Sensory Systems for Robotic Applications

Contents
About the Editors
1 Development of tactile sensors for intelligent robotics research
1.1 Introduction
1.2 Developed tactile sensors and implementations
1.2.1 Conformable and scalable tactile sensor for 3D-curved surfaces
1.2.1.1 Ability to fit on 3D-curved surfaces due to branch-shaped sheet
1.2.1.2 Customizability by free cutting
1.2.1.3 Communication networks and modularization
1.2.1.4 Pressure sensing by photo-reflector
1.2.1.5 Examples of implementation
1.2.2 High-density tactile sensor for bare-hand-like sensor gloves
1.2.2.1 Design and implementation
1.2.2.2 Consistency with mass production
1.2.2.3 Contact resistance method
1.2.2.4 Toward new applications using tactile sensing
1.2.3 Stretchable tactile sensor based on inverse problem analysis
1.2.3.1 Electrical impedance tomography
1.2.3.2 Conductive rubber sheet
1.2.3.3 Conductive knit fabric
1.2.3.4 Pressure-sensitive but stretch-insensitive conductor
1.2.3.5 Issues and future prospects
1.3 Tactile sensing and robotics: future direction
1.3.1 Automaton model
1.3.2 State-action model
1.3.3 Future direction
1.4 Conclusion
References
2 Developmental soft robotics
2.1 Introduction
2.2 Bio-inspired soft robotics
2.2.1 Soft materials and soft actuation
2.2.2 Soft robot control, simulation and learning
2.3 Developmental soft robotics
2.3.1 Facets of development
2.3.1.1 Incremental process and self-organization
2.3.1.2 Degrees of freedoms, freezing and freeing
2.3.1.3 Self-exploration and spontaneous activity
2.3.1.4 Intrinsic motivation
2.3.1.5 Categorization
2.3.1.6 Morphology and morphological computation
2.3.1.7 Sensory-motor coordination
2.3.1.8 Body schema
2.3.2 Soft robotics and developmental time scales
2.3.3 Design principles
2.3.3.1 Functional morphology and morphological computation
2.3.3.2 Soft system–environment interactions
2.3.3.3 Sensor morphology and soft perception
2.3.4 Ontogenetics and adaptivity
2.3.4.1 Adaptation and growth
2.3.4.2 Tool use and extended phenotype
2.4 Challenges and perspectives
2.4.1 Evolutionary robotics
2.4.2 Complexity and scalability
2.4.3 Learning through the body
References
3 Three-axis tactile sensor using optical transduction mechanism
3.1 Introduction
3.2 Design concept of the optical three-axis tactile sensor
3.2.1 Basic principle
3.2.2 Conical-columnar feeler-type optical three-axis tactile sensor
3.2.3 Tracking-centroid-movement-type optical three-axis tactile sensor
3.3 Actual design of the optical three-axis tactile sensor
3.3.1 Aluminum-dome type
3.3.2 Rubber-dome type
3.3.3 Tracking-contact-area-movement type
3.4 Applications
3.4.1 Tasks achieved by three-axis tactile sensing
3.4.2 Picking-up and counting paper
3.4.3 Human-robot communication
3.5 Conclusion
References
4 Strain sensors for soft robotic applications
4.1 Introduction
4.2 Mechanisms for strain sensors
4.2.1 Strain sensing based on intrinsic properties of materials and tunneling effect
4.2.2 Disconnection and microcrack propagation mechanism
4.3 Classification of strain sensors
4.3.1 Piezoresistive strain sensors
4.3.2 Capacitive-type strain sensors
4.3.3 Triboelectric-type strain sensors
4.4 Conclusion
References
5 Neuromorphic principles for large-scale robot skin
5.1 Classical engineering approaches are reaching their limits
5.1.1 Motivations for robot skin
5.1.2 Robot skin
5.1.3 Challenges and limits of robot skin
5.2 Biology employs a toolbox full of optimized principles
