Adaptive Human-Aware Robot Navigation in Close Proximity to Humans

Mikael Svenstrup, Søren Tranberg Hansen, Hans Jørgen Andersen, Thomas Bak

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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Resumé

For robots to be able coexist with people in future everyday human environments, they must be able to act in a safe, natural and comfortable way. This work addresses the motion of a mobile robot in an environment, where humans potentially want to interact with it. The designed system consists of three main components: a Kalman filter‐ based algorithm that derives a personʹs state information (position, velocity and orientation) relative to the robot; another algorithm that uses a Case‐Based Reasoning approach to estimate if a person wants to interact with the robot; and, finally, a navigation system that uses a potential field to derive motion that respects the personʹs social zones and perceived interest in interaction.
OriginalsprogEngelsk
TidsskriftInternational Journal of Advanced Robotic Systems
Vol/bind8
Udgave nummer2
Sider (fra-til)1-15
Antal sider15
ISSN1729-8806
StatusUdgivet - jun. 2011

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Navigation
Robots
Navigation systems
Kalman filters
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Adaptive Human-Aware Robot Navigation in Close Proximity to Humans. / Svenstrup, Mikael; Hansen, Søren Tranberg; Andersen, Hans Jørgen; Bak, Thomas.

I: International Journal of Advanced Robotic Systems, Bind 8, Nr. 2, 06.2011, s. 1-15.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Adaptive Human-Aware Robot Navigation in Close Proximity to Humans

AU - Svenstrup, Mikael

AU - Hansen, Søren Tranberg

AU - Andersen, Hans Jørgen

AU - Bak, Thomas

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AB - For robots to be able coexist with people in future everyday human environments, they must be able to act in a safe, natural and comfortable way. This work addresses the motion of a mobile robot in an environment, where humans potentially want to interact with it. The designed system consists of three main components: a Kalman filter‐ based algorithm that derives a personʹs state information (position, velocity and orientation) relative to the robot; another algorithm that uses a Case‐Based Reasoning approach to estimate if a person wants to interact with the robot; and, finally, a navigation system that uses a potential field to derive motion that respects the personʹs social zones and perceived interest in interaction.The operation of the system is evaluated in a controlled scenario in an open hall environment. It is demonstrated that the robot is able to learn to estimate if a person wishes to interact, and that the system is capable of adapting to changing behaviours of the humans in the environment.

KW - Human‐Robot Interaction

KW - Robot Motion

KW - Intention Estimation

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JO - International Journal of Advanced Robotic Systems

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