Abstract
Facing human activity-aware navigation with a cognitive architecture raises several difficulties integrating the components and orchestrating behaviors and skills to perform social tasks. In a real-world scenario, the navigation system should not only consider individuals like obstacles. It is necessary to offer particular and dynamic people representation to enhance the HRI experience. The robot’s behaviors must be modified by humans, directly or indirectly. In this paper, we integrate our human representation framework in a cognitive architecture to allow that people who interact with the robot could modify its behavior, not only with the interaction but also with their culture or the social context. The human representation framework represents and distributes the proxemic zones’ information in a standard way, through a cost map. We have evaluated the influence of the decision-making system in human-aware navigation and how a local planner may be decisive in this navigation. The material developed during this research can be found in a public repository (https://github.com/IntelligentRoboticsLabs/social_navigation2_WAF) and instructions to facilitate the reproducibility of the results.
Highlights
In recent years, robots have come out from factories and research laboratories and are beginning to populate human-populated domestic and work environments
Using Planning Definition Domain Language (PDDL) in one loop and Behavior Trees in the other, in combination with DWB and Timed Elastic Band (TEB), PDDL + TEB shows a navigation time lower than the time used by the Behavior Trees option, Table 1
This paper has presented the continuation of our research in social navigation, applying the concept of proxemic
Summary
Robots have come out from factories and research laboratories and are beginning to populate human-populated domestic and work environments. Multimedia Tools and Applications particular, we are interested in social navigation This term’s social component refers to the fact that this task has to consider people and the social conventions humans apply when moving between and towards other humans. This work is encompassed within a research project where the authors have been working on the following research problem: A social robot aiming to interact with humans needs to adapt its navigation behavior when deployed in a real-world environment. Some works [3, 26, 41] consider this zone as a restricted zone for robot navigation We propose that this zone be adaptive because, depending on the context, it will be a restricted or a cooperation zone where the robot enters to carry out a task with the person
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