Matsuno / Liu / Yin | Intelligent Robotics and Applications | Buch | 978-981-952094-7 | sack.de

Buch, Englisch, 614 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 961 g

Reihe: Lecture Notes in Artificial Intelligence

Matsuno / Liu / Yin

Intelligent Robotics and Applications

18th International Conference, ICIRA 2025, Okayama, Japan, August 6-9, 2025, Proceedings, Part I
Erscheinungsjahr 2025
ISBN: 978-981-952094-7
Verlag: Springer

18th International Conference, ICIRA 2025, Okayama, Japan, August 6-9, 2025, Proceedings, Part I

Buch, Englisch, 614 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 961 g

Reihe: Lecture Notes in Artificial Intelligence

ISBN: 978-981-952094-7
Verlag: Springer


The 3-volume set, LNAI 16074-16076, constitutes the proceedings of the 18th International Conference on Intelligent Robotics and Applications, ICIRA 2025, which took place in Okayama, Japan, during August 6-9, 2025.

The 165 full papers included in these proceedings were carefully reviewed and selected from 329 submissions.

They were organized in topical sections as follows: 

Part 1: Robotic Dexterous Manipulation and Intelligent Control; Intelligent Perception and Control Technologies for Marine Robotic Systems; Intelligent Technology in Neural Decoding, Modulation, and Interfacing; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Soft Robotics.

Part 2: Hand-Centric Human-Robot Collaboration Advances in Perception, Control, and Interaction; Intelligent Technology in Healthcare; Advanced Localization, Navigation and Control Technologies in Intelligent Robotic Systems; Wearable Robotics for Gait Analysis, Training, and Rehabilitation; Embodied Intelligence in Biomimetic Robotics, Humanoid Robotics.

Part 3: Magnetic Actuated Microrobots for Biomedical Engineering:Design, Control, and Application; Innovative Design and Performance Evaluation of Robot Mechanisms; Sensation-Perception-Actuation-Rehabilitation Oriented Technologies for Wearable Exoskeletons; Pattern Analysis and Machine Intelligence: Vision, Language, Multimodal Learning, and Applications; Bio-mechatronic Integration and Rehabilitation Robots.

Matsuno / Liu / Yin Intelligent Robotics and Applications jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


.- Robotic Dexterous Manipulation and Intelligent Control.

.- A Physics-informed Neural Network-based Momentum Observer Considering Velocity Effects for Contact Force Estimation in Industrial Robots.

.- A High-Precision and Compliant Interaction Method forRobot Based on Model Predictive Impedance Control.

.- Dynamics Modeling and Vibration Suppression of Industrial Robots Handling Flexible Payloads.

.- Dual-Channel Adaptive Impedance Algorithm with Leveling Module in Dual-Arm Collaborative Robots.

.- RL-Force: Reinforcement Learning with Force  Estimation for Humanoid Locomotion Subject to  Continuous External Disturbances.

.- Intrinsic Vision-Based Learning for Proprioceptive Sensing of Soft Pneumatic Actuators.

.- Visual-Guided Diffusion Policy and Mesh-DMP Integration for Robotic Freeform Surface Polishing.

.- Boosting Industrial Changeover Efficiency: A Large-Model-Based Explore-Then-Reproduce Framework for Changeover Tasks.

.- Learning Human-like Finger Gaiting on an Anthropomorphic Hand.

.- Learning Stable Nonlinear Dynamical Systems With Symmetric Negative Definite Matrix Generation Network.

.- Object's CoM-Aware Pose Optimization of Humanoid  Upperlimbs for Dual-Arm Collaborative Carrying.

.- Contact Driven Functional Grasp Synthesis via Hand-Object Interaction State Representation.

.- Intelligent Perception and Control Technologies for Marine Robotic Systems.

.- Co-Simulation of Trajectory Tracking Control for Underwater Vehicles: A Case Study on RexROV Using Simulink and UUV Simulator.

.- An Elastodynamic Modeling Approach on Component Mode Synthesis for Hybrid Machining Cell.

