Robotic Emotions: Navigation with Feeling

Robotic Emotions: Navigation with Feeling

Christopher P. Lee-Johnson (Victoria University of Wellington, New Zealand) and Dale A. Carnegie (Victoria University of Wellington, New Zealand)
DOI: 10.4018/978-1-60566-354-8.ch006
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Abstract

The hypothesis that artificial emotion-like mechanisms can improve the adaptive performance of robots and intelligent systems has gained considerable support in recent years. To test this hypothesis, a mobile robot navigation system has been developed that employs affect and emotion as adaptation mechanisms. The robot’s emotions can arise from hard-coded interpretations of local stimuli, as well as from learned associations stored in global maps. They are expressed as modulations of planning and control parameters, and also as location-specific biases to path-planning. Our focus is on affective mechanisms that have practical utility rather than aesthetic appeal, so we present an extensive quantitative analysis of the system’s performance in a range of experimental situations.
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Background

Artificial affect representations can be broadly categorized into symbolic and neurophysiological models (Aylett, 2006). Symbolic models are typically favored by large-scale general-purpose AI frameworks, and emphasize cognitive roles of affect such as goal prioritization and memory management. They are often based on cognitive appraisal theories of emotion such as that proposed by Ortony et al. (1988). These types of models often have limited applicability in the robotics domain, where symbolic objects are not simply assumed to exist; they must be derived from real-world sensor data.

Thus, robotic implementations are typically more heavily inspired by neurobiological theories of emotion such as that proposed by Damasio (1999). Affect and emotions may be employed as internal ‘sensors’, or as discrete states that drive action selection. One of the main functions of this type of affect representation is to motivate a robot to respond quickly to certain events without waiting for its slower cognitive processes to ponder the situation. Affect is thus regarded as a potential replacement for deliberative processing in robotic controllers. Interactions between affect and deliberative processing have received little attention in the robotics domain, because they are often viewed as competitors for the same role.

One robotic affect model that has inspired various implementations is Valásquez’s Cathexis architecture (Valásquez, 1997), which models Ekman’s six basic emotions (anger, fear, happiness, sadness, disgust and surprise) (Ortony and Turner, 1990) as ‘proto-specialist’ agents (Minsky, 1986) executing in parallel. Emotions are one of several inputs that control behavior activation. A similar approach is adopted by Breazeal (2003) for the robotic head Kismet. In Kismet’s model, stimuli are tagged with three dimensions of affective information (valence, arousal and stance), and their associated emotional responses compete for activation in a winner-takes-all manner. In addition to driving certain cognitive processes, emotions are portrayed as variations in the robot’s facial expression, gaze direction and tone of voice.

Key Terms in this Chapter

Survival Drive: An affective state governing parameter modulations that directly influence the likelihood or potential outcomes of existence-threatening events such as collisions.

Deliberative Navigation: Following paths that are planned utilizing global maps constructed a priori and/or updated in response to environmental dynamics.

Affective Stimulus: A function of an internal or external event that elicits an affective response.

Dynamic Window: A rectangular search space of discrete linear and angular velocities bounded by a robot’s kinematic and dynamic constraints.

Reactive Control: Real-time selection of motor outputs in response to short-term sensor data or local map data.

Mapped Emotion: A set of emotional intensities associated with specific locations in the environment due to previous stimuli.

Strategic Drive: An affective state governing parameter modulations that alter cognitive strategies without directly affecting an intelligent system’s prospects for survival.

Global Emotion: A single intensity value representing an emotion elicited by stimuli perceived at the present time.

