top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
Toward Connected, Cooperative and Intelligent IoV [[electronic resource] ] : Frontier Technologies and Applications / / by Kai Liu, Penglin Dai, Victor C.S. Lee, Joseph Kee-Yin Ng, Sang Hyuk Son
Toward Connected, Cooperative and Intelligent IoV [[electronic resource] ] : Frontier Technologies and Applications / / by Kai Liu, Penglin Dai, Victor C.S. Lee, Joseph Kee-Yin Ng, Sang Hyuk Son
Autore Liu Kai
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (327 pages)
Disciplina 004.167
Altri autori (Persone) DaiPenglin
LeeVictor C. S
NgJoseph Kee-Yin
SonSang Hyuk
Soggetto topico Mobile computing
Cooperating objects (Computer systems)
Mathematical optimization
Algorithms
Internet of things
Machine learning
Mobile Computing
Cyber-Physical Systems
Discrete Optimization
Design and Analysis of Algorithms
Internet of Things
Machine Learning
ISBN 981-9996-47-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I. Introduction -- Chapter 1. Background of IoV -- Chapter 2. State-of-the-Art -- Part II. Connected IoV: Vehicular Communications and Data Dissemination -- Chapter 3. Data Dissemination via I2V/V2V Communications in Software Defined Vehicular Networks -- Chapter 4. Network Coding Assisted Data Broadcast in Large-Scale Vehicular Networks -- Chapter 5. Fog Computing Empowered Data Dissemination in Heterogeneous Vehicular Networks -- Chapter 6. Temporal Data Uploading and Dissemination in Real-time Vehicular Networks -- Part III Cooperative IoV: End-Edge-Cloud Cooperative Scheduling and Optimization -- Chapter 7. Convex Optimization on Vehicular End-Edge-Cloud Cooperative Task Offloading -- Chapter 8. An Approximation Algorithm for Joint Data Uploading and Task Offloading in IoV -- Chapter 9. Distributed Task Offloading and Workload Balancing in IoV -- Part IV. Intelligent IoV: Key Enabling Technologies in Vehicular Edge Intelligence -- Chapter 10. Toward Timely and Reliable DNN Inference in Vehicular Edge Intelligence -- Chapter 11. Deep Q-learning based Adaptive Multimedia Streaming in Vehicular Edge Intelligence -- Chapter 12. A Multi-agent Multi-objective Deep Reinforcement Learning Solution for Digital Twin in Vehicular Edge Intelligence -- Part V. Case Studies -- Chapter 13. See Through System -- Chapter 14. Non-Line-of-Sight Collision Warning System -- Chapter 15. Proactive Traffic Abnormity Warning System -- Chapter 16. UAV-assisted Pedestrian Detection System -- Chapter 17. Vehicular Indoor Localization and Tracking System -- Part VI. Conclusion and Future Directions -- Chapter 18. Conclusion -- Chapter 19. Future Directions.
Record Nr. UNINA-9910845085903321
Liu Kai  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Towards autonomous robot systems : 22nd annual conference, TAROS 2021, Lincoln, UK, September 8-10, 2021 : proceedings / / Charles Fox [and five others] editors
Towards autonomous robot systems : 22nd annual conference, TAROS 2021, Lincoln, UK, September 8-10, 2021 : proceedings / / Charles Fox [and five others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (451 pages)
Disciplina 629.892
Collana Lecture Notes in Computer Science
Soggetto topico Autonomous robots
Artificial intelligence
Machine learning
ISBN 3-030-89177-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Algorithms -- A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning -- 1 Introduction -- 2 Related Work -- 3 Research Methods -- 3.1 Problem Formulation -- 3.2 Rewards -- 3.3 Task Success Classifiers -- 3.4 Training Methodology -- 4 Experiments and Results -- 4.1 Training Tasks -- 4.2 Success Classifiers Results -- 4.3 Experimental Results of the DRL Agents -- 5 Conclusion and Future Work -- References -- An Open-Source Multi-goal Reinforcement Learning Environment for Robotic Manipulation with Pybullet -- 1 Introduction -- 2 Environment -- 2.1 Single-Step Tasks -- 2.2 Multi-step Tasks -- 2.3 APIs and Programming Style -- 3 Benchmark and Discussion -- 3.1 Reproducing Hindsight Experience Replay on Single-Step Tasks -- 3.2 Benchmarking Multi-step Tasks -- 3.3 Challenges and Opportunities -- 4 Conclusion -- References -- CPG-Actor: Reinforcement Learning for Central Pattern Generators -- 1 Introduction -- 1.1 Related Work -- 1.2 Contributions -- 2 Methodology -- 2.1 Differentiable Central Pattern Generators -- 3 Evaluation -- 3.1 Experimental Setup -- 4 Results -- 4.1 CPG-Actor and Previous Baselines, Comparison -- 4.2 Evaluation of Progressive Task Achievement -- 5 Discussion and Future Work -- References -- Deep Semantic Segmentation of 3D Plant Point Clouds -- 1 Introduction -- 2 Related Work -- 2.1 3D Plant Segmentation -- 2.2 Deep Learning for 3D Plant Segmentation -- 2.3 PointNet++ -- 3 Methodology -- 3.1 Data Set -- 3.2 Network Architecture -- 3.3 Performance Metrics -- 3.4 Network Training -- 4 Evaluation -- 4.1 Quantitative Performance Evaluation -- 4.2 Qualitative Performance Evaluation -- 5 Conclusions and Future Work -- References -- Discovering Stable Robot Grasps for Unknown Objects in Presence of Uncertainty Using Bayesian Models -- 1 Introduction -- 2 Related Work.
