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Intention and Body-Mood Engineering via Proactive Robot Moves in HRI

Intention and Body-Mood Engineering via Proactive Robot Moves in HRI

O. Can Görür, Aydan M. Erkmen
Copyright: © 2019 |Pages: 29
ISBN13: 9781522580607|ISBN10: 1522580603|EISBN13: 9781522580614
DOI: 10.4018/978-1-5225-8060-7.ch012
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MLA

Görür, O. Can, and Aydan M. Erkmen. "Intention and Body-Mood Engineering via Proactive Robot Moves in HRI." Rapid Automation: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 247-275. https://doi.org/10.4018/978-1-5225-8060-7.ch012

APA

Görür, O. C. & Erkmen, A. M. (2019). Intention and Body-Mood Engineering via Proactive Robot Moves in HRI. In I. Management Association (Ed.), Rapid Automation: Concepts, Methodologies, Tools, and Applications (pp. 247-275). IGI Global. https://doi.org/10.4018/978-1-5225-8060-7.ch012

Chicago

Görür, O. Can, and Aydan M. Erkmen. "Intention and Body-Mood Engineering via Proactive Robot Moves in HRI." In Rapid Automation: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 247-275. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8060-7.ch012

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Abstract

This chapter focuses on emotion and intention engineering by socially interacting robots that induce desired emotions/intentions in humans. The authors provide all phases that pave this road, supported by overviews of leading works in the literature. The chapter is partitioned into intention estimation, human body-mood detection through external-focused attention, path planning through mood induction and reshaping intention. Moreover, the authors present their novel concept, with implementation, of reshaping current human intention into a desired one, using contextual motions of mobile robots. Current human intention has to be deviated towards the new desired one by destabilizing the obstinance of human intention, inducing positive mood and making the “robot gain curiosity of human”. Deviations are generated as sequences of transient intentions tracing intention trajectories. The authors use elastic networks to generate, in two modes of body mood: “confident” and “suspicious”, transient intentions directed towards the desired one, choosing among intentional robot moves previously learned by HMM.

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