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Joint visual coverage and Energy Consumption Optimization for UAV-Aided 5G-and-Beyond Communications

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第12期73卷 19417-19431页

作者： Huang, Zhengrui Wang, Shujie Penn State Univ Dept Geog University Pk PA 16802 USA Earth & Environm Syst Inst EESI Dept Geog University Pk PA 16802 USA Penn State Univ Inst Computat & Data Sci ICDS University Pk PA 16802 USA

With the rapid advancement in cellular technologies, integrating unmanned aerial vehicles (UAVs) into 5G and beyond becomes a promising solution to enabling UAV-related services, which poses a pressing need for ubiquitous wireless coverage and effective onboard energy management. Joint optimization of coverage and energy, however, remains understudied, especially in the scenario of 5G and beyond, i.e., extended wireless coverage with limited onboard energy. In this article, we propose a novel approach to optimizing the configuration of a team of UAVs to cover an arbitrary 3-D surface, including their transmit power, 3-D locations, and number. Here, the discussed problem is formulated as a multiobjective optimization problem (MOP), whose goal is to simultaneously maximize visual coverage (VC) and minimize energy consumption (EC). To optimally solve this MOP, we analy-tically derive the closed-form expression of VC and maximize VC by jointly optimizing the transmit power and 3-D location of a UAV. The transmit power and 3-D location of a UAV are further updated by minimizing the EC arising from aerial movement and wireless transmission. Given the optimized VC and EC of an individual UAV, the optimal number of UAVs is obtained by finding the best tradeoff between minimum VC and total EC, subject to a given set of constraints on transmit power, signal-to-interference-plus-noise ratios, outage probabilities, sensing distances, and onb-oard energy. Simulation results validate the effectiveness of the proposed approach, revealing that energy efficiency (EE) remains high with an extended coverage area.

关键词： Autonomous aerial vehicles 5G mobile communication Optimization Internet of Things Interference Wireless communication Probability 5G and beyond energy consumption energy efficiency multiobjective optimization unmanned aerial vehicle visual coverage

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Deployment Optimization of Spotlights for visual coverage in Pure Dark Indoor Scene

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第7期19卷 8518-8527页

作者： Chen, Xi Lei, Zike Yang, Yong Chai, Li Wuhan Univ Sci & Technol Engn Res Ctr Met Automat & Measurement Technol Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Hubei Peoples R China Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China

In this article, a deployment method of spotlights is studied for visual coverage task in pure dark indoor scene. To characterize the illumination performance of target in visual sensor, a criterion called illumination strength of spotlight with combining the diffuse reflection and specular reflection on the basis of distance/angle illumination attenuation of light source as well as shading is proposed. Then, an optimization problem is formulated for a number of spotlights with the aim of covering the target with a desired luminance value in camera network as uniformly as possible. An elimination genetic algorithm possessing faster convergence rate and better convergence performance than standard genetic algorithm is utilized to solve the optimization problem. Finally, numerical simulations and experiments are conducted to validate the proposed deployment method of multiple spotlights for visual coverage task in pure dark indoor scene.

关键词： Illumination sensors deployment visual coverage

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Cooperative Motion Planning for Persistent 3D visual coverage With Multiple Quadrotor UAVs

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第3期21卷 3374-3383页

作者： Wang, Hongpeng Song, Shangyuan Guo, Qianghui Xu, Dian Zhang, Xiaoyang Wang, Peizhao Nankai Univ Coll Artificial Intelligence Tianjin 300071 Peoples R China Nankai Univ Sch Math Sci LPMC Tianjin 300071 Peoples R China Nankai Univ Coll Elect Informat & Opt Engn Tianjin 300071 Peoples R China

In this paper, we address the multiple quadrotor UAVs trajectory planning optimization problem for large-scale, persistent, high-depth visual coverage tasks in three-dimensional (3-D) terrain environment. To minimize the overall energy expenditure of the UAVs for accomplishing a task, we set up an air-to-ground collaborative system which introduces base stations to hold and recharge UAVs. The system is formulated as an integer programming, and solved by a novel hierarchical reinforcement learning trajectory planning algorithm (RL-TP), in which the paths are obtained by reinforcement learning method, and then the trajectories are obtained by Bezier curve method. Both simulation and physical experiments show that RL-TP can effectively improve the efficiency and persistence of aerial visual coverage task. Note to Practitioners-While the multi-rotor UAV has been an important means for field monitoring, it suffers the problem of short battery life a lot. To make it more efficient and persistent, we use multiple UAVs and introduce ground base stations to charge the UAVs. The scenario is formulated as an air-to-ground collaborative system, and the motion planning strategy is to minimize the energy consumption. We propose a hierarchical collaborative coverage reinforcement learning trajectory planning algorithm (RL-TP) to solve it. We carry out both simulation and physical field experiments, and compare RL-TP with other popular methods. The experimental results show that the system is feasible and RL-TP performs well in both time efficiency and energy consumption. In future research, we will introduce unmanned ground vehicles to replace the stationary ground base stations to make the air-to-ground collaborative system more powerful and flexible.