3 Methodology -- 3.1 Object Extraction from Point Cloud -- 3.2 Grasp Metric Calculation -- 3.3 Probabilistic Modelling -- 4 Implementation -- 4.1 Configuration -- 4.2 Protocol -- 5 Results -- 6 Conclusion -- References -- Improving SLAM in Pipe Networks by Leveraging Cylindrical Regularity -- 1 Introduction -- 2 Related Work -- 3 System Overview -- 4 Cylinder Detection -- 4.1 Cylinder Representation and Estimation -- 4.2 Cylinder Detection -- 5 Bundle Adjustment with Cylindrical Regularity -- 6 Performance Validation and Evaluation -- 6.1 Synthetic Data -- 6.2 Real Data -- 6.3 Discussion -- 7 Conclusion -- References -- CRH*: A Deadlock Free Framework for Scalable Prioritised Path Planning in Multi-robot Systems -- 1 Introduction -- 2 Related Works -- 2.1 Heuristics -- 2.2 Rescheduling -- 2.3 Path Finding -- 3 Design and Development -- 3.1 Overview -- 3.2 A* Adaptations -- 3.3 Framework Facilities -- 4 Experiments -- 4.1 Evaluation of CRH* -- 4.2 Evaluation of Optimisation Improvements -- 5 Conclusion -- References -- Task-Based Ad-hoc Teamwork with Adversary -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Ad-Hoc Teamwork with Adversaries -- 3.2 On-Line Estimators for Ad-hoc Task Allocation with Adversary -- 3.3 OEATA-A Fundamentals -- 3.4 Sets of Estimators -- 3.5 Process of Estimation -- 4 Experiments -- 4.1 Level-Based Foraging Domain -- 4.2 Results -- 5 Conclusion -- References -- Human-Robot Cooperative Lifting Using IMUs and Human Gestures -- 1 Introduction -- 2 Human-Robot Cooperative Lifting Using IMUs and Gestures -- 2.1 Posture and Gesture Estimation -- 2.2 Cooperation Roles and States in Cooperative Lifting -- 2.3 Human-Robot Cooperative Lifting of a Table -- 3 Experimental Setup and Results -- 3.1 Setup -- 3.2 Calibration -- 3.3 Results -- 4 Discussion and Future Work -- 5 Conclusions -- References.
Reinforcement Learning-Based Mapless Navigation with Fail-Safe Localisation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 System Description -- 3.2 Localisation Algorithm -- 3.3 Reinforcement Learning Agent -- 4 Experiments and Results -- 4.1 Experiment Setup -- 4.2 Results -- 5 Conclusion -- References -- Collaborative Coverage for a Network of Vacuum Cleaner Robots -- 1 Introduction -- 2 Method -- 3 Results -- 4 Conclusion -- References -- Network-Aware Genetic Algorithms for the Coordination of MALE UAV Networks -- 1 Introduction -- 2 Problem Description -- 3 Power-Aware Genetic Algorithms -- 4 Network-Aware Genetic Algorithms -- 4.1 Integration with a Network Simulator -- 4.2 Network Topology Evaluation Model -- 5 Experimental Methodology -- 6 Results -- 7 Conclusions -- References -- Self-organised Flocking of Robotic Swarm in Cluttered Environments -- 1 Introduction -- 2 Flocking Method -- 2.1 Active Elastic Sheet Model -- 2.2 Extended AES Model -- 2.3 Metrics -- 2.4 Experimental Setup -- 3 Results and Discussion -- 4 Conclusion -- References -- Evaluating Feedback Modalities in a Mobile Robot for Telecare -- 1 Introduction -- 2 Materials and Methods -- 2.1 The Experimental System -- 2.2 Task -- 2.3 Research Hypotheses -- 2.4 Experimental Design -- 2.5 Dependent Measures -- 2.6 Participants -- 2.7 Procedure -- 2.8 Analysis -- 3 Results -- 3.1 Efficiency -- 3.2 Understanding -- 3.3 Effectiveness -- 3.4 User Perception -- 4 Discussion -- 4.1 Impact of Feedback Modality -- 4.2 Impact of Secondary Task Location -- 5 Conclusions and Future Work -- References -- Demonstrating the Differential Impact of Flock Heterogeneity on Multi-agent Herding -- 1 Introduction -- 1.1 Motivation -- 1.2 Related Work -- 2 Model -- 2.1 Experimental Setup -- 2.2 Sheep Agent Model -- 2.3 Dog Agent Model -- 3 Results -- 4 Conclusions -- References.
