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检索条件"任意字段=Conference on Navigation and Control Technologies for Unmanned Systems"

共 7752 条记录，以下是51-60 订阅

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Comparative Study of Q-Learning and SARSA Algorithms for UAV Path Planning in 3D Environments 28

Comparative Study of Q-Learning and SARSA Algorithms for UAV...

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28th IEEE International conference on Intelligent Engineering systems (INES)

作者： Zaghbani, Imen Jarray, Raja Bouallegue, Soufiene Univ Tunis El Manar Natl Engn Sch Tunis Res Lab Automat Control LARA Tunis 1002 Tunisia Univ Gabes Res Lab Automat Control LARA Natl Engn Sch Tunis Tunis 1002 Tunisia Univ Gabes High Inst Ind Syst Gabes Tunis 6072 Tunisia

ISBN: (纸本)9798350367607;9798350367591

Path planning processes in 3D environments with obstacles are essential for ensuring the successful navigation of unmanned Aerial Vehicles (UAVs). Recently, the artificial intelligence theory presents increasingly effective algorithms and tools to address such a robotics challenge. This paper presents a comparative study of two most commonly used Reinforcement Learning (RL) algorithms, namely Q-learning and SARSA learning. Through numerical experimentations under different navigation scenarios with varying levels of complexity and increasing numbers of static obstacles, key performance metrics like path's length, total actions number, average reward, execution time and collision avoidance are considered and evaluated. The demonstrative results indicate that the Q-learning algorithm well addressed the challenges of UAVs' path planning in static environments. The performance of such an algorithm has proven to be satisfactory and more promising for UAVs' navigation in complex configuration spaces when compared to the SARSA algorithm.

关键词： unmanned aerial vehicles path planning reinforcement learning Q-learning SARSA learning

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Autonomous navigation Method Based on Deep Reinforcement Learning with Dual-Layer Perception Mechanism

Autonomous Navigation Method Based on Deep Reinforcement Lea...

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2024 IEEE International conference on unmanned systems, ICUS 2024

作者： Yang, Ranhui Tang, Yuepeng Xiong, Guangming School of Mechanical Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350384185

Autonomous navigation systems are crucial in the field of robotics. Traditional methods often require extensive manual parameter tuning, which is time-consuming. In this paper, we present an autonomous navigation method that leverages deep reinforcement learning (DRL) enhanced by a dual-layer perception mechanism. This method integrates raw sensor data, local grid map, and the goal pose as inputs. Itutilizes the DRL framework to develop autonomous navigation strategies and directly generates robot action commands. This method eliminates the need for manual parameter adjustment, relying solely on continuous trial-and-error training to enable autonomous navigation. Comparative experiments in a simulation environment reveal that this system offers enhanced robustness and scalability compared to other DRL-based autonomous navigation systems. © 2024 IEEE.

关键词： Deep reinforcement learning

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Safeguarding Autonomous UAV navigation: Agent Design using Evolving Behavior Trees 18

Safeguarding Autonomous UAV Navigation: Agent Design using E...

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18th Annual IEEE International systems conference (SysCon)

作者： Potteiger, Nicholas Koutsoukos, Xenofon Vanderbilt Univ Dept Comp Sci Nashville TN 37235 USA

ISBN: (纸本)9798350358810;9798350358803

The rise in autonomous unmanned Aerial Vehicles (UAVs) for objectives requiring long-term navigation in diverse environments is attributed to their compact, agile, and accessible nature. Specifically, problems exploring dynamic obstacle and collision avoidance are of increasing interest as UAVs become more popular for tasks such as transportation of goods, formation control, and search and rescue routines. Prioritizing safety in the design of autonomous UAVs is crucial to prevent costly collisions that endanger pedestrians, mission success, and property. Safety must be ensured in these systems whose behavior emerges from multiple software components including learning-enabled components. Learning-enabled components, optimized through machine learning (ML) or reinforcement learning (RL), require adherence to safety constraints while interacting with the environment during training and deployment, as well as adaptation to new unknown environments. In this paper, we safeguard autonomous UAV navigation by designing agents based on behavior trees with learning-enabled components, referred to as Evolving Behavior Trees (EBTs). We learn the structure of EBTs with explicit safety components, optimize learning-enabled components with safe hierarchical RL, deploy, and update specific components for transfer to unknown environments. Safe and successful navigation is evaluated using a realistic UAV simulation environment. The results demonstrate the design of an explainable learned EBT structure, incurring near-zero collisions during training and deployment, with safe time-efficient transfer to an unknown environment.

关键词： unmanned aerial vehicles autonomous navigation explainable AI behavior trees hierarchical reinforcement learning genetic programming

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Proceedings of 2024 IEEE International conference on unmanned systems, ICUS 2024

Proceedings of 2024 IEEE International Conference on Unmanne...