关键词： UAV air-to-ground visual coverage motion planning reinforcement learning

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View planning for visual detection coverage tasks of large airplane upper surface using UAVs

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Biomimetic Intelligence and Robotics 2025年

作者： Zhun Huang Chinese Flight Test Establishment Xian 710089 China

In order to enhance the efficiency of visual inspection and effectively carry out 3D visual coverage tasks, this paper focuses on the 3D view planning problem concerning the visual coverage of an airplane’s surface using unmanned aerial vehicles (UAV). Our objective is to attain a sufficiently high coverage rate with the least number of viewpoints. The contributions of this work are enumerated as follows. Firstly, the 3D model of the target aircraft is spatially extended in accordance with the depth range of the camera mounted on the drone, thereby confining the sampling range of 3D viewpoints. Next, a candidate set of viewpoints is generated through random sampling and the probabilistic potential field technique. Subsequently, we propose a novel hyper-heuristic algorithm. In this algorithm, a genetic algorithm serves as a high-level heuristic strategy, in tandem with multiple low-level heuristic operators devised for combinatorial optimization. This not only augments the capacity to seek the global optimal solution but also expedites the convergence rate, aiming to ascertain the optimal subset of viewpoints. Moreover, we devise a new fitness function for appraising candidate solution vectors in the set covering problem (SCP), strengthening the evolutionary guidance for genetic algorithms. Eventually, experimental findings on the simulated and real airplanes corroborate the efficacy of the proposed method, i.e., it markedly diminishes the requisite number of viewpoints and augments inspection efficiency.

关键词： Airplane surface inspection View planning visual coverage Combinatorial optimization Unmanned aerial vehicle

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An Effective Method for Complete visual coverage Path Planning

An Effective Method for Complete Visual Coverage Path Planni...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Jie Li Xiaohui Hu Changwen Zheng Dept. of Electronic Engineering and Information Science University of Science and Technology of Chin National Key Laboratory of Integrated Information System Technology ISCAS

This paper addresses the complete visual coverage path planning problem in raster terrain and presents an effective solution with hierarchy based on multiple observers siting and an evolutionary path planning algorithm. The main idea of the method is to get a nearly optimal complete visual coverage path by connecting all of the observers in the visual coverage set. Firstly a new deterministic algorithm for a quasi minimal number set of observers is presented, which is superior to the general greedy algorithm in the time complexity and the quality of solutions. On the basis of that we further present a hierarchy path planning method whose core is an evolutionary algorithm. The advantage of the proposed method is that it realizes really complete visual coverage with a comparatively optimal path and easy to extend to the version of multiple paths.

关键词： visual coverage complete coverage path planning multiple observers sitting evolutionary algorithm raster terrain

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Evolutionary Algorithm for Optimal visual coverage Path in Raster Terrain

Evolutionary Algorithm for Optimal Visual Coverage Path in R...

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2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Jie Li Dept.of Electronic Engineering and Information Science University of Science and Technology of China Hefei,China Changwen Zheng,Xiaohui Hu National Key Laboratory of Integrated Information System Technology,ISCAS Beijing,China

There is a wide range of applications in both military and civil fields for optimal path problem in raster terrain whose cost is visibility *** the path search problem whose objective is maximal average horizon,the traditional algorithms are unsuitable due to the characteristic of the *** paper presents a method based on evolutionary algorithm,which may rapidly get the optimal solution by designing multiple effective evolutionary operators and self-adaptively adjusting the probability of each *** show that the method presented is superior to the simulated annealing algorithm.

关键词： evolutionary algorithm average horizon visual coverage raster terrain

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Availability Issues for Relevant Area coverage in Wireless visual Sensor Networks

Availability Issues for Relevant Area Coverage in Wireless V...

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CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

作者： Costa, Daniel G. Duran-Faundez, Cristian Bittencourt, Joao Carlos N. State Univ Feira de Santana DTEC UEFS Feira De Santana Brazil Univ Bio Bio DIEE UBB Concepcion Chile Univ Fed Reconcavo Bahia CETS UFRB Cruz Das Almas Brazil

ISBN: (纸本)9781538631232

Camera-enabled sensors deployed for visual monitoring will cover a region of the target field, providing information for many innovative applications based on wireless sensing. Actually, some areas of the monitored field may have more relevance than others, according to the characteristics of the applications, which may indicate that such areas need better coverage to avoid blind spots and achieve higher visual redundancy. In order to provide a metric to assess how well relevant areas are being covered, this paper proposes an availability metric which associates coverage to the relevance of areas, which may be useful when assessing monitoring availability. Moreover, a greedy algorithm is also proposed to compute sensing orientations for all visual sensors, aiming at the enhancement of visual coverage over the most relevant areas. With such proposals, it is possible to initially address the particular problem of visual coverage over areas with different relevances, providing practical mechanisms to improve the overall availability level of monitoring applications in wireless visual sensor networks.

关键词： Availability Wireless visual Sensor Networks visual coverage Camera Optimization

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coverage Overlaps Reduction with Delaunay Triangulation for visual Sensor Networks

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JOURNAL OF INTERNET TECHNOLOGY 2019年第3期20卷 809-816页

作者： Zhang, Shun-Miao Huang, De-Gen Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou Fujian Peoples R China Fujian Univ Technol Coll Informat Sci & Engn Fuzhou Fujian Peoples R China

A visual sensor network (VSN) employs visual (camera) sensors instead of scalar sensors to establish the wireless network for wide area monitoring and target tracking. The visual sensing coverage of a VSN is quite related to the sensing direction and sensing angle of each camera sensors in the network. Many research issues of VSNs are similar but much different from the ones of ordinary scalar sensor networks, and the visual coverage issue is more specific. In the past years, a great number of research literatures have been proposed to address the coverage issues for ordinary scalar sensor networks. A part of the existing approaches use geometric structure concepts in the researches. However, utilizing geometric structures to solve visual sensing coverage has not drawn much attention of researches. This study, therefore, utilizes a geometric structure of Delaunay Triangulation with its characteristics to improve overall visual coverage of a sensing field for VSNs. The results of evaluation with simulations show the proposed approach performs very well and obtains a significant visual coverage improvement for VSNs. This could be a reference basis for further studies.

关键词： visual sensor network visual coverage Delaunay triangulation Geometry

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Placing and scheduling many depth sensors for wide coverage and efficient mapping in versatile legged robots

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INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2020年第4期39卷 431-460页

作者： Brandao, Martim Figueiredo, Rui Takagi, Kazuki Bernardino, Alexandre Hashimoto, Kenji Takanishi, Atsuo Univ Oxford Oxford Robot Inst Oxford England Univ Lisbon Inst Super Tecn Lisbon Portugal Waseda Univ Tokyo Japan Meiji Univ Tokyo Japan

This article tackles the problem of designing 3D perception systems for robots with high visual requirements, such as versatile legged robots capable of different locomotion styles. In order to guarantee high visual coverage in varied conditions (e.g., biped walking, quadruped walking, ladder climbing), such robots need to be equipped with a large number of sensors, while at the same time managing the computational requirements that arise from such a system. We tackle this problem at both levels: sensor placement (how many sensors to install on the robot and where) and run-time acquisition scheduling under computational constraints (not all sensors can be acquired and processed at the same time). Our first contribution is a methodology for designing perception systems with a large number of depth sensors scattered throughout the links of a robot, using multi-objective optimization for optimal trade-offs between visual coverage and the number of sensors. We estimate the Pareto front of these objectives through evolutionary optimization, and implement a solution on a real legged robot. Our formulation includes constraints on task-specific coverage and design symmetry, which lead to reliable coverage and fast convergence of the optimization problem. Our second contribution is an algorithm for lowering the computational burden of mapping with such a high number of sensors, formulated as an information-maximization problem with several sampling techniques for speed. Our final system uses 20 depth sensors scattered throughout the robot, which can either be acquired simultaneously or optimally scheduled for low CPU usage while maximizing mapping quality. We show that, when compared with state-of-the-art robotic platforms, our system has higher coverage across a higher number of tasks, thus being suitable for challenging environments and versatile robots. We also demonstrate that our scheduling algorithm allows higher mapping performance to be obtained than with naive and s

关键词： Design optimization sensor placement visual coverage next-best view sensor scheduling 3D mapping

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MSNS: mobile sensor network simulator for area coverage and obstacle avoidance based on GML

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2012年第1期2012卷 1-15页

作者： Jeong, Young-Sik Han, Youn-Hee Park, James J. Lee, SooYoung Seoul Natl Univ Sci & Technol Dept Comp Sci & Engn Seoul South Korea Elect & Telecommun Res Inst Embedded Software Res Dept Taejon 305606 South Korea Wonkwang Univ Dept Comp Engn Iksan 570749 South Korea Korea Univ Technol & Educ Adv Technol Res Ctr Cheonan South Korea

A mobile sensor network is a distributed collection of sensors, each of which has sensing, computation, communication, and locomotion capabilities. In particular, locomotion facilitates the ability to self-deployment. In such a network of self-deployable mobile sensors, it is difficult to evaluate the effectiveness of mobile sensor network deployment in a given target area because we cannot predict the coverage rate for the target area. The coverage rate will be changed due to the number of sensor required in the target area, connectivity degree to be maintained and unknown obstacles. In this article, we develop mobile sensor network simulator (MSNS) in order to visualize (1) coverage secured by mobile sensors and (2) avoidance of obstacle objects (building, road and wall, and so on) on the real map drawn by GML (Geography Markup Language). From a user, MSNS receives the number of mobile sensor nodes, connectivity degree, sensor node's sensing range, communication range, and supersonic wave range. And then it visualizes the location information of sensor nodes, connectivity degree, and sensing coverage, all of which change with simulation time. Thereby we can estimate how many nodes are required in a given target area, and also calculate coverage rate of the target area in advance to the real deployment of mobile sensors.

关键词： mobile sensor network visual coverage connectivity potential field

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