Evaluation of an OpenCV Implementation of Structure from Motion on Open Source Data -- 1 Introduction -- 2 Algorithmic Description -- 3 Implementation and Experimental Results -- 4 Comparison -- 5 Conclusions -- References -- Benchmark of Visual and 3D Lidar SLAM Systems in Simulation Environment for Vineyards -- 1 Introduction -- 2 Related Work -- 3 SLAM Algorithms -- 3.1 RTAB-Map -- 3.2 ORB-SLAM2 -- 3.3 LIO-SAM -- 3.4 StaticMapping -- 4 Evaluation -- 4.1 Environment -- 4.2 Testing Scenarios -- 4.3 SLAM Algorithms Configurations -- 4.4 Metrics -- 4.5 Results -- 5 Conclusion -- References -- Lidar-Only Localization with 3D Pose-Feature Map -- 1 Introduction -- 2 Related Work -- 3 Framework Architecture and Background -- 3.1 Framework Architecture -- 3.2 Lidar-Only Odometry Background -- 4 Pose-Feature Map Localization -- 4.1 Pose-Feature Map -- 4.2 Adaptive Local-Map Matching -- 4.3 Integrating Localization -- 5 Experiments -- 5.1 Hardware, Datasets and Parameter Setting -- 5.2 Localization Performance -- 6 Conclusion -- References -- Toward Robust Visual Odometry Using Prior 2D Map Information and Multiple Hypothesis Particle Filtering -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Conclusions -- References -- Comparison of Concentrated and Distributed Compliant Elements in a 3D Printed Gripper -- 1 Introduction -- 2 Compliant Gripper Simulation -- 3 3D Printed Grippers -- 4 Conclusion -- References -- Perception of a Humanoid Robot as an Interface for Auditory Testing -- 1 Introduction -- 2 Experimental Design -- 2.1 Voice Cue Sensitivity -- 2.2 Gender Categorization -- 2.3 Emotion Identification -- 2.4 Speech-on-Speech Perception -- 2.5 Video Analysis -- 3 Further Work -- References -- Deep Learning Traversability Estimator for Mobile Robots in Unstructured Environments -- 1 Introduction -- 2 Traversability Prediction Model -- 2.1 Input Features.
2.2 Network Architecture -- 2.3 Robot Model and Failure Events -- 3 Dataset Generation -- 3.1 OpenSimplex Synthetic Maps Generation -- 3.2 Dataset Collection and Training -- 4 Results -- 4.1 Prediction Performance - Synthetic Dataset -- 4.2 Prediction Performance - Planetary Mission Use Case -- 5 Conclusion and Future Work -- References -- Systems -- Predicting Artist Drawing Activity via Multi-camera Inputs for Co-creative Drawing -- 1 Introduction -- 2 Background -- 3 Research Set-Up -- 4 Drawing Data Gathering Study -- 5 Visual Based Models -- 6 Experiments and Results -- 7 Discussion and Limitations -- 8 Summary and Future Work -- References -- 3D Printed Mechanically Modular Two-Degree-Of-Freedom Robotic Segment Utilizing Variable-Stiffness Actuators -- 1 Introduction -- 2 Design Considerations -- 3 Segment Design -- 4 Control Electronics -- 5 Mechanical Construction -- 6 Position Sensing and Torque Estimation -- 7 Characterizing VSA Dynamics -- 8 Control and Simulation Using ROS -- 9 MATLAB Simulations and Demo -- 10 Discussion -- References -- Design of a Multimaterial 3D-Printed Soft Actuator with Bi-directional Variable Stiffness -- 1 Introduction -- 2 Design and Fabrication of the Actuator -- 3 Control Setup -- 4 Testing -- 5 Conclusion -- References -- Designing a Multi-locomotion Modular Snake Robot -- 1 Introduction -- 2 Proposed Design -- 2.1 Locomotion -- 2.2 Housing -- 2.3 Smart Servos -- 2.4 Biomimetic Snakeskin -- 3 Experiments and Discussion -- 3.1 Prototype 1 - Snakeskin Testing -- 3.2 Prototype 2 - Housing and Smart Servos -- 4 Conclusion -- References -- Deep Robot Path Planning from Demonstrations for Breast Cancer Examination -- 1 Introduction -- 2 Methodology -- 2.1 Data-Set Acquisition -- 2.2 Deep-Model -- 3 Results -- 4 Conclusion -- References.
Priors Inspired by Speed-Accuracy Trade-Offs for Incremental Learning of Probabilistic Movement Primitives.
