Human-Robot Interaction in Social Robotics

Book description

Social robots are a frontier research area in robotics and human–computer interaction. This book summarizes the research of the Robovie project at ATR Intelligent Robotics and Communication Laboratories, a world leader in humanoid interactive robotics. The text covers interdisciplinary topics related to interactive robots, including human behavior recognition and behavior-based control. It presents the results of field studies conducted with non-technical users in everyday environments—such as train stations and shopping malls—and discusses the implementation of robots that interact with sensors and users over a telecommunications network.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. About the Authors
  7. Preface
  8. 1 Introduction to Network Robot Approach for Human–Robot Interaction
    1. 1.1 From Navigation and Manipulation to Human–Robot Introduction
    2. 1.2 Interactive Robots
    3. 1.3 Network Robots
  9. 2 Field Tests—Observing People’s Reaction
    1. 2.1 Introduction
    2. 2.2 Interactive Humanoid Robots for a Science Museum
      1. Abstract
      2. 2.2.1 Introduction
      3. 2.2.2 Related Works
      4. 2.2.3 The Osaka Science Museum
        1. 2.2.3.1 General Settings
        2. 2.2.3.2 Our Experimental Settings
      5. 2.2.4 System Configuration
        1. 2.2.4.1 Database
        2. 2.2.4.2 Embedded Ubiquitous Sensors in an Environment
        3. 2.2.4.3 Humanoid Robots
      6. 2.2.5 Robot Behavior
        1. 2.2.5.1 Locomotive Robot
        2. 2.2.5.2 Robots That Talk with Each Other
        3. 2.2.5.3 A Robot Saying Goodbye
      7. 2.2.6 Experiment
        1. 2.2.6.1 A 2-Month Exhibition
        2. 2.2.6.2 Results of the 2-Month Experiment
        3. 2.2.6.3 Experiments on the Behavior of Robots
        4. 2.2.6.4 Results of Robots’ Behavior
      8. 2.2.7 Discussion and Conclusion
        1. 2.2.7.1 Contributions
        2. 2.2.7.2 A Perspective on Autonomy for a Communication Robot in Daily Life
    3. Acknowledgments
    4. References
    5. 2.3 Humanoid Robots as a Passive-Social Medium—A Field Experiment at a Train Station
      1. Abstract
      2. 2.3.1 Introduction
      3. 2.3.2 Multi-robot Communication System
        1. 2.3.2.1 Design Policy
        2. 2.3.2.2 Humanoid Robot
        3. 2.3.2.3 Sensor
        4. 2.3.2.4 Scenario-Controlling System
        5. 2.3.2.5 Example of a Script
      4. 2.3.3 Experiment
        1. 2.3.3.1 Method
        2. 2.3.3.2 Participants
        3. 2.3.3.3 Conditions
        4. 2.3.3.4 Content of Scenarios
        5. 2.3.3.5 Measurement
        6. 2.3.3.6 Hypotheses
        7. 2.3.3.7 Results
      5. 2.3.4 Overview
        1. 2.3.4.1 Contribution to HRI Research
        2. 2.3.4.2 Contribution to Robot Design as a Medium
        3. 2.3.4.3 Effects of Robots as Passive-Social Medium
        4. 2.3.4.4 Novelty Effect
        5. 2.3.4.5 Limitations
      6. 2.3.5 Conclusion
    6. Acknowledgments
    7. References
    8. 2.4 An Affective Guide Robot in a Shopping Mall
      1. Abstract
      2. 2.4.1 Introduction
      3. 2.4.2 Design
      4. 2.4.3 Contemplating Robot Roles
        1. 2.4.3.1 Role 1: Guiding
        2. 2.4.3.2 Role 2: Building Rapport
        3. 2.4.3.3 Role 3: Advertisements
      5. 2.4.4 System Design
      6. 2.4.5 Behavior Design
        1. 2.4.5.1 General Design
        2. 2.4.5.2 Guiding Behavior
        3. 2.4.5.3 Building Rapport Behavior
        4. 2.4.5.4 Behavior for Advertisements
      7. 2.4.6 System Configuration
      8. 2.4.7 Autonomous System
        1. 2.4.7.1 Robovie
        2. 2.4.7.2 Person Identification
        3. 2.4.7.3 Position Estimation
        4. 2.4.7.4 Behavior and Episode Rules
        5. 2.4.7.5 Nonverbal Behaviors
      9. 2.4.8 Operator’s Roles
        1. 2.4.8.1 Substitute of Speech Recognition
        2. 2.4.8.2 Supervisor of Behavior Selector
        3. 2.4.8.3 Knowledge Provider
      10. 2.4.9 Conversational Fillers
      11. 2.4.10 Field Trial
        1. 2.4.10.1 Procedure
      12. 2.4.11 Results
        1. 2.4.11.1 Overall Transition of Interactions
        2. 2.4.11.2 Perception of Participants
        3. 2.4.11.3 Comparison with an Information Display
        4. 2.4.11.4 Integrated Analysis
      13. 2.4.12 Discussion
        1. 2.4.12.1 Degree of Operator Involvement
      14. 2.4.13 Conclusion
    9. Acknowledgments
    10. References
  10. 3 Users’ Attitude and Expectations
    1. 3.1 Introduction
    2. Reference
    3. 3.2 Is Interaction with Teleoperated Robots Less Enjoyable?
