1st Edition

An Introduction to Ethorobotics Robotics and the Study of Animal Behaviour

Edited By Judit Abdai, Adam Miklosi Copyright 2025
    584 Pages 115 B/W Illustrations
    by Routledge

    This pioneering text explores the emerging discipline of ethorobotics which brings together the fields of animal behaviour and robotics. It encourages closer collaboration between behavioural scientists and engineers to facilitate the creation of robots with a higher degree of functionality in animal/human environments, and to broaden understandings of animal behaviour in new and intriguing ways.

    Utilizing the knowledge of key ethologists and roboticists in the field today, the book is divided into four major parts. The first part is written for those with little or no background in the biology of animal behaviour, particularly for those coming from a engineering background seeking an accessible introduction to the field and how it can be applied to robotic behaviour. Topics include problem solving in animals, social cognition and communication (visual, acoustic, olfactory, etc.). The second part is an introduction to the basic construction of robots for non-engineers, and the possibilities offered by current technical achievements and their limitations to the study of animal behaviour. The third part explores the core theme of ethorobotics, the basic framework of the discipline, the field’s evolution, and current topics including ethical considerations, autonomy, to ‘living’ social robots. The fourth and final chapter looks at ethorobotics in practice through key research projects which have had the biggest impact.

    This is a ground-breaking interdisciplinary text which will appeal to upper-level undergraduates, postgraduates and researchers focusing on animal behaviour and cognition, as well as those undertaking courses in engineering, social robotics, biologically inspired robotics, AI, human-robot and animal-robot interactions.



    1. Ethology: The science of animal behaviour - Judit Abdai, Ádám Miklósi

    1.1. Ethology as the study of behaviour

    1.2. The ‘four questions’ of ethology

    1.3. Description and analysis of behaviour

    1.4. Modelling of behaviour systems in ethology

    1.5. Cognitive ethology: analysis of problem-solving behaviour

    1.6. Physical problem solving

    1.6.1. Spatial problem-solving

    1.6.2. Time and rhythms

    1.6.3. Mental architectures for objects

    1.6.4. Ethorobotic perspective

    1.7. Social problem solving

    1.7.1. Group structure

    1.7.2. A behavioural model on describing social complexity

    1.7.3. Social skills facilitating group living

    1.7.4. Ethorobotic perspective

    1.8. Communication

    1.8.1. Definition of communication and the use of terms

    1.8.2. Form of signals

    1.8.3. Intentionality in communication

    1.8.4. The versatility of communication system

    1.8.5. The communicative cycle

    1.8.6. Intra vs interspecific communication

    1.8.7. Linguistic vs non-linguistic communication

    1.8.8. Honesty and deception

    1.8.9. Ethorobotic perspectiv

    1.9. Social information gathering

    1.9.1. Social influence

    1.9.2. Social learning

    1.9.3. Learning from whom?

    1.9.4. Ethorobotic perspective

    1.10 Cooperation

    1.10.1. Cooperation and defection

    1.10.2. Contexts for cooperation

    1.10.3. Behavioural synchronisation

    1.10.4. Recruitment and choosing partners

    1.10.5. Sensitivity for outcomes

    1.10.6. Teaching

    1.10.7. Ethorobotic perspective

    1.11. Development of behaviour

    1.11.1. Developmental plasticity

    1.11.2. Maturation

    1.11.3. Environmental effects on development

    1.11.4. Sensitive periods

    1.11.5. The origin of problem-solving skills

    1.11.6. Exploration, attention and learning

    1.11.7. Learning mechanisms for accommodation to environmental challenges

    1.11.8. Play

    1.11.9. Ethorobotical perspective


    2. Ethorobotics: Ethological approach to interactive, social robots - Judit Abdai, Ádám Miklósi

    2.1. Introduction

    2.1.1. Possible definitions for robots

    2.1.2. A challenge to robotics

    2.1.3. The ‘Santa Claus’ phenomenon

    2.1.4. Conclusions, prospects, questions

    2.2. The robots among us

    2.2.1. Robots in the society

    2.2.2. Human-Robot Interaction (HRI)

    2.2.3. Animal-Robot Interaction

    2.2.4. How to measure HRI performance

    2.2.5. Conclusions, prospects, questions

    2. 3. What is ethorobotics?