Record Nr. UNINA-9910508449103321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Towards autonomous robot systems : 22nd annual conference, TAROS 2021, Lincoln, UK, September 8-10, 2021 : proceedings / / Charles Fox [and five others] editors
Towards autonomous robot systems : 22nd annual conference, TAROS 2021, Lincoln, UK, September 8-10, 2021 : proceedings / / Charles Fox [and five others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (451 pages)
Disciplina 629.892
Collana Lecture Notes in Computer Science
Soggetto topico Autonomous robots
Artificial intelligence
Machine learning
ISBN 3-030-89177-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Algorithms -- A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning -- 1 Introduction -- 2 Related Work -- 3 Research Methods -- 3.1 Problem Formulation -- 3.2 Rewards -- 3.3 Task Success Classifiers -- 3.4 Training Methodology -- 4 Experiments and Results -- 4.1 Training Tasks -- 4.2 Success Classifiers Results -- 4.3 Experimental Results of the DRL Agents -- 5 Conclusion and Future Work -- References -- An Open-Source Multi-goal Reinforcement Learning Environment for Robotic Manipulation with Pybullet -- 1 Introduction -- 2 Environment -- 2.1 Single-Step Tasks -- 2.2 Multi-step Tasks -- 2.3 APIs and Programming Style -- 3 Benchmark and Discussion -- 3.1 Reproducing Hindsight Experience Replay on Single-Step Tasks -- 3.2 Benchmarking Multi-step Tasks -- 3.3 Challenges and Opportunities -- 4 Conclusion -- References -- CPG-Actor: Reinforcement Learning for Central Pattern Generators -- 1 Introduction -- 1.1 Related Work -- 1.2 Contributions -- 2 Methodology -- 2.1 Differentiable Central Pattern Generators -- 3 Evaluation -- 3.1 Experimental Setup -- 4 Results -- 4.1 CPG-Actor and Previous Baselines, Comparison -- 4.2 Evaluation of Progressive Task Achievement -- 5 Discussion and Future Work -- References -- Deep Semantic Segmentation of 3D Plant Point Clouds -- 1 Introduction -- 2 Related Work -- 2.1 3D Plant Segmentation -- 2.2 Deep Learning for 3D Plant Segmentation -- 2.3 PointNet++ -- 3 Methodology -- 3.1 Data Set -- 3.2 Network Architecture -- 3.3 Performance Metrics -- 3.4 Network Training -- 4 Evaluation -- 4.1 Quantitative Performance Evaluation -- 4.2 Qualitative Performance Evaluation -- 5 Conclusions and Future Work -- References -- Discovering Stable Robot Grasps for Unknown Objects in Presence of Uncertainty Using Bayesian Models -- 1 Introduction -- 2 Related Work.
3 Methodology -- 3.1 Object Extraction from Point Cloud -- 3.2 Grasp Metric Calculation -- 3.3 Probabilistic Modelling -- 4 Implementation -- 4.1 Configuration -- 4.2 Protocol -- 5 Results -- 6 Conclusion -- References -- Improving SLAM in Pipe Networks by Leveraging Cylindrical Regularity -- 1 Introduction -- 2 Related Work -- 3 System Overview -- 4 Cylinder Detection -- 4.1 Cylinder Representation and Estimation -- 4.2 Cylinder Detection -- 5 Bundle Adjustment with Cylindrical Regularity -- 6 Performance Validation and Evaluation -- 6.1 Synthetic Data -- 6.2 Real Data -- 6.3 Discussion -- 7 Conclusion -- References -- CRH*: A Deadlock Free Framework for Scalable Prioritised Path Planning in Multi-robot Systems -- 1 Introduction -- 2 Related Works -- 2.1 Heuristics -- 2.2 Rescheduling -- 2.3 Path Finding -- 3 Design and Development -- 3.1 Overview -- 3.2 A* Adaptations -- 3.3 Framework Facilities -- 4 Experiments -- 4.1 Evaluation of CRH* -- 4.2 Evaluation of Optimisation Improvements -- 5 Conclusion -- References -- Task-Based Ad-hoc Teamwork with Adversary -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Ad-Hoc Teamwork with Adversaries -- 3.2 On-Line Estimators for Ad-hoc Task Allocation with Adversary -- 3.3 OEATA-A Fundamentals -- 3.4 Sets of Estimators -- 3.5 Process of Estimation -- 4 Experiments -- 4.1 Level-Based Foraging Domain -- 4.2 Results -- 5 Conclusion -- References -- Human-Robot Cooperative Lifting Using IMUs and Human Gestures -- 1 Introduction -- 2 Human-Robot Cooperative Lifting Using IMUs and Gestures -- 2.1 Posture and Gesture Estimation -- 2.2 Cooperation Roles and States in Cooperative Lifting -- 2.3 Human-Robot Cooperative Lifting of a Table -- 3 Experimental Setup and Results -- 3.1 Setup -- 3.2 Calibration -- 3.3 Results -- 4 Discussion and Future Work -- 5 Conclusions -- References.