      1. Abstract
      2. 3.2.1 Introduction
      3. 3.2.2 Experimental System
      4. 3.2.3 Experiment
        1. 3.2.3.1 Participants and Environment
        2. 3.2.3.2 Procedure
        3. 3.2.3.3 Conditions
        4. 3.2.3.4 Measures
      5. 3.2.4 Results
        1. 3.2.4.1 Does Prior Knowledge of Operator’s Presence Vary Impressions?
        2. 3.2.4.2 Participants Affected by Prior Knowledge of Operator’s Presence
      6. 3.2.5 Conclusion
    4. Acknowledgments
    5. References
    6. 3.3 Hesitancy in Interacting with Robots—Anxiety and Negative Attitudes
      1. Abstract
      2. 3.3.1 Introduction
      3. 3.3.2 Psychological Scales for Human–Robot Interaction
        1. 3.3.2.1 Background: Attitudes and Anxiety
        2. 3.3.2.2 Negative Attitudes toward Robots Scale (NARS)
        3. 3.3.2.3 Robot Anxiety Scale (RAS)
      4. 3.3.3 Experiment
        1. 3.3.3.1 Participants and Settings
        2. 3.3.3.2 Procedures
        3. 3.3.3.3 Measurement
      5. 3.3.4 Results
        1. 3.3.4.1 Measurement Result
        2. 3.3.4.2 Prediction of Communication Avoidance Behavior from Anxiety and Negative Attitudes
      6. 3.3.5 Conclusion
    7. Acknowledgments
    8. References
    9. Appendix—Items in the NARS [15] and RAS [16]
  11. 4 Modeling Natural Behaviors for Human-Like Interaction with Robots
    1. 4.1 Introduction
    2. References
    3. 4.2 A Model of Natural Deictic Interaction
      1. 4.2.1 Introduction
      2. 4.2.2 Related Works
      3. 4.2.3 Model of Deictic interaction
      4. 4.2.4 Development of a Communication Robot Capable of Natural Deictic Interaction
      5. 4.2.5 Evaluation Experiment
        1. 4.2.5.1 Method
        2. 4.2.5.2 Procedures
        3. 4.2.5.3 Measurement
        4. 4.2.5.4 Results
        5. 4.2.5.5 Summary
        6. 4.2.5.6 Limitations
      6. 4.2.6 Conclusion
    4. Acknowledgments
    5. References
    6. 4.3 A Model of Proximic Behavior for Being Together While Sharing Attention
      1. 4.3.1 Introduction
      2. 4.3.2 Related Work
      3. 4.3.3 Modeling of Implicit Cue for Attention-Shifting
        1. 4.3.3.1 Definition of “Implicit” Attention-Shifting
        2. 4.3.3.2 Overview of Modeling
        3. 4.3.3.3 Estimating Attention from Implicit Cues
        4. 4.3.3.4 Detecting Partner’s Attention-Shift from Implicit Cues
        5. 4.3.3.5 Predicting Partner’s Next Attention from Implicit Cues
      4. 4.3.4 Modeling of Spatial Position
        1. 4.3.4.1 Constraint of Proximity
        2. 4.3.4.2 Body Orientation
        3. 4.3.4.3 Constraint of Partner’s Field of View
        4. 4.3.4.4 Constraint of Robot’s Field of View
      5. 4.3.5 Position Model for a Presenter Robot
      6. 4.3.6 Implementation
        1. 4.3.6.1 System Configuration
        2. 4.3.6.2 Robot Controller
      7. 4.3.7 Evaluation Experiment
        1. 4.3.7.1 Conditions
        2. 4.3.7.2 Procedure
        3. 4.3.7.3 Measures
        4. 4.3.7.4 Hypothesis and Predictions
      8. 4.3.8 Results
        1. 4.3.8.1 Verification of Prediction 1
