Design and integration of a spatio-temporal memory with emotional influences to categorize and recall the experiences of an autonomous mobile robot

Leconte, Francis; Ferland, François; Michaud, François

doi:10.1007/s10514-015-9496-2

Cited by 28 publications

(14 citation statements)

References 25 publications

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“…During the past decade there have been several approaches that implemented episodic and semantic long-term memory in artificial systems (e.g., [5,6,10,13,14,15,16,18,22]). We believe that these works addressed only partially some of the main challenges that poses the implementation of long-term memory for social robots, and that still some of the questions described in the next paragraphs need to be answered.…”

Section: Open Questions For Implementing Long-term Memory For Social mentioning

confidence: 99%

Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home League

Pavez

Ruiz‐del‐Solar

Amo

et al. 2019

RoboCup 2018: Robot World Cup XXII

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Long-term memory is essential to feel like a continuous being, and to be able to interact/communicate coherently. Social robots need long-term memories in order to establish long-term relationships with humans and other robots, and do not act just for the moment. In this paper this challenge is highlighted, open questions are identified, the need of addressing this challenge in the RoboCup@Home League with new tests is motivated, and a new test is proposed.

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Section: Open Questions For Implementing Long-term Memory For Social mentioning

confidence: 99%

Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home League

Pavez

Ruiz‐del‐Solar

Amo

et al. 2019

RoboCup 2018: Robot World Cup XXII

View full text Add to dashboard Cite

show abstract

“…In addition, based on evidence that emotions play a role in episodic memory mechanisms [56][57][58], similar type of influences should be considered in such memory models. In this experiment, a spatio-temporal (ST) memory model consisting of a cascade of two Adaptive Resonance Theory (ART) networks [21] was developed to implement an episodic-like memory within HBBA. The first ART network is used to categorize spatial events, while the second one extracts temporal episodes from the robot's experiences.…”

Section: Fetch-and-deliver Task Using An Episodic-like Spatio-temporamentioning

confidence: 99%

“…Section 3 introduces IRL-1/TR, a robot platform used for experimenting with HBBA. Section 4 follows describing HBBA implementation for three interaction scenarios: 1) a telepresence application using a display of proximity, visual, audible and force data [20]; 2) a fetch-and-deliver task using an episodic-like spatiotemporal memory model [21]; and 3) a tour-guide task with perception filtering for selective attention [22]. Section 5 discusses design issues and expected challenges to be addressed with HBBA, followed by conclusions and suggestions for future work.…”

Section: Introductionmentioning

confidence: 99%

Coordination mechanism for integrated design of Human-Robot Interaction scenarios

Ferland

Reveleau

Leconte

et al. 2017

Paladyn, Journal of Behavioral Robotics

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Abstract:The ultimate long-term goal in Human-Robot Interaction (HRI) is to design robots that can act as a natural extension to humans. This requires the design of robot control architectures to provide structure for the integration of the necessary components into HRI. This paper describes how HBBA, a Hybrid Behavior-Based Architecture, can be used as a unifying framework for integrated design of HRI scenarios. More specifically, we focus here on HBBA's generic coordination mechanism of behavior-producing modules, which allows to address a wide range or cognitive capabilities ranging from assisted teleoperation to selective attention and episodic memory. Using IRL-1, a humanoid robot equipped with compliant actuators for motion and manipulation, proximity sensors, cameras and a microphone array, three interaction scenarios are implemented: multi-modal teleoperation with physical guidance interaction, fetching-anddelivering and tour-guiding.

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“…The OCC model of emotions lacks the specification of the agent's memory and how the agent's behaviors are modulated with the use of emotions. The memory system combined with emotions has been adopted in [10], where an Episodiclike Memory System (EM) with emotions regulating the intensities of memories on a robot is used. The EM has the advantage of learning online through experience and the capacity to predict expected events based on past experiences.…”

Section: Introductionmentioning

confidence: 99%

Learning users' and personality-gender preferences in close human-robot interaction

Cruz-Maya

Tapus

2017

2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

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Robots are expected to interact with persons in their everyday activities and should learn the preferences of their users in order to deliver a more natural interaction. Having a memory system that remembers past events and using them to generate an adapted robot's behavior is a useful feature that robots should have. Nevertheless, robots will have to face unknown situations and behave appropriately. We propose the usage of user's personality (introversion/extroversion) to create a model to predict user's preferences so as to be used when there are no past interactions for a certain robot's task. For this, we propose a framework that combines an Emotion System based on the OCC Model with an Episodic-Like Memory System. We did an experiment where a group of participants customized robot's behavior with respect to their preferences (personal distance, gesture amplitude, gesture speed). We tested the obtained model against preset behaviors based on the literature about extroversion preferences on interaction. For this, a different group of participants was recruited. Results shows that our proposed model generated a behavior that was more preferred by the participants than the preset behaviors. Only the group of introvert-female participants did not present any significant difference between the different behaviors.

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Design and integration of a spatio-temporal memory with emotional influences to categorize and recall the experiences of an autonomous mobile robot

Cited by 28 publications

References 25 publications

Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home League

Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home League

Coordination mechanism for integrated design of Human-Robot Interaction scenarios

Learning users' and personality-gender preferences in close human-robot interaction

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