.- Safety-Critical Flocking Control of Multiple Unmanned Surface Vehicles Based on Exponential Control Barrier Functions.

.- Research on hybrid buoy inclined landing motion control.

.- Fast and Automatic Dock for Precise UAV Landing on a USV in Marine Environment.

.- Positioning and Orientation for Single LiDAR of USVs Obstructed By Offshore Operation Platform.

.- A Fault Diagnosis Scheme for Underwater Thrusters Considering Sensor Faults.

.- Bio-Inspired Soft Robotic Arms Capable of Object Grasping and Bipedal Locomotion in Amphibious Environments.

.- Position Compensation Method for Cable-Pulling Robot in Generator Maintenance without Rotor Removal.

.- Intelligent Technology in Neural Decoding, Modulation, and Interfacing.

.- Research on Pose Control Dataset Augmentation Method Based on Generative Adversarial Networks.

.- Optimal Electrode Configuration for Wrist sEMG-Based Gesture Recognition:
A Systematic Evaluation of Number and Placement.

.- Robotic Grinding of Thin-Walled Parts: Reinforcement Learning-Based Chatter Suppression Method.

.- Electrode shift-robust decomposition of surface EMG signals via deep learning: A simulation study.

.- Enhancing Softness Discrimination in Vision-Based Tactile Sensors via Modeling and Optimization of Gradient-Stiffness Elastomers.

.- Filtering Selection for High-density sEMG in Motor Unit Decomposition.

.- Sensory Input Shapes Motor Output: Decoding Corticomuscular Coherence under Vibration-Induced Modulation.

.- Adaptive Network Design for SSVEP/SSMVEP Classi?cation via SE and Con?gurable Convolutions.

.- Multimodal Assessment of Visual-Motor Integration in Attention Deffcit/Hyperactivity Disorder.

.- Comparison of Propagation and Activation Characteristics of Motor Units Decomposed from Wrist and Forearm Surface Electromyography Signals.

.- High-Discrimination Multi-Level Electrotactile Feedback via Compound PerceptionDescriptors and Efficient Calibration.

.- Cross-Task EEG Mental Workload Detection in Aviation: An LSTM Framework Leveraging Task-Invariant Neural Signatures.

.- Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements.

.- A Physiology-Informed Training Protocol for Cross-Paradigm Transfer Learning in ErrP-based Brain-Computer Interface.

.- Design and Implementation of Thermoplastic Composite Robotic Winding System.

.- A Stretchable Resistive Electronic Skin for Shape Sensing of End Continua of Flexible Surgical Instruments.

.- An Intelligent Process Decision-Making Method for Robotic Grinding Random Defects via Incremental Learning and Database.

.- Knee Prosthesis Stair Ascending with Adaptive Clearance and Foot Placement.

.- A Hybrid FES-Soft Exosuit System to Improve Interlimb Symmetry in Post-Stroke Patients.

.- Digital Twin Modeling and Performance Evaluation of a Gimbal Servo System.

.- Kinematics Modeling and Calibration of a Continuum Manipulator Considering Nonconstant Elasticity.

.- Predictive Modeling of Robot Deformation Errors via Incremental Learning.

.- Soft Robotics.

.- Design and Analysis of a Morphing Wing Based on Corrugated-honeycomb Structure for UAV.

.- Design and Analysis of a Novel Metamaterial with Tunable Coefficient of Thermal Expansion.

.- Neural Implicit Embedded PWM Control Approach for Dielectric Elastomer Actuators with Rate-Dependent Viscoelasticity.

.- Design of a Rigid–Elastic–Soft Coupled DELTA Mechanism with Variable Cartesian Stiffness.

.- Pneumatic kirigami actuators with programmable motion for versatile robotic functionalities.

.- Stress Monitoring and Adaptive Grasping forRobotic Grippers Using Distributed Optical Fiber Sensing.

.- Radial Basis Function Neural Network-Based Adaptive Trajectory Tracking Control for Continuum Robots.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.