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2024 IEEE International conference on unmanned systems, ICUS 2024

ISBN: (纸本)9798350384185

The proceedings contain 327 papers. The topics discussed include: a structural re-parameterization multiple object tracking algorithm for underwater unmanned autonomous systems;neural network algorithm for the knapsack allocation problem in unmanned systems;swarm navigation control algorithm for unmanned surface vehicles based on priority speed control;a method of distributed cluster task management based on multi-agent systems;fault-tolerant control for unmanned aerial vehicles via an adaptive neural network observer;control and planning of rotary wing unmanned aerial vehicles applied to high-altitude cableway detection;trajectory prediction method for unmanned systems based on dynamic graph neural network with adaptive weight adjustment;modeling the unmanned cluster collaboration problem and its application within the intelligence domain;and a hierarchical graph search method for path planning of unmanned ground vehicle for freight transportation.

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A Proposed Framework for UAS Positioning in GPS-Denied and GPS-Spoofed Environments 24

A Proposed Framework for UAS Positioning in GPS-Denied and G...

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Integrated Communications, navigation and Surveillance conference (ICNS)

作者： Burbank, Jack L. Foust, Landon Greene, Trevor Kaabouch, Naima Univ North Dakota Sch Elect Engn & Comp Sci Grand Forks ND 58202 USA

ISBN: (纸本)9798350393101;9798350393095

unmanned Aerial systems have become ubiquitous and are now widely used in commercial, consumer, and military applications. Their widespread use is due to a combination of their low cost, high capability, and ability to perform tasks and go places that are not easy or safe for humans. Most UAS platforms are dependent on Global navigation Satellite systems (GNSS), such as the Global Positioning System (GPS), to provide positioning information for navigation and flight control. Without reliable GPS signals, the flight path cannot be trusted, and flight safety cannot be assured. However, GPS is vulnerable to several types of malicious attacks, including jamming, spoofing, or physical attacks on the GPS constellation itself. Additionally, there are environments in which GPS reception is not always possible, a key example being urban canyon areas where line-of-site to the GPS satellite constellation may be blocked or obscured by large obstacles such as buildings. Numerous methods have been proposed for position estimation in GPS denied environments. However, these methods have significant limitations and typically exhibit poor performance in certain environments and scenarios. This paper analyzes the strengths and weaknesses of existing alternate positioning methods and describes a framework where multiple positioning solutions are jointly employed to construct an optimal position estimate. The proposed framework aims to reduce computation complexity of and yield good positioning performance across a wide variety of environments.

关键词： unmanned Aerial System Positioning navigation GPS-denied Operations

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Radio navigation Algorithms for Tasks of Industrial Internet of Things

Radio Navigation Algorithms for Tasks of Industrial Internet...

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2024 International Russian Smart Industry conference, SmartIndustryCon 2024

作者： Ushkov, A.N. Riazantsev, R.G. Morozov, N.V. Trofimov, A.Y. National Research University 'Moscow Power Engineering Institute' Moscow Polytechnic University Moscow Russia National Research University 'Moscow Power Engineering Institute' Moscow Russia

ISBN: (纸本)9798350395044

Increasing the bandwidth of modern cellular communication devices opens up new opportunities for automation and control of industrial processes. The minimization of wireless data transmission devices and data processing conducted with the help of cloud technologies and plant digitalization algorithms allows increasing the efficiency, safety and environmental friendliness of production devices. The integration of network technologies into data collection systems and cloud management of the actuator system is one of the steps towards the creation of Industry 4.0 systems where management and decision-making processes are conducted with the help of artificial intelligence algorithms. Determining the location of systems, devices and their nodes during the technological process implementation is an important task that becomes especially relevant with the introduction of robotic unmanned systems into technological processes. This paper discusses the possibilities of using navigation algorithms for the tasks of the industrial Internet of Things related to indoor navigation. The main areas of use of navigation tools are analyzed, as well as methods for integrating radar and radio navigation algorithms into the systems of Internet of Things and industrial Internet of Things. During the work, a robotic plafthorm with a naviagtion system, controlled via a cloud service, was developed and tested. At the same time, the methods of primary signal processing are considered to reduce the impact of fluctuations and interference in the system to the minimum. The experimental data obtained on a full-scale mock-up showed the effectiveness of the applied algorhithms. © 2024 IEEE.

关键词： Internet of things

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An Automatic navigation System for New Technical Advanced Drones for Different Alpplications 5

An Automatic Navigation System for New Technical Advanced Dr...