Reinforcement Learning-Based Mapless Navigation with Fail-Safe Localisation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 System Description -- 3.2 Localisation Algorithm -- 3.3 Reinforcement Learning Agent -- 4 Experiments and Results -- 4.1 Experiment Setup -- 4.2 Results -- 5 Conclusion -- References -- Collaborative Coverage for a Network of Vacuum Cleaner Robots -- 1 Introduction -- 2 Method -- 3 Results -- 4 Conclusion -- References -- Network-Aware Genetic Algorithms for the Coordination of MALE UAV Networks -- 1 Introduction -- 2 Problem Description -- 3 Power-Aware Genetic Algorithms -- 4 Network-Aware Genetic Algorithms -- 4.1 Integration with a Network Simulator -- 4.2 Network Topology Evaluation Model -- 5 Experimental Methodology -- 6 Results -- 7 Conclusions -- References -- Self-organised Flocking of Robotic Swarm in Cluttered Environments -- 1 Introduction -- 2 Flocking Method -- 2.1 Active Elastic Sheet Model -- 2.2 Extended AES Model -- 2.3 Metrics -- 2.4 Experimental Setup -- 3 Results and Discussion -- 4 Conclusion -- References -- Evaluating Feedback Modalities in a Mobile Robot for Telecare -- 1 Introduction -- 2 Materials and Methods -- 2.1 The Experimental System -- 2.2 Task -- 2.3 Research Hypotheses -- 2.4 Experimental Design -- 2.5 Dependent Measures -- 2.6 Participants -- 2.7 Procedure -- 2.8 Analysis -- 3 Results -- 3.1 Efficiency -- 3.2 Understanding -- 3.3 Effectiveness -- 3.4 User Perception -- 4 Discussion -- 4.1 Impact of Feedback Modality -- 4.2 Impact of Secondary Task Location -- 5 Conclusions and Future Work -- References -- Demonstrating the Differential Impact of Flock Heterogeneity on Multi-agent Herding -- 1 Introduction -- 1.1 Motivation -- 1.2 Related Work -- 2 Model -- 2.1 Experimental Setup -- 2.2 Sheep Agent Model -- 2.3 Dog Agent Model -- 3 Results -- 4 Conclusions -- References.
Evaluation of an OpenCV Implementation of Structure from Motion on Open Source Data -- 1 Introduction -- 2 Algorithmic Description -- 3 Implementation and Experimental Results -- 4 Comparison -- 5 Conclusions -- References -- Benchmark of Visual and 3D Lidar SLAM Systems in Simulation Environment for Vineyards -- 1 Introduction -- 2 Related Work -- 3 SLAM Algorithms -- 3.1 RTAB-Map -- 3.2 ORB-SLAM2 -- 3.3 LIO-SAM -- 3.4 StaticMapping -- 4 Evaluation -- 4.1 Environment -- 4.2 Testing Scenarios -- 4.3 SLAM Algorithms Configurations -- 4.4 Metrics -- 4.5 Results -- 5 Conclusion -- References -- Lidar-Only Localization with 3D Pose-Feature Map -- 1 Introduction -- 2 Related Work -- 3 Framework Architecture and Background -- 3.1 Framework Architecture -- 3.2 Lidar-Only Odometry Background -- 4 Pose-Feature Map Localization -- 4.1 Pose-Feature Map -- 4.2 Adaptive Local-Map Matching -- 4.3 Integrating Localization -- 5 Experiments -- 5.1 Hardware, Datasets and Parameter Setting -- 5.2 Localization Performance -- 6 Conclusion -- References -- Toward Robust Visual Odometry Using Prior 2D Map Information and Multiple Hypothesis Particle Filtering -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Conclusions -- References -- Comparison of Concentrated and Distributed Compliant Elements in a 3D Printed Gripper -- 1 Introduction -- 2 Compliant Gripper Simulation -- 3 3D Printed Grippers -- 4 Conclusion -- References -- Perception of a Humanoid Robot as an Interface for Auditory Testing -- 1 Introduction -- 2 Experimental Design -- 2.1 Voice Cue Sensitivity -- 2.2 Gender Categorization -- 2.3 Emotion Identification -- 2.4 Speech-on-Speech Perception -- 2.5 Video Analysis -- 3 Further Work -- References -- Deep Learning Traversability Estimator for Mobile Robots in Unstructured Environments -- 1 Introduction -- 2 Traversability Prediction Model -- 2.1 Input Features.
