Evolving synthetic pain into an adaptive self-awareness framework for robots

Anshar, Muh; Williams, Mary-Anne

doi:10.1016/j.bica.2015.10.002

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…Assuming the non-human participation in self-related interactions, the topics of social bots, human-bot communication, AI bots, chatbots, personal assistants, or other conversational media were manually filtered out. A few records already represent this research field (Nathanson, 2017;Claffey and Brady, 2017;Anshar and Williams, 2016). Despite the widespread adoption of these technologies, only pioneers have found a connection to self-concept research so far.…”

Section: The Latest Trends Of Self-concept Research In Social Media M...mentioning

confidence: 99%

How Do Social Media Machines Affect Self-Concept Research?

Fehér¹,

Katona²

2023

KOME

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Advanced digital technologies broadly penetrate self-activities, such as algorithms, machine learning, or artificial intelligence. This trend is most evident on social media, where contents, attitudes and evaluative judgments meet on technology-driven platforms. Moreover, human networks also started communicating with social bots or conversational interfaces. All these challenges can trigger a redesign of self-concept via technology. Therefore, the paper investigates how social media machines affect self-concept-related academic research. First, pioneers of the field are presented. Second, the self-concept research in digital technology and social media is summarised. Topic networks illustrate critical research fields with the latest trends and future implications. Last but not least, we also investigate how emerging media phenomena affect academic trends in the case of social bots or fake news. The study aims to support the connected research in psychology, business, management, education, political science, medicine and media studies with an understanding of the latest trends. The additional goal is to highlight the potential of market-based research cooperation with academia supporting significant developments and funding.

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Section: The Latest Trends Of Self-concept Research In Social Media M...mentioning

confidence: 99%

How Do Social Media Machines Affect Self-Concept Research?

Fehér¹,

Katona²

2023

KOME

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“…Our artificial pain for robots contains three classifications of synthetic pain de-rived from the report [13], described as follows:…”

Section: A Artificial Painmentioning

confidence: 99%

“…Artificial pain definition is integrated into a NAO robot mechanism, which utilise our novel Adaptive Self-awareness framework for robots (ASAF) [13]. The ASAF framework consists of several elements as shown in Fig.…”

Section: B Integrationmentioning

confidence: 99%

Evolving artificial pain from fault detection through pattern data analysis

Anshar

Williams

2017

2017 IEEE International Conference on Real-Time Computing and Robotics (RCAR)

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Fault detection is a classical area of study in robotics and extensive research works have been dedicated to investigate its broad applications. As the breath of robots applications requiring human interaction grow, it is important for robots to acquire sophisticated social skills such as empathy towards pain. However, it turns out that this is difficult to achieve without having an appropriate concept of pain that relies on robots being aware of their own body machinery aspects. This paper introduces the concept of pain, based on the ability to develop a state of awareness of robots own body and the use of the fault detection approach to generate artificial robot pain. Faults provide the stimulus and defines a classified magnitude value, which constitutes artificial pain generation, comprised of synthetic pain classes. Our experiment evaluates some of synthetic pain classes and the results show that the robot gains awareness of its internal state through its ability to predict its joint motion and generate appropriate artificial pain. The robot is also capable of alerting humans whenever a task will generate artificial pain, or whenever humans fails to acknowledge the alert, the robot can take a considerable preventive actions through joint stiffness adjustment.

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Nociceptive Memristor

et al. 2018

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The biomimetic characteristics of the memristor as an electronic synapse and neuron have inspired the advent of new information technology in the neuromorphic computing. The application of the memristors can be extended to the artificial nerves on condition of the presence of electronic receptors which can transfer the external stimuli to the internal nerve system. In this work, nociceptor behaviors are demonstrated from the Pt/HfO /TiN memristor for the electronic receptors. The device shows four specific nociceptive behaviors; threshold, relaxation, allodynia, and hyperalgesia, according to the strength, duration, and repetition rate of the external stimuli. Such nociceptive behaviors are attributed to the electron trapping/detrapping to/from the traps in the HfO layer, where the depth of trap energy level is ≈0.7 eV. Also, the built-in potential by the work function mismatch between the Pt and TiN electrodes induces time-dependent relaxation of trapped electrons, providing the appropriate relaxation behavior. The relaxation time can take from several milliseconds to tens of seconds, which corresponds to the time span of the decay of biosignal. The material-wise evaluation of the electronic nociceptor in comparison with other material, which did not show the desired functionality, Pt/Ti/HfO /TiN, reveals the importance of careful material design and fabrication.

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Evolving synthetic pain into an adaptive self-awareness framework for robots

Cited by 4 publications

References 21 publications

How Do Social Media Machines Affect Self-Concept Research?

How Do Social Media Machines Affect Self-Concept Research?

Evolving artificial pain from fault detection through pattern data analysis

Nociceptive Memristor

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