        2. 4.3.8.2 Verification of Prediction 2
        3. 4.3.8.3 Verification of Prediction 3
      9. 4.3.9 Limitations
      10. 4.3.10 Conclusions
    7. References
    8. 4.4 A Model for Natural and Comprehensive Direction Giving
      1. 4.4.1 Introduction
      2. 4.4.2 Related Works
        1. 4.4.2.1 Utterance
        2. 4.4.2.2 Gesture
        3. 4.4.2.3 Timing
      3. 4.4.3 Modeling Robot’s Direction Giving
        1. 4.4.3.1 Utterance
        2. 4.4.3.2 Gesture
        3. 4.4.3.3 Timing
      4. 4.4.4 Evaluation Experiment
        1. 4.4.4.1 Hypothesis and Predictions
        2. 4.4.4.2 Method
      5. 4.4.5 Results
        1. 4.4.5.1 Verification of Predictions
        2. 4.4.5.2 Comparison of Naturalness Ratings
      6. 4.4.6 Limitations
      7. 4.4.7 Conclusion
    9. Acknowledgments
    10. References
  12. 5 Sensing Systems: Networked Robot Approach
    1. 5.1 Introduction
    2. 5.2 Laser-Based Tracking of Human Position and Orientation Using Parametric Shape Modeling
      1. Abstract
      2. 5.2.1 Introduction
      3. 5.2.2 Related Work
      4. 5.2.3 Position Tracking
        1. 5.2.3.1 Detection and Association
        2. 5.2.3.2 Particle Filtering
        3. 5.2.3.3 State Model
        4. 5.2.3.4 Motion Model
        5. 5.2.3.5 Likelihood Model
      5. 5.2.4 Orientation Estimation
        1. 5.2.4.1 Theoretical Shape Model
        2. 5.2.4.2 Radial Data Representation
        3. 5.2.4.3 Empirical Distance Distribution Model
        4. 5.2.4.4 First-Pass θ Determination
        5. 5.2.4.5 Second-Pass θ Determination
        6. 5.2.4.6 Correction of Reversals
      6. 5.2.5 Laboratory Performance Analysis
        1. 5.2.5.1 Setup and Procedure
        2. 5.2.5.2 Results
      7. 5.2.6 Natural Walking Experiment
        1. 5.2.6.1 Setup and Procedure
        2. 5.2.6.2 Results
      8. 5.2.7 Discussion
        1. 5.2.7.1 Performance Tuning
        2. 5.2.7.2 Real-Time Operation
        3. 5.2.7.3 Future Work
      9. 5.2.8 Conclusions
    3. References
    4. 5.3 Super-Flexible Skin Sensors Embedded on the Whole Body, Self-Organizing Based on Haptic Interactions
      1. Abstract
      2. 5.3.1 Introduction
      3. 5.3.2 Background and Comparisons
      4. 5.3.3 Self-Organizing Tactile Sensor Method to Decide Sensor Boundaries
        1. 5.3.3.1 Basic Idea
        2. 5.3.3.2 Feature Space
        3. 5.3.3.3 Overview
        4. 5.3.3.4 CLAFIC Method
        5. 5.3.3.5 Learning Sensor Banks
        6. 5.3.3.6 Somatosensory Map
      5. 5.3.4 Experiments
        1. 5.3.4.1 Hardware
        2. 5.3.4.2 Field Experiment
        3. 5.3.4.3 Construction of the Haptic Interaction Database
      6. 5.3.5 Results
      7. 5.3.6 Discussion
      8. 5.3.7 Conclusions
    5. Acknowledgments
    6. References
    7. 5.4 Integrating Passive RFID tag and Person Tracking for Social Interaction in Daily Life
      1. Abstract
      2. 5.4.1 Introduction
      3. 5.4.2 Person Tracking and Identification
        1. 5.4.2.1 Previous Methods
      4. 5.4.3 Proposed Method