5.2.1 Skin receptors are tuned to sense specific stimulus features
5.2.2 Skin receptors transduce stimuli features to binary action potentials
5.2.3 Skin information is encoded by different neural codes
5.2.4 Skin information ascends somatotopically ordered
5.2.5 Skin information is structured and processed hierarchically
5.2.5.1 Topographical features
5.2.5.2 Surface structural features (texture)
5.2.5.3 Geometrical and dynamical features
5.2.6 The cognitive where
5.2.7 The cognitive what
5.3 Biological principles are the key to large-scale robot skin
5.3.1 Neuromorphic event-driven sensors
5.3.2 Neuromorphic information representation in hierarchical structures
5.4 Neuromorphic systems realize biological principles
5.4.1 Neuromorphic event-driven vision has been engineered first
5.4.1.1 The dynamic vision sensor
5.4.1.2 The asynchronous time-based vision sensor (ATIS)
5.4.1.3 The dynamic and active vision pixel sensor
5.4.1.4 Applications prove the efficiency of neuromorphic vision sensors
5.4.2 The neuromorphic AER is a standard for transmitting events
5.4.2.1 The AER
5.4.2.2 AER for distributed sensors and processing
5.4.3 The send-on-delta principle allows event-driven transmission and processing in synchronous systems
5.4.3.1 The send-on-delta principle
5.4.3.2 Comparison of SoDP with AER
5.4.4 Neuromorphic event-driven skin is under development
5.4.4.1 Transduction of tactile stimuli to events in quasi-digital AER
5.4.4.2 Neuromorpic event-driven tactile sensors generate events in AER
5.4.4.3 Neuromorphic event-driven tactile sensors with AER for large-scale robot skin
5.4.4.4 Neuromorphic force sensors with high spatiotemporal resolution using SoDP
5.4.5 Neuromorphic information representations mimic the primary somatosensory cortex
5.4.5.1 Robot skin systems structure tactile information somatotopically
5.4.5.2 Real-time robot skin systems with generalized information representations
5.4.6 Neuromorphic parallel information streams of the cognitive where and what
5.4.6.1 The where pathway
5.4.6.2 The what pathway
5.4.6.3 The connection of the where and the what pathway
5.5 The realization of an event-driven large-scale robot skin system
5.5.1 Robot skin system
5.5.1.1 Robot skin
5.5.1.2 Structural self-calibration
5.5.1.3 Event-driven robot skin
5.5.1.4 Neuromorphic skin system
5.5.2 Event-driven reactive skin control
5.5.3 The benefits
References
6 Soft three-axial tactile sensors with integrated electronics for robot skin
6.1 Introduction
6.2 Related work
6.2.1 Piezoelectric-based sensors
6.2.2 Optical-based sensors
6.2.3 Hall-effect-based sensors
6.2.4 PSECR-based sensors
6.2.5 Piezoresistive-based sensors
6.2.6 Capacitive-based sensors
6.2.7 MEMS-based sensors
6.2.8 Proximity detection
6.2.9 Summary of related work
6.3 Three-axis capacitive soft skin sensor
6.3.1 Concept
6.3.2 Implementation
6.3.2.1 Copper beryllium plate with bump
6.3.2.2 Tilt double-sided transducers
6.3.2.3 Temperature compensation pad
6.3.2.4 Manufacturing
6.3.3 Experiments
6.3.3.1 Linearity and hysteresis
6.3.3.2 Tri-axial force
6.3.3.2.1 Normal force calibration
6.3.3.2.2 Shear force calibration
6.3.3.4 Temperature influences compensation and minimum detectable pressure
6.3.3.3 SNR
6.3.4 Summary
6.4 Three-axis Hall-effect sensors
6.4.1 Concept
6.4.2 Implementation
6.4.3 Experiment
6.4.3.1 Test setup
6.4.3.2 Temperature compensation tests
6.4.3.3 Calibration
6.4.3.4 Response time
6.4.3.5 Minimum detectable force
6.4.3.6 SNR
