Humanoid robot magic show performance

Yang, Jeehyun; Jeong, Jaesik; Jamzuri, Eko Rudiawan; Baltes, Jacky

doi:10.1007/s11042-023-14690-w

Cited by 3 publications

(2 citation statements)

References 28 publications

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“… Jeong et al (2022) use a robot magic show to test a new method for analyzing interactions in performance art with a view towards clarify the artist’s intent. Yang et al (2023) describe a humanoid robot performing pen tricks while trying on different personalities. Both studies focus on humanoid robots, and not robots and chatbots in general.…”

Section: Related Researchmentioning

confidence: 99%

Would you be impressed: applying principles of magic to chatbot conversations

Siskind,

Nichols,

Gomez

2024

Front. Robot. AI

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A magician’s trick and a chatbot conversation have something in common: most of their audiences do not know how they work. Both are also constrained by their own limitations: magicians by the constraints of biology and physics, and dialogue systems by the status of current technology. Magicians and chatbot creators also share a goal: they want to engage their audience. But magicians, unlike the designers of dialogue systems, have centuries of practice in gracefully skirting limitations in order to engage their audience and enhance a sense of awe. In this paper, we look at these practices and identify several key principles of magic and psychology to apply to conversations between chatbots and humans. We formulate a model of communication centered on controlling the user’s attention, expectations, decisions, and memory based on examples from the history of magic. We apply these magic principles to real-world conversations between humans and a social robot and evaluate their effectiveness in a Magical conversation setting compared to a Control conversation that does not incorporate magic principles. We find that human evaluators preferred interactions that incorporated magical principles over interactions that did not. In particular, magical interactions increased 1) the personalization of experience, 2) user engagement, and 3) character likability. Firstly, the magical experience was “personalized.” According to survey results, the magical conversation demonstrated a statistically significant increase in “emotional connection” and “robot familiarity.” Therefore, the personalization of the experience leads to higher levels of perceived impressiveness and emotional connection. Secondly, in the Magical conversation, we find that the human interlocutor is perceived to have statistically-significantly higher engagement levels in four of seven characteristics. Thirdly, participants judged the robot in the magical conversation to have a significantly greater degree of “energeticness,”“humorousness,” and “interestingness.” Finally, evaluation of the conversations with questions intended to measure contribution of the magical principals showed statistically-significant differences for five out of nine principles, indicating a positive contribution of the magical principles to the perceived conversation experience. Overall, our evaluation demonstrates that the psychological principles underlying a magician’s showmanship can be applied to the design of conversational systems to achieve more personalized, engaging, and fun interactions.

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Section: Related Researchmentioning

confidence: 99%

Would you be impressed: applying principles of magic to chatbot conversations

Siskind,

Nichols,

Gomez

2024

Front. Robot. AI

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“…Humanoid robots, i.e., robots resembling human beings, have developed rapidly in recent years. Many researchers have developed these kinds of robots for various purposes, such as learning assistance for primary education [1], clinical applications [2], [3], playing games [4], [5], assisting the elderly [6], and even playing soccer. Humanoid robots have been developed to play football in the same way as human beings, such as passing the ball to a nearby player, kicking the ball towards the goal, and recognizing other team members on the field in real time.…”

Section: Introductionmentioning

confidence: 99%

Tiny-YOLO distance measurement and object detection coordination system for the BarelangFC robot

Susanto,

Ricardo Silitonga,

Analia

et al. 2023

IJECE

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<span lang="EN-US">A humanoid robot called BarelangFC was designed to take part in the Kontes Robot Indonesia (KRI) competition, in the robot coordination division. In this division, each robot is expected to recognize its opponents and to pass the ball towards a team member to establish coordination between the robots. In order to achieve this team coordination, a fast and accurate system is needed to detect and estimate the other robot’s position in real time. Moreover, each robot has to estimate its team members’ locations based on its camera reading, so that the ball can be passed without error. This research proposes a Tiny-YOLO deep learning method to detect the location of a team member robot and presents a real-time coordination system using a ZED camera. To establish the coordinate system, the distance between the robots was estimated using a trigonometric equation to ensure that the robot was able to pass the ball towards another robot. To verify our method, real-time experiments was carried out using an NVDIA Jetson NX Xavier, and the results showed that the robot could estimate the distance correctly before passing the ball toward another robot.</span>

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