      5. 5.4.4 System Configuration
        1. 5.4.4.1 System Overview
        2. 5.4.4.2 Humanoid Robot
        3. 5.4.4.3 Floor Sensor
      6. 5.4.5 Hypotheses-Based Mechanism
        1. 5.4.5.1 Making a Hypotheses Mechanism
        2. 5.4.5.2 Verifying Hypotheses Mechanism
      7. 5.4.6 Performance Evaluation
        1. 5.4.6.1 Settings
        2. 5.4.6.2 Result
      8. 5.4.7 Discussion
        1. 5.4.7.1 HRI Contributions
        2. 5.4.7.2 Performance Improvement Approach
      9. 5.4.8 Conclusion
    8. Acknowledgments
    9. References
    10. 5.5 Friendship Estimation Model for Social Robots to Understand Human Relationships
      1. Abstract
      2. 5.5.1 Introduction
      3. 5.5.2 Friendship Estimation Model from Observation
        1. 5.5.2.1 Related Research on Friendship
        2. 5.5.2.2 Related Research on Sensor-Based Observation of Humans’ Interactions
        3. 5.5.2.3 Friendship Estimation Model
        4. 5.5.2.4 Algorithm
      4. 5.5.3 Robovie: An Interactive Humanoid Robot
        1. 5.5.3.1 Hardware of Interactive Humanoid Robot
        2. 5.5.3.2 Person Identification with Wireless ID Tags
        3. 5.5.3.3 Interactive Behaviors
      5. 5.5.4 Experiment and Result
        1. 5.5.4.1 Method
        2. 5.5.4.2 Results for Frequency of Friend-Accompanying Behavior
        3. 5.5.4.3 Results for Friendship Estimation
        4. 5.5.4.4 Results for Comparison between Frequency of Interaction with the Robot and Estimation Result
      6. 5.5.5 Conclusions
    11. Acknowledgments
    12. References
    13. 5.6 Estimating Group States for Interactive Humanoid Robots
      1. Abstract
      2. 5.6.1 Introduction
      3. 5.6.2 Estimating a Group State
        1. 5.6.2.1 Sensing Part
        2. 5.6.2.2 Clustering Part
        3. 5.6.2.3 Estimating Part
      4. 5.6.3 Experiment
        1. 5.6.3.1 Gathering Data for Evaluation
        2. 5.6.3.2 Making an SVM Model Using Gathered Data
        3. 5.6.3.3 Evaluation of Proposed Method
      5. 5.6.4 Discussion
        1. 5.6.4.1 Contributions for Human–Robot Interaction
        2. 5.6.4.2 Performance Improvement Approach
      6. 5.6.5 Conclusion
    14. Acknowledgments
    15. References
  13. 6 Shared Autonomy and Teleoperation
    1. 6.1 Introduction
    2. References
    3. 6.2 A Semi-Autonomous Social Robot That Asks Help from a Human Operator
      1. Abstract
      2. 6.2.1 Introduction
      3. 6.2.2 Semi-Autonomous Robot System
        1. 6.2.2.1 Overview
        2. 6.2.2.2 Reactive Layer
        3. 6.2.2.3 Behavioral Layer
        4. 6.2.2.4 Reflective Layer
      4. 6.2.3 Field Trial at a Train Station
        1. 6.2.3.1 Environment and Settings
        2. 6.2.3.2 Results
      5. 6.2.4 Conclusion
    4. Acknowledgments
    5. References
    6. 6.3 Teleoperation of Multiple Social Robots
      1. Abstract
      2. 6.3.1 Introduction
        1. 6.3.1.1 Related Work
        2. 6.3.1.2 Design Considerations
        3. 6.3.1.3 Social Human-Robot Interaction
        4. 6.3.1.4 Autonomy Design
        5. 6.3.1.5 Teleoperation Interface Design
