Paper
16 October 2000 Robotic comfort zones
Maxim Likhachev, Ronald C. Arkin
Author Affiliations +
Proceedings Volume 4196, Sensor Fusion and Decentralized Control in Robotic Systems III; (2000) https://doi.org/10.1117/12.403722
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States
Abstract
The paper investigates how the psychological notion of comfort can be useful in the design of robotic systems. A review of the existing study of human comfort, especially regarding its presence in infants, is conducted with the goal being to determine the relevant characteristics for mapping it onto the robotics domain. Focus is place on the identification of the salient features in the environment that affect the comfort level. Factors involved include current state familiarity, working conditions, the amount and location of available resources, etc. As part of our newly developed comfort function theory, the notion of an object as a psychological attachment for a robot is also introduced, as espoused in Bowlby's theory of attachment. The output space of the comfort function and its dependency on the comfort level are analyzed. The results of the derivation of this comfort function are then presented in terms of the impact they have on robotic behavior. Justification for the use of the comfort function are then presented in terms of the impact they have on robotic behavior. Justification for the use of the comfort function in the domain of robotics is presented with relevance for real-world operations. Also, a transformation of the theoretical discussion into a mathematical framework suitable for implementation within a behavior-based control system is presented. The paper concludes with results of simulation studies and real robot experiments using the derived comfort function.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maxim Likhachev and Ronald C. Arkin "Robotic comfort zones", Proc. SPIE 4196, Sensor Fusion and Decentralized Control in Robotic Systems III, (16 October 2000); https://doi.org/10.1117/12.403722
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Cited by 26 scholarly publications.
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KEYWORDS
Robotics

Robotic systems

Safety

Psychology

Mathematical modeling

Body temperature

Control systems

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