Social robot navigation to improve people comfort in collaborative navigation daily tasks
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2022
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Universidad Rey Juan Carlos
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In recent years, robots have been moving from research laboratories to being part of everyday
life in our homes and society. This new reality creates everyday situations where humans
interact and collaborate with robots. For such interactions to be satisfactory for humans, they
must be natural, comfortable, and safe, mainly if we focus on human-robot interactions with
mobile robots. The above conditions require developing robotic systems adaptive to a dynamic
environment, such as an environment populated by people and to current social rules. So, the
main goal of this thesis by compendium is propose a solution, which integrated into the robot
control architecture, allows us to modify the robot behavior according the people’s behavior
with whom it shares space.
There are four fields of study that compose the fundamental part of the proposed solution:
Robot Navigation: the robot must navigate in dynamic environments reliably and safely,
Human-Robot Interaction: responsible for handling the social systems, such as dialog or
proxemics, to collect data from humans, Context Awareness, the robot has been aware of the
environment and process it to generate knowledge. Finally, Cognitive Architecture orchestrates
the behaviors following principles based on knowledge and/or human-like cognitive processes.
The main contributions of the present dissertation are the development of a dynamic solution
to represent people and their context in terms of personal space and the development of a novel
proxemic zone to improve collaboration tasks between humans and robots, the cooperation
zone. These contributions play a part in improving people’s comfort during HRI behaviors and
have enabled collaborative navigation actions, such as escorting or following a person.
Furthermore, the empirical investigations performed in competition scenarios demonstrate
the solution’s validity and show that it is ready to be deployed in real environments.
Descripción
Tesis Doctoral leída en la Universidad Rey Juan Carlos de Madrid en 2022. Directores :
Dr. Francisco Martín Rico
Dr. Francisco Javier Rodríguez Lera
Programa de Doctorado en Tecnologías de la Información y las
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