    2.3.1. Definition

    2.3.2. Ethorobotics vs social robotics

    2.3.3. The uncanny valley hypothesis

    2.3.4. Ethorobots as species

    2.3.5. The niche concept

    2.3.6. The robot phenotype: morphology, behaviour, and performance

    2.3.7. Robot taxonomy

    2.3.8. Technological evolution

    2.3.9. Conclusions, prospects, questions

    2.4. Planning of ethorobots

    2.4.1. What are ethorobots for? Solving problems

    2.4.2. The concept of embodiment

    2.4.3. The structure of embodiment

    2.4.4. The nature of embodiment

    2.4.5. The environment and embodiment

    2.4.6. Modularity and segmentation

    2.4.7. Autonomy

    2.4.8. Animacy and restlessness

    2.4.9. Readiness

    2.4.10. Personality: consistent tendencies in behavioural differences among individuals

    2.4.11. Conclusions, prospects, questions

    2.5. Ethorobotic perspectives for building robotic mental architectures

    2.5.1. Inner states: motivation

    2.5.2. Inner states: emotion

    2.5.3. Physical problem solving

    2.5.4. Social problem solving

    2.5.5. Conclusions, prospects, questions

    2.6. Social behaviour functions in robots

    2.6.1. Robots in the human social network

    2.6.2. Attachment

    2.6.3. Communication

    2.6.4. Social partners as information sources

    2.6.5. Cooperation

    2.6.6 Conclusions, prospects, questions

    2.7. Ethical considerations: ethorobots are machines


    3. An introduction to robot construction - Bence Ferdinandy, Péter Telkes, Judit Abdai, Ádám Miklósi

    3.1. Introduction

    3.2. An overview of sensing skills

    3.3. Internal sensors

    3.3.1. Measuring kinematic parameters: proprioceptors

    3.3.2. Measuring dynamic parameters

    3.4. External sensors

    3.4.1. Visual sensors - eyes

    3.4.2. Cameras as robotic eyes

    3.4.3. Active visual sensors

    3.4.4. Bioinspired sensors for vision

    3.4.5. The advantages and disadvantages of using visual sensors

    3.4.6. Hearing sensors – ears

    3.4.7. Microphones as robotic ears

    3.4.8. Active acoustic sensors

    3.4.9. Bioinspired sensors for hearing

    3.4.10. The advantages and disadvantages of using acoustic sensors

    3.4.11. Smelling and tasting sensors – noses and tongues

    3.4.12. Olfaction

    3.4.13. Gustation

    3.4.14. Artificial chemosensation: e-noses and e-tongues

    3.4.15. The advantages and disadvantages of using chemosensors

    3.4.16. Magnetosensors

    3.4.17. Artificial magnetosensors

    3.4.18. Conclusions on sensing for ethorobotics

    3.5. Mechanisms for movement and actions

    3.5.1. Bodies to be moved

    3.5.2. Moving on the ground: trunk, neck, tail

    3.5.3. Moving on the ground: legs

    3.5.4. Moving on the ground: wheels

    3.5.5. Legs or wheels?

    3.5.6. Manipulating objects

    3.4.3. Alternative actuators for controlling movements

    3.5.7. Signalling actions

    3.6. Energy sources for autonomous robots

    3.7. Conclusions for ethorobotics

    3.8. Modelling problem-solving architectures for ethorobots

    3.8.1. Introduction

    3.8.2. The Standard Model of the Mind (smom)

    3.8.3. Extended Standard Problem Solving Architecture (ESPSA)

    3.9. Artificial intelligence and machine learning

    3.9.1. Introduction

    3.9.2. Paradigms in machine learning

    3.9.3. Models

    3.9.4. Techniques

    3.10. Architecture implementations

    3.10.1. Emergence and hierarchy as a property of complex systems

    3.10.2. Architectures from computer science

    3.10.3. Architectures from control theory

    3.10.4. Deep reinforcement learning architecture

    3.10.5. SOAR: a ‘cognitive’ architecture

    3.10.6. Conclusions for ethorobotics



    4. Ethorobotics in practice: past, present and future – case studies - Beáta Korcsok, Ádám Miklósi, Judit Abdai

    4.1. Introduction

    4.2. Nao

    4.2.1. Overview

    4.2.2. Embodiment

    4.2.3 Further developments and improvements

    4.2.4 Autonomy

    4.2.5. Sensory and motor capabilities

    4.2.6. Software architecture and related system capabilities

    4.2.7. Utilisation in HRI research

    4.2.8. Ethorobotic perspectives

    4.2.9. Future utility

    4.2.10. Similar robots

    4.3. Kaspar

    4.3.1. Overview

    4.3.2. Embodiment

    4.3.3. Further developments and improvements

    4.3.4. Autonomy

    4.3.5. Sensory and motor capabilities

    4.3.6. Software architecture and related system capabilities

    4.3.7. Utilisation in HRI research

    4.3.8. Ethorobotic perspectives

    4.3.9. Future utility

    4.3.10 Similar robots

    4.4. Aibo

    4.4.1. Overview

    4.4.2. Embodiment

    4.4.3. Further developments and improvements

    4.4.4. Autonomy

    4.4.5. Sensory and motor capabilities

    4.4.6. Software architecture and related system capabilities

    4.4.7. Utilisation in HRI research

    4.4.8. Ethorobotic perspectives

    4.4.9. Future utility

    4.4.10. Similar robots

    4.5. Bellabot

    4.5.1. Overview

    4.5.2. Embodiment

    4.5.3. Further developments and improvements

    4.5.4. Autonomy

    4.5.5. Sensory and motor capabilities

    4.5.6. Software architecture and related system capabilities

    4.5.7. Utilisation in HRI research

    4.5.8. Ethorobotic perspectives

    4.5.9. Future utility

    4.5.10. Similar robots

    4.6. Conclusions from an ethorobotic perspective


    Judit Abdai, Department of Ethology, Eotvos Lorand University, Hungary.

    Ádám Miklósi, Department of Ethology, Eotvos Lorand University, Hungary.