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5th IEEE International conference on Computing, Power, and Communication technologies, IC2PCT 2024

作者： Talwandi, Navjot Singh Thakur, Payal Khare, Shanu Chandigarh University Dept of Computer Science Engineering Punjab India

ISBN: (纸本)9798350383522

Autonomous pilot technology integrated into drones has ushered in a new era of unmanned aircraft systems, creating a multitude of applications This abstract examines the importance of the importance and potential of autonomous pilot aircraft, underscoring its transformative impact on industries ranging from agriculture to surveillance and beyond navigation requires intelligent a unmanned aerial vehicles (UAVs) will be equipped with sophisticated artificial and sensor systems, enabling them to operate autonomously without constant human intervention A rapidly growing field in robotics and aerospace technology Tires It is showing to do so, the paper provides a comprehensive overview, including key concepts, challenges, and recent developments in autonomous automation enter the box. It also discusses, and educates, the critical importance of real-time operations, the critical role of obstacle detection and avoidance systems, and the use of GPS and optical-based navigation delves into how machine learning and artificial intelligence enhance the autonomy of drones. In addition, the paper explores the many potential applications and benefits of autonomous drone communications, from search and rescue missions to precision agricultural delivery Growing interest and investment in this technology in 2013 highlights its potential to transform industries, promising a future marked by improved safety and performance. © 2024 IEEE.

关键词： and applications artificial intelligence Autonomous drones GPS machine learning navigation obstacle avoidance real-time data processing vision-based navigation

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INS/UWB Cooperative navigation Based on Distance and Angle in Underground Space

INS/UWB Cooperative Navigation Based on Distance and Angle i...

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2024 IEEE International conference on unmanned systems, ICUS 2024

作者： Chen, Jianheng Zhou, Dezhong Shi, Yining Qin, Haopeng Yang, Jiajian Hou, Yanqing School of Systems Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350384185

Urban underground space operations have become essential to many municipal projects in recent years. Aiming at the challenges of satellite navigation system (GNSS) denied environment, poor lighting conditions, and complex pipeline conditions in the underground environment, this paper proposes an INS / UWB navigation scheme based on cooperative angle and distance measured by UWB(Ultra Wide Band), to realize the robot's precise navigation and autonomous operation in the underground space. This scheme uses various sensors such as UWB and MEMS IMU(Miniature Inertial Measurement Unit) to achieve long-distance navigation with low error accumulation. The theoretical research and experimental results show that the technical scheme has the characteristics of low cost, low power consumption, and high precision and can provide location service in the underground environment. © 2024 IEEE.

关键词： Satellite navigation aids

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Cooperative Formation and navigation Methods for Distributed unmanned Surface Vehicle systems with Sensing Information 16

Cooperative Formation and Navigation Methods for Distributed...

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16th International conference on Signal Processing systems, ICSPS 2024

作者： Luo, Hao Lai, Zhuoyun Wang, Yinlu Ocean College Jiangsu University of Science and Technology Zhenjiang212003 China College of Information Science and Engineering Hohai University Changzhou213200 China Jiangsu Zanqi Technology Co. Ltd Changzhou213022 China

ISBN: (纸本)9781510689251

This paper investigates distributed strategy to improve the control efficiency for unmanned surface vehicles (USVs) in cooperative coexistence. We propose a distributed method of cooperative formation control and navigation with sensing information under motion constraints. Firstly, a distributed unmanned surface vehicle (USV) system model is developed using the dynamics model of the USVs. Local coordinates are employed to optimize the heading vector, enabling the USVs to navigate toward their destination while maintaining a specific formation. Subsequently, a control gain optimization model is formulated for the distributed USV system based on motion constraints. Lastly, the sensing information-based gain matrix design involves no-convex optimization, which is solved via a semidefinite relaxation (SDR) approach. Numerical results validate that the proposed approach significantly improves the control efficiency of the USV system and reduces communication overhead. © 2025 SPIE.

关键词： Convex optimization

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Guidance of Quadrotor unmanned Aerial Vehicles via Adaptive Multiple-Surface Sliding Mode control

Guidance of Quadrotor Unmanned Aerial Vehicles via Adaptive ...

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American control conference (ACC)

作者： Incremona, Gian Paolo Ferrara, Antonella Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Univ Pavia Dipartimento Ingn Ind & Informaz I-27100 Pavia Italy

ISBN: (纸本)9798350328066

In many application domains, navigation of unmanned aerial vehicles (UAVs) requires a planar flight to move along a desired path or to track a moving object under uncertain conditions. In this paper, we propose a robust control approach for quadrotor UAVs performing a nonholonomic-like navigation with a predefined velocity based guidance law. Specifically, the quadrotor model is first recast in the framework of nonholonomic systems, and then an adaptive multiple-surface sliding mode approach, with suboptimal second order sliding mode control, is applied. The robustness features of the proposed approach are discussed and assessed in simulation.

关键词： Sliding mode control unmanned aerial vehicles nonholonomic systems

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