2.2 Network Architecture -- 2.3 Robot Model and Failure Events -- 3 Dataset Generation -- 3.1 OpenSimplex Synthetic Maps Generation -- 3.2 Dataset Collection and Training -- 4 Results -- 4.1 Prediction Performance - Synthetic Dataset -- 4.2 Prediction Performance - Planetary Mission Use Case -- 5 Conclusion and Future Work -- References -- Systems -- Predicting Artist Drawing Activity via Multi-camera Inputs for Co-creative Drawing -- 1 Introduction -- 2 Background -- 3 Research Set-Up -- 4 Drawing Data Gathering Study -- 5 Visual Based Models -- 6 Experiments and Results -- 7 Discussion and Limitations -- 8 Summary and Future Work -- References -- 3D Printed Mechanically Modular Two-Degree-Of-Freedom Robotic Segment Utilizing Variable-Stiffness Actuators -- 1 Introduction -- 2 Design Considerations -- 3 Segment Design -- 4 Control Electronics -- 5 Mechanical Construction -- 6 Position Sensing and Torque Estimation -- 7 Characterizing VSA Dynamics -- 8 Control and Simulation Using ROS -- 9 MATLAB Simulations and Demo -- 10 Discussion -- References -- Design of a Multimaterial 3D-Printed Soft Actuator with Bi-directional Variable Stiffness -- 1 Introduction -- 2 Design and Fabrication of the Actuator -- 3 Control Setup -- 4 Testing -- 5 Conclusion -- References -- Designing a Multi-locomotion Modular Snake Robot -- 1 Introduction -- 2 Proposed Design -- 2.1 Locomotion -- 2.2 Housing -- 2.3 Smart Servos -- 2.4 Biomimetic Snakeskin -- 3 Experiments and Discussion -- 3.1 Prototype 1 - Snakeskin Testing -- 3.2 Prototype 2 - Housing and Smart Servos -- 4 Conclusion -- References -- Deep Robot Path Planning from Demonstrations for Breast Cancer Examination -- 1 Introduction -- 2 Methodology -- 2.1 Data-Set Acquisition -- 2.2 Deep-Model -- 3 Results -- 4 Conclusion -- References.
Priors Inspired by Speed-Accuracy Trade-Offs for Incremental Learning of Probabilistic Movement Primitives.
Record Nr. UNISA-996464390103316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Towards autonomous robotic systems : 23rd annual conference, TAROS 2022, Culham, UK, September 7-9, 2022, proceedings / / Salvador Pacheco-Gutierrez [and four others], editors
Towards autonomous robotic systems : 23rd annual conference, TAROS 2022, Culham, UK, September 7-9, 2022, proceedings / / Salvador Pacheco-Gutierrez [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Descrizione fisica 1 online resource (333 pages)
Disciplina 629.892
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Human-robot interaction
Autonomous robots
Machine learning
ISBN 3-031-15908-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910591031203321
Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Towards autonomous robotic systems : 23rd annual conference, TAROS 2022, Culham, UK, September 7-9, 2022, proceedings / / Salvador Pacheco-Gutierrez [and four others], editors
Towards autonomous robotic systems : 23rd annual conference, TAROS 2022, Culham, UK, September 7-9, 2022, proceedings / / Salvador Pacheco-Gutierrez [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Descrizione fisica 1 online resource (333 pages)
Disciplina 629.892
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Human-robot interaction
Autonomous robots
Machine learning
ISBN 3-031-15908-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996490367303316
Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Towards Heterogeneous Multi-Core Systems-on-Chip for Edge Machine Learning : Journey from Single-Core Acceleration to Multi-core Heterogeneous Systems / / Vikram Jain and Marian Verhelst
Towards Heterogeneous Multi-Core Systems-on-Chip for Edge Machine Learning : Journey from Single-Core Acceleration to Multi-core Heterogeneous Systems / / Vikram Jain and Marian Verhelst
Autore Jain Vikram
Edizione [First edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2024]
Descrizione fisica 1 online resource (199 pages)
Disciplina 005.758
Soggetto topico Edge computing
Machine learning
Systems on a chip - Design and construction
ISBN 3-031-38230-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- List of Abbreviations -- List of Figures -- List of Tables -- 1 Introduction -- 1.1 Machine Learning at the (Extreme) Edge -- 1.1.1 Applications -- 1.1.2 Algorithms -- 1.1.3 Hardware -- 1.2 Open Challenges for ML Acceleration at the (Extreme) Edge -- 1.3 Book Contributions -- 2 Algorithmic Background for Machine Learning -- 2.1 Support Vector Machines -- 2.2 Deep Learning Models -- 2.2.1 Neural Networks -- 2.2.2 Training -- 2.2.3 Inference: Neural Network Topologies -- 2.2.4 Model Compression -- 2.3 Feature Extraction -- 2.4 Conclusion -- 3 Scoping the Landscape of (Extreme) Edge Machine Learning Processors -- 3.1 Hardware Acceleration of ML Workloads: A Primer -- 3.1.1 Core Mathematical Operation -- 3.1.2 General Accelerator Template -- 3.2 Evaluation Metrics -- 3.3 Survey of (Extreme) Edge ML Hardware Platforms -- 3.4 Evaluating the Surveyed Hardware Platforms -- 3.5 Insights and Trends -- 3.6 Conclusion -- 4 Hardware-Software Co-optimization Through Design Space Exploration -- 4.1 Motivation -- 4.2 Exploration Methodology -- 4.2.1 ZigZag -- 4.2.2 Post-Processing of ZigZag's Results -- 4.3 DNN Workload Comparison -- 4.3.1 Exploration Setup -- 4.3.2 Visualization of the Complete Trade-Off Space -- 4.3.3 Impact of HW Architecture on Optimal Workload -- 4.3.4 Impact of Workload on Optimal HW Architecture -- 4.4 Conclusion -- 5 Energy-Efficient Single-Core Hardware Acceleration -- 5.1 Motivation -- 5.2 Metrics for Hardware Optimization -- 5.3 State-of-the-Art in Object Detection on FPGA -- 5.4 Cost-Aware Algorithmic Optimization -- 5.4.1 Object Detection Algorithms -- 5.4.2 Quantization of Tiny-YOLOv2 -- Post-training Quantization -- Quantization-Aware Training -- 5.5 Cost-Aware Architecture Optimization -- 5.5.1 Hardware Mapping of Convolutional Layers.
