information distributed via a cost map for navigation.
- Evaluation of the decision-making system's influence on human-aware navigation and the role of local planners.
Main Results:
- Demonstrated that human representation and proxemic zones significantly influence navigation decisions.
- Showcased how a local planner is decisive in achieving human-aware navigation.
- Validated the framework's ability to allow human-influenced behavioral modification.
Conclusions:
- The developed framework successfully integrates human social context into robot navigation.
- Dynamic human representation is crucial for sophisticated human-aware navigation and enhanced HRI.
- The research provides a foundation for more socially intelligent and adaptable robot systems.
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