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| Titolo: |
Biomimetic and biohybrid systems : 11th international conference, living machines 2022, virtual event, July 19-22, 2022, proceedings / / edited by Alexander Hunt [and six others]
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| Pubblicazione: | Cham, Switzerland : , : Springer, , [2023] |
| ©2023 | |
| Descrizione fisica: | 1 online resource (419 pages) |
| Disciplina: | 006.3 |
| Soggetto topico: | Computer engineering |
| Artificial intelligence | |
| Computer systems | |
| Persona (resp. second.): | HuntAlexander |
| Nota di bibliografia: | Includes bibliographical references and index. |
| Nota di contenuto: | Intro -- Preface -- Organization -- Contents -- Unit Cell Based Artificial Venus Flytrap -- 1 Introduction -- 2 Construction of Unit Cell Based AVF -- 2.1 Unit Cell Design -- 2.2 Motion and Actuation Force Characterization -- 3 Results -- 4 Discussion -- 4.1 Snapping Motion of UC AVF -- 5 Conclusion -- References -- Ten Years of Living Machines Conferences: Transformers-Based Automated Topic Grouping -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Cluster Backgrounds -- 3.2 Temporal Evolution -- 4 Discussions and Conclusion -- References -- Multi-material FDM 3D Printed Arm with Integrated Pneumatic Actuator -- 1 Introduction -- 2 Materials and Methods -- 2.1 Multi-Material 3D Printing Procedure and Parameters -- 2.2 Soft Robotic Arm Design -- 2.3 Print Results and Lift Capability -- 3 Conclusion and Outlook -- References -- SNS-Toolbox: A Tool for Efficient Simulation of Synthetic Nervous Systems -- 1 Introduction -- 2 Neural Models -- 2.1 Non-spiking Neurons and Synapses -- 2.2 Spiking Neurons and Synapses -- 3 Software Design and Workflow -- 3.1 Design Phase -- 3.2 Compilation -- 3.3 Simulation -- 4 Results -- 4.1 Backend Simulation Performance -- 4.2 Backend Variant Performance -- 4.3 Example Network Design -- 5 Discussion and Future Work -- References -- Scaling a Hippocampus Model with GPU Parallelisation and Test-Driven Refactoring -- 1 Introduction -- 2 Hippocampus Review -- 2.1 Neuroanatomy -- 2.2 Unitary Coherent Particle Filter Model -- 3 Experiment Design -- 4 Methods -- 4.1 Task Configuration -- 4.2 TensorFlow -- 4.3 Formal Refactoring Process -- 5 Results -- 5.1 Bottleneck Locations -- 5.2 Final System Performance -- 6 Discussion -- References -- Application-Oriented Comparison of Two 3D Printing Processes for the Manufacture of Pneumatic Bending Actuators for Bioinspired Macroscopic Soft Gripper Systems -- 1 Introduction. |
| 2 Materials and Methods -- 2.1 Printing and Materials -- 2.2 Actuator Design -- 3 Results -- 4 Conclusion and Outlook -- References -- Integrating Spiking Neural Networks and Deep Learning Algorithms on the Neurorobotics Platform -- 1 Introduction -- 1.1 Background -- 2 Method -- 2.1 Neurorobotics Platform -- 2.2 WhiskEye -- 2.3 Environment -- 2.4 Brain Model -- 2.5 Transfer Functions -- 2.6 Predictive Coding Network -- 2.7 Spike Analysis -- 3 Results -- 3.1 Head Angle Estimated by the SNN Follows Ground Truth -- 3.2 PCN Prediction Error Increases with Drift -- 3.3 Ideothetic Information Drives Network in Periods of Darkness -- 4 Discussion -- References -- Quasi-static Modeling of Feeding Behavior in Aplysia Californica -- 1 Introduction -- 2 Model -- 2.1 Odontophore and I2, I3 Muscles -- 2.2 Assumptions -- 2.3 Governing Equations -- 2.4 Reformulation -- 3 