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Found 30 papers, 0 papers with code
Distributed Robust Learning based Formation Control of Mobile Robots based on Bioinspired Neural Dynamics
This paper addresses the challenges of distributed formation control in multiple mobile robots, introducing a novel approach that enhances real-world practicability.
A Novel Feature Learning-based Bio-inspired Neural Network for Real-time Collision-free Rescue of Multi-Robot Systems
In this paper, a feature learning-based bio-inspired neural network (FLBBINN) is proposed to quickly generate a heuristic rescue path in complex and dynamic environments, as traditional approaches usually cannot provide a satisfactory solution to real-time responses to sudden environmental changes.
Intelligent Collective Escape of Swarm Robots Based on a Novel Fish-inspired Self-adaptive Approach with Neurodynamic Models
Fish schools present high-efficiency group behaviors through simple individual interactions to collective migration and dynamic escape from the predator.
Current Effect-eliminated Optimal Target Assignment and Motion Planning for a Multi-UUV System
In addition, a critical innovation within the CBNNTAP algorithm is its capacity to address the disruptive effects of ocean currents, where an adjustment component is seamlessly integrated to counteract the deviations caused by these currents, which enhances the accuracy of both motion planning and target assignment for the UUVs.
Intelligent Escape of Robotic Systems: A Survey of Methodologies, Applications, and Challenges
As the emphasis on safety becomes increasingly paramount and advancements in robotic technologies continue to advance, a wide range of intelligent escape methodologies has been developed in recent years.
Distributed Neurodynamics-Based Backstepping Optimal Control for Robust Constrained Consensus of Underactuated Underwater Vehicles Fleet
Robust constrained formation tracking control of underactuated underwater vehicles (UUVs) fleet in three-dimensional space is a challenging but practical problem.
Distributed Robust Learning-Based Backstepping Control Aided with Neurodynamics for Consensus Formation Tracking of Underwater Vessels
This paper addresses distributed robust learning-based control for consensus formation tracking of multiple underwater vessels, in which the system parameters of the marine vessels are assumed to be entirely unknown and subject to the modeling mismatch, oceanic disturbances, and noises.
Distributed Leader Follower Formation Control of Mobile Robots based on Bioinspired Neural Dynamics and Adaptive Sliding Innovation Filter
This paper investigated the distributed leader follower formation control problem for multiple differentially driven mobile robots.
Optimal Scheduling in IoT-Driven Smart Isolated Microgrids Based on Deep Reinforcement Learning
In this paper, we investigate the scheduling issue of diesel generators (DGs) in an Internet of Things (IoT)-Driven isolated microgrid (MG) by deep reinforcement learning (DRL).
A GOA-Based Fault-Tolerant Trajectory Tracking Control for an Underwater Vehicle of Multi-Thruster System without Actuator Saturation
This paper proposes an intelligent fault-tolerant control (FTC) strategy to tackle the trajectory tracking problem of an underwater vehicle (UV) under thruster damage (power loss) cases and meanwhile resolve the actuator saturation brought by the vehicle's physical constraints.
Broad Learning System with Takagi-Sugeno Fuzzy Subsystem for Tobacco Origin Identification based on Near Infrared Spectroscopy
In this paper, a novel broad learning system with Takagi-Sugeno (TS) fuzzy subsystem is proposed for rapid identification of tobacco origin.
Intelligent Feature Extraction, Data Fusion and Detection of Concrete Bridge Cracks: Current Development and Challenges
As a common appearance defect of concrete bridges, cracks are important indices for bridge structure health assessment.
Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks
Traditional machine learning techniques have been widely used to establish the trust management systems.
A Fuzzy Logic-based Cascade Control without Actuator Saturation for the Unmanned Underwater Vehicle Trajectory Tracking
An intelligent control strategy is proposed to eliminate the actuator saturation problem that exists in the trajectory tracking process of unmanned underwater vehicles (UUV).
A Novel Knowledge-Based Genetic Algorithm for Robot Path Planning in Complex Environments
In this paper, a novel knowledge-based genetic algorithm for path planning of a mobile robot in unstructured complex environments is proposed, where five problem-specific operators are developed for efficient robot path planning.
A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics
In comparative studies, the proposed combined hybrid control strategy has ensured control signals smoothness, which is critical in real world applications, especially for an unmanned underwater vehicle that needs to operate in complex underwater environments.
Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks
Next, the integration of AI and trust management is developed to optimize the intelligence and security.
Rapid-Flooding Time Synchronization for Large-Scale Wireless Sensor Networks
Accurate and fast-convergent time synchronization is very important for wireless sensor networks.
Fast Convergence Time Synchronization in Wireless Sensor Networks Based on Average Consensus
Based on the suggestion that the greater the algebraic connectivity leads to the faster the convergence, a novel multi-hop average consensus time synchronization (MACTS) is developed with innovative implementation in this paper.
Novel Maximum Likelihood Estimation of Clock Skew in One-Way Broadcast Time Synchronization
Clock skew compensation is essential for accurate time synchronization in wireless networks.
An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks
To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy trust evaluation and outlier detection for WSNs.
A Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks
And then a density based outlier detection mechanism is introduced to acquire an adaptive trust threshold used to isolate the malicious nodes from being cluster heads.
An Intelligent Trust Cloud Management Method for Secure Clustering in 5G enabled Internet of Medical Things
To assure secure and reliable communication in 5G edge computing and D2D enabled IoMT systems, this paper presents an intelligent trust cloud management method.
An Intelligent Deterministic Scheduling Method for Ultra-Low Latency Communication in Edge Enabled Industrial Internet of Things
Then a non-collision theory based deterministic scheduling (NDS) method is proposed to achieve ultra-low latency communication for the time-sensitive flows.
AVDDPG: Federated reinforcement learning applied to autonomous platoon control
Both Inter-FRL and Intra-FRL are applied to a custom AV platooning environment using both gradient and weight aggregation to observe the performance effects FRL can have on AV platoons relative to an AV platooning environment trained without FRL.
Designs, Motion Mechanism, Motion Coordination, and Communication of Bionic Robot Fishes: A Survey
Various methods are needed to narrow the gap in swimming performance between robot fishes and fish.
Consensus Formation Tracking for Multiple AUV Systems Using Distributed Bioinspired Sliding Mode Control
Consensus formation tracking of multiple autonomous underwater vehicles (AUVs) subject to nonlinear and uncertain dynamics is a challenging problem in robotics.
Joint Energy Dispatch and Unit Commitment in Microgrids Based on Deep Reinforcement Learning
Nowadays, the application of microgrids (MG) with renewable energy is becoming more and more extensive, which creates a strong need for dynamic energy management.
Angel's Girl for Blind Painters: an Efficient Painting Navigation System Validated by Multimodal Evaluation Approach
This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands.
Face Mask Assistant: Detection of Face Mask Service Stage Based on Mobile Phone
Aimed at solving the problem that we don't know which service stage of the mask belongs to, we propose a detection system based on the mobile phone.
