Intelligent Robotics and Applications

The 10-volume set LNAI 15201-15210 constitutes the proceedings of the 17th International Conference on Intelligent Robotics and Applications, ICIRA 2024, which took place in Xi'an, China, during July 31August 2, 2024.

The 321 full papers included in these proceedings were carefully reviewed and selected from 489 submissions.

They were organized in topical sections as follows:

Part I: Innovative Design and Performance Evaluation of Robot Mechanisms.

Part II: Robot Perception and Machine Learning; Cognitive Intelligence and Security Control for Multi-domain Unmanned Vehicle Systems.

Part III: Emerging Techniques for Intelligent Robots in Unstructured Environment; Soft Actuators and Sensors; and Advanced Intelligent and Flexible Sensor Technologies for Robotics.

Part IV: Optimization and Intelligent Control of Underactuated Robotic Systems; and Technology and application of modular robots.

Part V: Advanced actuation and intelligent control in medical robotics: Advancements in Machine Vision for Enhancing Human-Robot Interaction; and Hybrid Decision-making and Control for Intelligent Robots.

Part VI: Advances in Marine Robotics; Visual, Linguistic, Affective Agents: Hybrid-augmented Agents for Robotics; and Wearable Robots for Assistance, Augmentation and Rehabilitation of human movements.

Part VII: Integrating World Models for Enhanced Robotic Autonomy; Advanced Sensing and Control Technologies for Intelligent Human-Robot Interaction; and Mini-Invasive Robotics for In-Situ Manipulation.

Part VIII: Robot Skill Learning and Transfer; Human-Robot Dynamic System: Learning, Modelling and Control; AI-Driven Smart Industrial Systems; and Natural Interaction and Coordinated Collaboration of Robots in Dynamic Unstructured Environments.

Part IX: Robotics in Cooperative Manipulation, MultiSensor Fusion, and Multi-Robot Systems; Human-machine Co-adaptive Interface; Brain inspired intelligence for robotics; Planning, control and application of bionic novel concept robots; and Robust Perception for Safe Driving.

Part X: AI Robot Technology for Healthcare as a Service; Computational Neuroscience and Cognitive Models for Adaptive Human-Robot Interactions; Dynamics and Perception of Human-Robot Hybrid Systems; and Robotics for Rehabilitation: Innovations, Challenges, and Future Directions.

Contenu

.- Robot Perception and Machine Learning.
.- Sparse representation of robotic machining deformation based on key points determination.
.- A Cross-media Localization Method for Amphibious Climbing Robot.
.- YOWOv2: A Stronger yet Efffcient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection.
.- Double Barrier Function Based Mutual Collision Avoidance Motion Planning Scheme Synthesized by Varying-parameter Neural Network for Redundant Dual Manipulators.
.- Multi-Scale Topology of Residual Network for Haze Removal.
.- Multi-task Heterogeneous Framework for Semi-supervised Medical Image Segmentation.
.- GI-Grasp: Target-Oriented 6DoF Grasping Strategy with Grasp Intuition Based on Vision-Language Models.
.- S2NeRF: Neural Radiance Fields Training with Sparse Points and Sparse Views.
.- Person Re-identiffcation with Multi-stage Channel Feature Aggregation.
.- Semi-Supervised Underwater Object Detection Using Grid Marker-Assisted Image Enhancement.
.- Modality Mitigation And Diverse Part Awareness for Visible-Infrared Person Re-identiffcation.
.- Binocular Reconstruction and Monocular 6Dof Pose Estimation for Model Free Robot Grasping.
.- Mip-NeRF+: Multi-Scale 3D Scene Synthesis.
.- StereoNeRF: Learning Radiance Fields from Stereo Observation for Driving View Synthesis.
.- Person Re-Identification Based on Random Occlusion for Local Feature Fusion.
.- MDLIRE-Net: Semantic Segmentation of Point Clouds Based on Multidimensional Local Information Reencoding.
.- Trajectory prediction method of flying uneven object based on improved Informer.
.- Error Propagation Mechanism for the 2.5-D Grid Map Update in LiDAR Gaze Control Applications for Omni-directional Wheeled Robots.
.- EMFIR: Efficient Dense Magnetic Field Mapping Based on Implicit Representation.
.- MFap: Multi-view Feature Map for Visual Localization.
.- Cognitive Intelligence and Security Control for Multi-domain Unmanned Vehicle Systems.
.- Research on the Method of Trajectory Planning for Unmanned Aerial Vehicles in Complex Terrains Based on Reinforcement Learning.
.- Research on functional safety-oriented supercapacitor vehicle-mounted low-voltage power supply system for new energy vehicles.
.- Application of Stroke Extraction and Trajectory Planning in Robotic Calligraphy.
.- Efficient Autonomous Exploration of Complex Environments Based on the Mobile Robot.
.- Distributed Formation Coordinated Control of Multiple Unmanned Surface Vehicles Based on Deep Reinforcement Learning.
.- A Hybrid Control Model for Platoons at Mixed-trafffc Freeways Based on Deep Reinforcement Learning.
.- Collision-Free Time-Varying Formation Control via Relative Localization.
.- Design of Human-Machine Collaborative Assembly System based on Reconfigurable Processes.
.- A Survey on Detecting Foreign Objects on Transmission Lines Based on UAV Images.
.- Homogeneous Multi-Robot Patrolling Based on Humanoid Formation Configuration.
.- All-in-one Image Restoration in Adverse Weather Conditions with Spatial-Frequency Domain Information.
.- Distributed Adaptive Control of Multiple Robots for Cooperative Load Transportation.
.- Research on Multi UAV Algorithm Based on Evolutionary Reinforcement learning.