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Table of Contents
Foreword
Craig DeLancey
Preface
Jordi Vallverdú, David Casacuberta
Chapter 1
Oscar Deniz, Javier Lorenzo, Mario Hernández, Modesto Castrillón
Social intelligence seems to obviously require emotions. People have emotions, recognize them in others and also express them. A wealth of... Sample PDF
Emotional Modeling in an Interactive Robotic Head
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Chapter 2
Cyril Laurier, Perfecto Herrera
Creating emotionally sensitive machines will significantly enhance the interaction between humans and machines. In this chapter we focus on enabling... Sample PDF
Automatic Detection of Emotion in Music: Interaction with Emotionally Sensitive Machines
$37.50
Chapter 3
Christoph Bartneck, Michael J. Lyons
The human face plays a central role in most forms of natural human interaction so we may expect that computational methods for analysis of facial... Sample PDF
Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble
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Chapter 4
Sajal Chandra Banik, Keigo Watanabe, Maki K. Habib, Kiyotaka Izumi
Multi-robot team work is necessary for complex tasks which cannot be performed by a single robot. To get the required performance and reliability... Sample PDF
Multirobot Team Work with Benevolent Characters: The Roles of Emotions
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Chapter 5
Matthias Scheutz, Paul Schermerhorn
Effective decision-making under real-world conditions can be very difficult as purely rational methods of decision-making are often not feasible or... Sample PDF
Affective Goal and Task Selection for Social Robots
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Chapter 6
Christopher P. Lee-Johnson, Dale A. Carnegie
The hypothesis that artificial emotion-like mechanisms can improve the adaptive performance of robots and intelligent systems has gained... Sample PDF
Robotic Emotions: Navigation with Feeling
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Chapter 7
C. Gros
All self-active living beings need to solve the motivational problem—the question of what to do at any moment of their life. For humans and... Sample PDF
Emotions, Diffusive Emotional Control and the Motivational Problem for Autonomous Cognitive Systems
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Chapter 8
Bruce J. MacLennan
This chapter addresses the “Hard Problem” of consciousness in the context of robot emotions. The Hard Problem, as defined by Chalmers, refers to the... Sample PDF
Robots React, but Can They Feel?
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Chapter 9
Mercedes García-Ordaz, Rocío Carrasco-Carrasco, Francisco José Martínez-López
It is contended here that the emotional elements and features of human reasoning should be taken into account when designing the personality of... Sample PDF
Personality and Emotions in Robotics from the Gender Perspective
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Chapter 10
Antoni Gomila, Alberto Amengual
In this chapter we raise some of the moral issues involved in the current development of robotic autonomous agents. Starting from the connection... Sample PDF
Moral Emotions for Autonomous Agents
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Chapter 11
Pietro Cipresso, Jean-Marie Dembele, Marco Villamira
In this work, we present an analytical model of hyper-inflated economies and develop a computational model that permits us to consider expectations... Sample PDF
An Emotional Perspective for Agent-Based Computational Economics
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Chapter 12
Michel Aubé
The Commitment Theory of Emotions is issued from a careful scrutiny of emotional behavior in humans and animals, as reported in the literature on... Sample PDF
Unfolding Commitments Management: A Systemic View of Emotions
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Chapter 13
Sigerist J. Rodríguez, Pilar Herrero, Olinto J. Rodríguez
Today, realism and coherence are highly searched qualities in agent’s behavior; but these qualities cannot be achieved completely without... Sample PDF
A Cognitive Appraisal Based Approach for Emotional Representation
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Chapter 14
Clément Raïevsky, François Michaud
Emotion plays several important roles in the cognition of human beings and other life forms, and is therefore a legitimate inspiration for providing... Sample PDF
Emotion Generation Based on a Mismatch Theory of Emotions for Situated Agents
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Chapter 15
Artificial Surprise  (pages 267-291)
Luis Macedo, Amilcar Cardoso, Rainer Reisenzein, Emiliano Lorini
This chapter reviews research on computational models of surprise. Part 1 begins with a description of the phenomenon of surprise in humans, reviews... Sample PDF
Artificial Surprise
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Chapter 16
Tom Adi
A new theory of emotions is derived from the semantics of the language of emotions. The sound structures of 36 Old Arabic word roots that express... Sample PDF
A Theory of Emotions Based on Natural Language Semantics
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Chapter 17
Huma Shah, Kevin Warwick
The Turing Test, originally configured as a game for a human to distinguish between an unseen and unheard man and woman, through a text-based... Sample PDF
Emotion in the Turing Test: A Downward Trend for Machines in Recent Loebner Prizes
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Chapter 18
Félix Francisco Ramos Corchado, Héctor Rafael Orozco Aguirre, Luis Alfonso Razo Ruvalcaba
Emotions play an essential role in the cognitive processes of an avatar and are a crucial element for modeling its perception, learning, decision... Sample PDF
Artificial Emotional Intelligence in Virtual Creatures
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Chapter 19
Sarantos I. Psycharis
In our study we collected data with respect to cognitive variables (learning outcome), metacognitive indicators (knowledge about cognition and... Sample PDF
Physics and Cognitive-Emotional-Metacognitive Variables: Learning Performance in the Environment of CTAT
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Chapter 20
Anthony G. Francis Jr., Manish Mehta, Ashwin Ram
Believable agents designed for long-term interaction with human users need to adapt to them in a way which appears emotionally plausible while... Sample PDF
Emotional Memory and Adaptive Personalities
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Chapter 21
Dorel Gorga, Daniel K. Schneider
The purpose of this contribution is to discuss conceptual issues and challenges related to the integration of emotional agents in the design of... Sample PDF
Computer-Based Learning Environments with Emotional Agents
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Chapter 22
Emotional Ambient Media  (pages 443-459)
Artur Lugmayr, Tillmann Dorsch, Pabo Roman Humanes
The “medium is the message”: nowadays the medium as such is non-distinguishable from its presentation environment. However, what is the medium in an... Sample PDF
Emotional Ambient Media
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Chapter 23
Jordi Vallverdú, David Casacuberta
During the previous stage of our research we developed a computer simulation (called ‘The Panic Room’ or, more simply, ‘TPR’) dealing with synthetic... Sample PDF
Modelling Hardwired Synthetic Emotions: TPR 2.0
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Chapter 24
Cecile K.M. Crutzen, Hans-Werner Hein
A vision of future daily life is explored in Ambient Intelligence (AmI). It follows the assumption that information technology should disappear into... Sample PDF
Invisibility and Visibility: The Shadows of Artificial Intelligence
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