        6. 6.3.1.6 Task Difficulty Metrics
      3. 6.3.2 Implementation
        1. 6.3.2.1 Social Human–Robot Interaction
        2. 6.3.2.2 Autonomy Design
        3. 6.3.2.3 Multi-Robot Coordination
        4. 6.3.2.4 Teleoperation Interface Design
      4. 6.3.3 Experimental Validation
        1. 6.3.3.1 Laboratory Experiment
        2. 6.3.3.2 Experimental Results
        3. 6.3.3.3 Operator Experience
      5. 6.3.4 Simulation
        1. 6.3.4.1 Interaction Model
        2. 6.3.4.2 Task Success
        3. 6.3.4.3 Operator Allocation
        4. 6.3.4.4 Number of PTC Behaviors
        5. 6.3.4.5 Relying on Autonomy
      6. 6.3.5 Discussion
        1. 6.3.5.1 Effectiveness of Shared Autonomy
        2. 6.3.5.2 Defining Criticality
        3. 6.3.5.3 Operator Workload
        4. 6.3.5.4 Limitations
      7. 6.3.6 Conclusions
    7. Acknowledgment
    8. References
  14. 7 Learning and Adaptation
    1. 7.1 Introduction
    2. Reference
    3. 7.2 Moderating Users’ Tension to Enable Them to Exhibit Other Emotions
      1. Abstract
      2. 7.2.1 Introduction
      3. 7.2.2 Does Tension Disturb Occurrence of Other Emotions?
        1. 7.2.2.1 Background
        2. 7.2.2.2 Hypothesis: Disturbance Caused by Tension
        3. 7.2.2.3 Hypothesis Verification
      4. 7.2.3 System Configuration
        1. 7.2.3.1 Overview
        2. 7.2.3.2 Robovie
        3. 7.2.3.3 Face Tracking Unit
        4. 7.2.3.4 Emotion Recognition Unit
        5. 7.2.3.5 Speech Recognition Unit
        6. 7.2.3.6 Behavior Selector: Tension Moderation
      5. 7.2.4 Experiment
        1. 7.2.4.1 Settings
        2. 7.2.4.2 Results
        3. 7.2.4.3 Discussion
      6. 7.2.5 Conclusion
    4. Acknowledgments
    5. References
    6. 7.3 Adapting Nonverbal Behavior Parameters to Be Preferred by Individuals
      1. Abstract
      2. 7.3.1 Introduction
      3. 7.3.2 The Behavior Adaptation System
        1. 7.3.2.1 The Robot and Its Interaction Behaviors
        2. 7.3.2.2 Adapted Parameters
        3. 7.3.2.3 Reward Function
        4. 7.3.2.4 The PGRL Algorithm
      4. 7.3.3 Evaluation
        1. 7.3.3.1 Participants
        2. 7.3.3.2 Settings
        3. 7.3.3.3 Measurements
      5. 7.3.4 Adaptation Results
      6. 7.3.5 Discussion
        1. 7.3.5.1 Difficulties
      7. 7.3.6 Conclusion
    7. Acknowledgments
    8. References
    9. 7.4 Learning Pedestrians’ Behavior in a Shopping Mall
      1. Abstract
      2. 7.4.1 Introduction
        1. 7.4.1.1 Related Works
        2. 7.4.1.2 The Use of Space
        3. 7.4.1.3 Global Behavior
        4. 7.4.1.4 System Configuration
        5. 7.4.1.5 Analysis of Accumulated Trajectories
        6. 7.4.1.6 Anticipation System
        7. 7.4.1.7 Field Test with a Social Robot
      3. 7.4.2 Conclusion
    10. Acknowledgments
    11. References
  15. Index

Product information

  • Title: Human-Robot Interaction in Social Robotics
  • Author(s): Takayuki Kanda, Hiroshi Ishiguro
  • Release date: December 2017
  • Publisher(s): CRC Press
  • ISBN: 9781351832410