5.5.2 Hardware Architecture of the Accelerator -- 5.6 Cost-Aware System Optimization -- 5.6.1 Data Communication Architecture -- 5.6.2 Tiling Strategy -- 5.7 Implementation Results -- 5.8 Conclusion -- 6 TinyVers: A Tiny Versatile All-Digital Heterogeneous Multi-core System-on-Chip -- 6.1 Motivation -- 6.2 Algorithmic Background -- 6.2.1 Convolution and Dense Operation -- 6.2.2 Deconvolution -- 6.2.3 Support Vector Machines (SVMs) -- 6.3 TinyVers Hardware Architecture -- 6.3.1 Smart Sensing Modes for TinyML -- 6.3.2 Power Management -- 6.4 FlexML Accelerator -- 6.4.1 FlexML Architecture Overview -- 6.4.2 Dataflow Reconfiguration -- 6.4.3 Efficient Zero-Skipping for Deconvolution and Blockwise Structured Sparsity -- 6.4.4 Support Vector Machine -- 6.5 Deployment of Neural Networks on TinyVers -- 6.6 Design for Test and Fault-Tolerance -- 6.7 Chip Implementation and Measurement -- 6.7.1 Peak Performance Analysis -- 6.7.2 Workload Benchmarks -- 6.7.3 Power Management -- 6.7.4 Instantaneous Power Trace -- Keyword Spotting Application -- Machine Monitoring Application -- 6.8 Comparison with SotA -- 6.9 Conclusion -- 7 DIANA: DIgital and ANAlog Heterogeneous Multi-core System-on-Chip -- 7.1 Motivation -- 7.2 Design Choices -- 7.2.1 Dataflow Concepts -- 7.2.2 Design Space Exploration -- 7.2.3 A Reconfigurable Heterogeneous Architecture -- 7.2.4 Optimization Strategies for Multi-core -- 7.3 System Architecture -- 7.3.1 The RISC-V CPU and Network Control -- 7.3.2 Memory System -- 7.4 AIMC Computing Core -- 7.4.1 AIMC Core Microarchitecture -- 7.4.2 Memory Control Unit (MCU) -- 7.4.3 AIMC Macro -- 7.4.4 Output Buffer and SIMD Unit -- 7.5 Digital DNN Accelerator -- 7.6 Measurements -- 7.6.1 Efficiency vs. Accuracy Trade-Off in the Analog Macro -- 7.6.2 Peak Performance and Efficiency Characterization -- 7.6.3 Workload Performance Characterization.
7.6.4 SotA Comparison -- 7.7 Conclusion -- 8 Networks-on-Chip to Enable Large-Scale Multi-core ML Acceleration -- 8.1 Motivation -- 8.2 Background -- 8.2.1 Network-on-Chips -- 8.2.2 AXI Protocol -- Burst -- Multiple Outstanding Transaction -- 8.3 Interconnect Architecture of PATRONoC -- 8.4 Implementation Results -- 8.5 Performance Evaluation -- 8.5.1 Uniform Random Traffic -- 8.5.2 Synthetic Traffic -- 8.5.3 DNN Workload Traffic -- 8.6 Related Work -- 8.7 Conclusion -- 9 Conclusion -- 9.1 Overview and Contributions -- 9.2 Suggestions for Future Work -- 9.2.1 The Low Hanging Fruits -- 9.2.2 Medium Term -- 9.2.3 Moonshot -- 9.3 Closing Remarks -- References -- References -- Index.
Record Nr. UNINA-9910760277003321
Jain Vikram  
Cham, Switzerland : , : Springer, , [2024]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Towards Net-Zero Targets : Usage of Data Science for Long-Term Sustainability Pathways / / by Neha Sharma, Prithwis Kumar De
Towards Net-Zero Targets : Usage of Data Science for Long-Term Sustainability Pathways / / by Neha Sharma, Prithwis Kumar De
Autore Sharma Neha (Of Tufts University. School of Medicine)
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (258 pages)
Disciplina 363.73874561
Collana Advances in Sustainability Science and Technology
Soggetto topico Computational intelligence
Sustainability
Artificial intelligence
Artificial intelligence - Data processing
Machine learning
Computational Intelligence
Artificial Intelligence
Data Science
Machine Learning
ISBN 981-19-5244-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. Climate Change and AI in the Financial, Energy, Domestic and Transport Sectors -- Chapter 2. Role of Banking Sector in Climate Change – Literature Review and Data Preparation -- Chapter 3. Application of Machine Learning to Predict Climate Change Consequences due to Investments by Banks in Fossil Fuel Sectors -- Chapter 4. Effect of Non-Renewable Energy Sources on Climate Change in India- Literature Review and Data Preparation -- Chapter 5. Using Machine Learning to Predict the Effect of Non-Renewable Energy Sources on Climate Change in India -- Chapter 6. Impact of Household Emissions on Climate Change in India – Literature Review and Data Preparation -- Chapter 7. Use of Unsupervised Learning Algorithms to Segment Indian States based on Primary Energy Household Emissions -- Chapter 8. Application of Machine Learning in Climate Change for Transport Sector – Literature Review and Data Preparation -- Chapter 9. Application of Machine Learning to Predict CO2 Emission from Transport Sector to Mitigate Climate Change -- Chapter 10. Carbon Emission Calculator: Impact of AI on Climate Change.