6.4.3.7 Hysteresis
6.4.3.8 Spatial crosstalk test
6.4.3.9 Contact shape detection
6.4.3.10 Measurements on Allegro hand
6.5 Conclusion
References
7 A review of tactile sensing in e-skin, wearable device, robotic, and medical service
7.1 Introduction
7.2 Hardware of various tactile sensing technologies
7.2.1 Resistive
7.2.2 Piezoelectric
7.2.3 Capacitive
7.2.4 Optical
7.2.5 Magnetic field
7.2.6 Quantum tunneling composite
7.2.7 Triboelectric effect
7.2.8 Field-effect transistor
7.3 Design criterion and performance index of a tactile sensing system
7.4 Applications of tactile sensing technologies
7.4.1 Development trend of tactile sensing technologies in e-skin
7.4.2 Development trend of tactile sensing technologies in a wearable device
7.4.3 Development trend of tactile sensing technologies in robotic
7.4.4 Development trend of tactile sensing technologies in medical service
7.5 Challenges and discussion
7.5.1 Standardization of fabrication process
7.5.2 Data transmission of high-density tactile sensing elements
7.5.3 Fault tolerance and autocalibration
7.5.4 Layout of sensing elements on an irregular 3D
References
8 Neuroengineering approaches for cognitive hearing technology
8.1 Introduction
8.2 General aspects of neurofeedback in a hearing aid
8.3 Decoding selective attention to speech from the auditory brainstem response to the temporal fine structure
8.4 Decoding speech comprehension from cortical tracking of speech features
8.5 Enhancing speech comprehension through transcranial electric stimulation
8.6 Summary
References
9 Mobile robot olfaction state-of-the-art and research challenges
9.1 Introduction
9.2 Odour dispersion
9.3 Artificial olfaction
9.3.1 Gas sensing
9.3.2 Flow sensing
9.4 Odour source localisation
9.4.1 Searching odours
9.4.2 Tracking odour plumes
9.4.2.1 Reactive strategies
9.4.2.2 Meta-heuristic search
9.4.2.3 Probabilistic methods
9.4.3 Source declaration
9.5 Learning in mobile robot olfaction
9.5.1 Source-term estimation
9.5.2 Policy search
9.5.2.1 Machine learning
9.5.2.2 Evolutionary computation
9.5.2.3 Swarm approaches
9.6 Open challenges
9.6.1 Artificial olfaction
9.6.2 Odour source localisation
9.6.3 Learning to locate odour sources
References
10 Vision sensors for robotic perception
10.1 Introduction
10.2 RGB cameras for robotic perception
10.3 Stereo cameras
10.4 Event cameras
10.4.1 Hardware
10.4.2 Applications in robotics
10.5 Depth cameras
10.6 Vision sensors for other modalities
10.6.1 Marker-based sensors
10.6.2 Image-based sensors
10.7 Conclusions
Acknowledgements
References
11 Audio sensors
11.1 Audio sensors
11.1.1 Airborne microphones
11.1.2 Microphones for underwater
11.1.3 Microphones for underground and structures
11.1.4 Microphones for biological bodies
11.2 Microphones for audible sounds
11.2.1 Indicators for microphone characteristics
11.3 Microphone array
11.4 Robot audition
11.5 Acoustic signal processing
11.6 OSS for robot audition
11.7 Applications of robot audition
11.7.1 Prince Shotoku robot
11.7.2 Drone audition system
11.7.3 VR system based on bird song scene analysis
11.8 Summary
References
12 Audio and gas sensors
12.1 Audio sensors
12.1.1 Hardware
12.1.1.1 Microphones
12.1.1.1.1 Miniature condenser microphones
12.1.1.1.2 MEMS microphones
12.1.1.2 Portable audio interfaces
12.1.1.3 Recommendations
12.1.1.4 Other acoustic sensors
12.1.2 Software
12.1.2.1 Localization
12.1.2.2 Separation
12.1.2.3 Currently implemented examples
References
Index