Results and Discussion -- References -- Conversion of Elastic Energy Stored in the Legs of a Hexapod Robot into Propulsive Force -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 D-Shaped Leg -- 3.2 Optimization of D-Shaped Leg -- 3.3 Fabrication of the Leg -- 4 Experiment -- 4.1 Fabrication of the Prototype -- 4.2 Control of the Prototype -- 4.3 Experimental Results -- 5 Conclusion -- References -- The Shaker: A Platform for Active Perturbations in Neuromechanical Studies of Small Animals -- 1 Introduction -- 2 The Shaker: A Three Degrees of Freedom Active Perturbation Platform -- 3 Preliminary and Coming Experiments -- References -- The Modelling of Different Dog Breeds on the Basis of a Validated Model -- 1 Introduction -- 2 Material and Methods -- 3 Results and Discussion -- References -- Analyzing 3D Limb Kinematics of Drosophila Melanogaster for Robotic Platform Development -- 1 Introduction -- 2 Methods -- 2.1 Data Collection -- 2.2 Kinematic Analysis -- 3 Results. | |
| 4 Discussion -- References -- Gut Feelings: Towards Robotic Personality Generation with Microbial Fuel Cells -- 1 Introduction -- 2 Background -- 3 Methods -- 4 Results and Discussion -- 5 Conclusion -- References -- Load Feedback from a Dynamically Scaled Robotic Model of Carausius Morosus Middle Leg -- 1 Introduction -- 2 Methods -- 2.1 Robotic Leg Construction -- 2.2 Robot Forward and Inverse Kinematics -- 2.3 Robotic Control -- 2.4 Treadmill and Dynamic Scaling -- 3 Results -- 4 Discussion -- 4.1 Comparison to Biomechanics and Neurophysiology -- 4.2 Application to Robotics -- References -- A Computational Approach for Contactless Muscle Force and Strain Estimations in Distributed Actuation Biohybrid Mesh Constructs -- 1 Introduction -- 2 Methods -- 2.1 Contactless Estimation of Distributed Muscle Strain -- 2.2 Contactless Estimation of Distributed Muscle Force -- 2.3 Characterization of a Biaxial Stretching Platform Towards In Vitro Validation -- 2.4 Statistical Analysis of Contactless Force and Strain Estimation Methods -- 3 Results and Discussion -- 3.1 Muscle Strain Estimation -- 3.2 Muscle Force Estimation -- 3.3 Characterization and Performance of Biaxial Stretching Platform -- 4 Conclusion -- References -- Development and Characterization of a Soft Bending Actuator -- 1 Introduction -- 2 Material Characterization -- 2.1 Electrical Breakdown Strength -- 2.2 Dielectric Constant -- 2.3 Density and Viscosity -- 2.4 Elastic Behavior -- 3 Bending Actuator -- 4 Conclusion and Outlook -- References -- .26em plus .1em minus .1emEvaluation of Gait Generation in Quadrupedal Legged Locomotion with Changing Anterior/Posterior Extreme Positions -- 1 Introduction -- 2 Spinal Cat Model -- 2.1 Leg Controller -- 2.2 Trajectory Planning -- 2.3 Phase Transition from the Stance to the Swing -- 3 Simulation with the Spinal Cat Model -- 3.1 Methods. | |
| 3.2 Color Maps for Evaluations -- 3.3 Stability Analysis Using Potential Function -- 3.4 Results -- 4 Discussions -- 4.1 Gaits with Forward Movement -- 4.2 Walk-Trot Transition Mechanism -- 5 Conclusion -- References -- Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method -- 1 Introduction -- 1.1 Background and Related Work -- 2 Methodology -- 2.1 Experimental Setup -- 2.2 Task Overview -- 2.3 Active Inference Framework -- 2.4 Experimental Conditions -- 3 Results -- 3.1 Localisation and Error -- 3.2 Belief Updating -- 3.3 Behaviour -- 4 Discussion -- References -- SLUGBOT, an Aplysia-Inspired Robotic Grasper for Studying Control -- 1 Introduction -- 1.1 Feeding Behavior in Aplysia and Prior Work -- 2 Methods -- 2.1 Fabricating McKibben Artificial Muscles -- 2.2 Fabricating Flat Artificial Muscles -- 2.3 Odontophore Design and Fabrication -- 2.4 Robot Assembly -- 2.5 Robot Control -- 3 Results -- 4 Discussion -- 4.1 Morphological Differences Between SLUGBOT and Aplysia -- 4.2 Neuronal Controller -- 5 Conclusion -- References -- Robotic Platform for Testing a Simple Stereopsis Network -- 1 Introduction -- 2 Methods -- 2.1 Robot and Cameras -- 2.2 Neural Network -- 3 Preliminary Results and Discussion -- 3.1 Camera Binocular Images -- 3.2 Future Work -- References -- A Scalable Soft Robotic Cellbot -- 1 Introduction -- 2 Concept of Robot Movement -- 3 Simulation Results for 3-Cell Model -- 4 Forces on n-Cell Model -- 5 Simulation Results for n-Cell Model -- 6 Physical Robot Results -- 7 Conclusions and Future Work -- References -- A Real-World Implementation of Neurally-Based Magnetic Reception and Navigation -- 1 Introduction -- 2 Methods -- 2.1 Summary of Earlier Work: Simulation Baseline -- 2.2 Current Study: Magnetic Coil System, Robotic Rate Table, and Physical Sensing -- 2.3 Current Study: Experiments -- 3 Results. | |
| 4 Discussion and Conclusion -- 5 Future Work -- References -- Design of a Biomolecular Neuristor Circuit for Bioinspired Control -- 1 Introduction -- 2 Methods -- 2.1 Biological Neuron Model -- 2.2 Neuristor Model -- 3 Results and Discussion -- 4 Conclusion -- References -- GymSlug: Deep Reinforcement Learning Toward Bio-inspired Control Based on Aplysia californica Feeding -- 1 Introduction -- 2 Methods -- 2.1 Hybrid Biomechanical Model of the Musculature and Boolean Network Model of Known Motor Neurons -- 2.2 GymSlug Reinforcement Learning Environment -- 2.3 Learning Model and Training Setup -- 3 Results -- 3.1 Deep Reinforcement Learning Achieves Effective Motor Neuron Control on the Hybrid Simulation Environment -- 3.2 Robustness of Trained Agent Policy -- 3.3 Egestion Behavior Training -- 4 Conclusion -- References -- A Synthetic Nervous System with Coupled Oscillators Controls Peristaltic Locomotion -- 1 Introduction -- 2 Simplified Worm Robot Kinematic Model -- 3 Methods -- 3.1 Mathematical Models -- 3.2 Functional Subnetwork Tuning -- 3.3 Stability Analysis -- 4 Results -- 4.1 SNS Simulation -- 4.2 Stability -- 5 Discussion and Future Work -- References -- Simple Reactive Head Motion Control Enhances Adaptability to Rough Terrain in Centipede Walking -- 1 Introduction -- 2 Model -- 3 Result -- 4 Conclusion and Future Work -- References -- Surrogate Modeling for Optimizing the Wing Design of a Hawk Moth Inspired Flapping-Wing Micro Air Vehicle -- 1 Introduction -- 2 Method -- 2.1 Wing Geometry Modeling -- 2.2 Flapping Kinematics -- 2.3 Computational Aerodynamic Simulations -- 3 Results and Discussion -- References -- A Novel Multi-vision Sensor Dataset for Insect-Inspired Outdoor Autonomous Navigation -- 1 Introduction -- 2 The Biological Principles in Insect Navigation -- 2.1 Visual Perception -- 2.2 Insect Visual Navigation Models. | |
| 2.3 Neuromorphic Processing. | |
| Titolo autorizzato: | Biomimetic and Biohybrid Systems ![]() |
| ISBN: | 3-031-20470-0 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 996503471803316 |
| Lo trovi qui: | Univ. di Salerno |
| Opac: | Controlla la disponibilità qui |