Record Nr. UNINA-9910627259203321
Sharma Neha (Of Tufts University. School of Medicine)  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Training knowledge bots for physics-based simulations using artificial neurals networks / / Jay Ming Wong, Jamshid A. Samareh
Training knowledge bots for physics-based simulations using artificial neurals networks / / Jay Ming Wong, Jamshid A. Samareh
Autore Wong Jay Ming
Pubbl/distr/stampa Hampton, Virginia : , : National Aeronautics and Space Administration, Langley Research Center, , November 2014
Descrizione fisica 1 online resource (13 pages) : color illustrations
Collana NASA/TM
Soggetto topico Neural nets
Machine learning
Computational fluid dynamics
Artificial intelligence
Trajectory analysis
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910703731403321
Wong Jay Ming  
Hampton, Virginia : , : National Aeronautics and Space Administration, Langley Research Center, , November 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Transactional machine learning with data streams and AutoML : build frictionless and elastic machine learning solutions with Apache Kafka in the cloud using Python / / Sebastian Maurice
Transactional machine learning with data streams and AutoML : build frictionless and elastic machine learning solutions with Apache Kafka in the cloud using Python / / Sebastian Maurice
Autore Maurice Sebastian
Edizione [1st ed. 2021.]
Pubbl/distr/stampa [Place of publication not identified] : , : Apress, , [2021]
Descrizione fisica 1 online resource (XV, 276 p. 36 illus.)
Disciplina 006.31
Soggetto topico Machine learning
ISBN 1-4842-7023-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1: Introduction: Big data, Auto Machine Learning and Data Streams -- Chapter 2: Transactional Machine Learning -- Chapter 3: Industry Challenges with Data Streams and AutoML -- Chapter 4: The Business Value of Transactional Machine Learning -- Chapter 5: The Technical Components and Architecture for Transactional Machine Learning -- Overview of a TML Solution -- Chapter 6: Template for Transactional Machine Learning Solutions -- CHAPTER 7: Visualize Your TML Model Insights: Optimization, Predictions and Anomalies -- Chapter 8: Evolution and Opportunities For Transactional Machine Learning in Almost Every Industry -- Chapter 9: Conclusion and Final Thoughts.
Record Nr. UNINA-9910484862803321
Maurice Sebastian  
[Place of publication not identified] : , : Apress, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Transactions on Computational Science XL [[electronic resource] /] / edited by Marina Gavrilova, C. J. Kenneth Tan, Mark Coates, Yaoping Hu, Henry Leung, Arash Mohammadi, Konstantinos N. Plataniotis, Helder Rodrigues de Oliveira
Transactions on Computational Science XL [[electronic resource] /] / edited by Marina Gavrilova, C. J. Kenneth Tan, Mark Coates, Yaoping Hu, Henry Leung, Arash Mohammadi, Konstantinos N. Plataniotis, Helder Rodrigues de Oliveira
Autore Gavrilova Marina
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (137 pages)
Disciplina 003.3
Altri autori (Persone) TanC. J. Kenneth
CoatesMark
HuYaoping
LeungHenry
MohammadiArash
PlataniotisKonstantinos N
de OliveiraHelder Rodrigues
Collana Transactions on Computational Science
Soggetto topico Mathematics - Data processing
Numerical analysis
Algorithms
Pattern recognition systems
Machine learning
Computers, Special purpose
Computational Science and Engineering
Numerical Analysis
Design and Analysis of Algorithms
Automated Pattern Recognition
Machine Learning
Special Purpose and Application-Based Systems
ISBN 3-662-67868-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Trustworthy Technologies for Autonomous Human-Machine Systems -- Challenges in Understanding Trust and Trust Modeling: Quenching the Thirst for AI Trust Management -- Stress Contagion Protocols for Human-Autonomy Teaming -- AVCA: Autonomous Virtual Cognitive Assessment -- Light-weighted CNN-Attention based Architecture Trained with a Hybrid Objective Function for EMG-based Human Machine Interfaces -- Fairness, Bias and Trust in the Context of Biometric-enabled Autonomous Decision Support -- An Autonomous Fake News Recognition System by Semantic Learning in Cognitive Computing -- Addressing Dataset Shift for Trustworthy Deep Learning Diagnostic Ultrasound Decision Support.
Record Nr. UNISA-996546851603316
Gavrilova Marina  
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui