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Efficient Hybrid Multi-Population Genetic Algorithm for Multi-UAV Task Assignment in Consumer Electronics Applications

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IEEE Transactions on Consumer Electronics 2025年

作者： Bai, Xiaoshan Jiang, Haoyu Li, Chao Ullah, Inam Dabel, Maryam M. Al Bashir, Ali Kashif Wu, Zongze Sam, Shuzhi Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen University Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan University of Hafr Al Batin Department of Computer Science and Engineering College of Computer Science and Engineering Saudi Arabia Manchester Metropolitan University Manchester United Kingdom Shenzhen518060 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp

关键词： Genetic algorithms

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P4toNFV: Offloading from P4 switches to NFV in programmable data planes

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International Journal of Communication systems 2024年第5期37卷 e5687-e5687页

作者： Pekar, Adrian Makara, Laszlo A. Lai, Yuan-Cheng Lin, Ying-Dar Seah, Winston Department of Networked Systems and Services Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary HUN-REN-BME Information Systems Research Group Budapest University of Technology and Economics Budapest Hungary Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand

P4 combines the benefits of hardware-based networking with the adaptability of software-based network operations. However, when faced with intricate network functions, P4 switches reveal constraints in memory and processing primitives. To address these, we advocate offloading traffic demanding intricate processing from the programmable data plane to network function virtualization (NFV). By leveraging this approach, P4 switches handle the core data plane, ensuring maximum performance, whereas virtualized network functions (VNF) cater to the intricate processing. Central to our research is the optimization of this offloading process, specifically considering delay constraints. We developed an analytical model that examines a P4 switch overseen by an SDN controller, integrating an offloading capability to NFV. The principal objective was to determine an offloading rate that minimizes packet processing delay. To this end, we employed a Bounded method, an advancement from Brent's method, to determine this optimal rate. The findings indicate that offloading approximately 66% of packets to the VNF achieves the lowest total delay, registering at 0.1505 (Formula presented.) s. This strategy of optimal offloading can notably reduce the system's average delay as the demand for network functions increases. The optimization technique we adopted exhibited rapid convergence in our experiments, reflecting the method's efficacy. Furthermore, a rigorous parametric sensitivity analysis spanning no offloading, full offloading, and optimal offloading strategies underscores that optimal offloading to NFV consistently augments system performance, particularly in terms of delay reduction. Conclusively, our study furnishes valuable insights into offloading strategies, augmenting the narrative on resource allocation in both PNFs and VNFs. © 2023 The Authors. International Journal of Communication systems published by John Wiley & Sons Ltd.

关键词： Network function virtualization

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Time-Robust Path Planning with Piece-Wise Linear Trajectory for Signal Temporal Logic Specifications

Time-Robust Path Planning with Piece-Wise Linear Trajectory ...

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American control Conference (ACC)

作者： Nhan-Khanh Le Erfaun Noorani Sandra Hirche John S. Baras Chair of Information-oriented Control (ITR) School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical and Computer Engineering Institute for Systems Research (ISR) at the University of Maryland College Park MD USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Real-world scenarios are characterized by timing uncertainties, e.g., delays, and disturbances. Algorithms with temporal robustness are crucial in guaranteeing the successful execution of tasks and missions in such scenarios. We study time-robust path planning for synthesizing robots' trajectories that adhere to spatial-temporal specifications expressed in Sig-nal Temporal Logic (STL). In contrast to prior approaches that rely on discretized trajectories with fixed time-steps, we leverage Piece-Wise Linear (PWL) signals for the synthesis. PWL signals represent a trajectory through a sequence of time-stamped waypoints. This allows us to encode the STL formula into a Mixed-Integer Linear Program (MILP) with fewer variables. This reduction is more pronounced for specifications with a long planning horizon. To that end, we define time-robustness for PWL signals. Subsequently, we propose quantitative semantics for PWL signals according to the recursive syntax of STL and prove their soundness. We then propose an encoding strategy to transform our semantics into a MILP. Our simulations showcase the soundness and the performance of our algorithm.

关键词： Uncertainty Semantics Transforms Syntactics Encoding Robustness Trajectory

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On modal observers for beyond rigid body H∞ control in high-precision mechatronics

arXiv

引用

arXiv 2022年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Hungary

The ever increasing need for performance results in increasingly rigorous demands on throughput and positioning accuracy of high-precision motion systems, which often suffer from position dependent effects that originate from relative actuation and sensing of the moving-body. Due to the highly stiff mechanical design, such systems are typically controlled using rigid body control design approaches. Nonetheless, the presence of position dependent flexible dynamics severely limits attainable position tracking performance. This paper presents two extensions of the conventional rigid body control framework towards active control of position dependent flexible dynamics. Additionally, a novel control design approach is presented, which allows for shaping of the full closed-loop system by means of structured H∞ co-design. The effectiveness of the approach is validated through simulation using a high-fidelity model of a state-of-the-art moving-magnet planar *** Codes 37M15 © 2022, CC BY.

关键词： Closed loop systems

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Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexagonal Boron Nitride for Integrated Quantum Photonics

Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexa...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Roberts, Henry C. Waseem, Aadil Wicker, Scott A. Abudayyeh, Hamza Kim, Dong Seob Liu, Zhida Randolph, Steven Li, Xiaoqin Li, Xiuling Department of Electrical and Computer Engineering Microelectronics Research Center The University of Texas at Austin 10100 Harry Ransom Trail AustinTX78758 United States Department of Physics Center for Complex Quantum Systems Center for Dynamics Control of Materials Texas Materials Institute The University of Texas at Austin 2515 Speedway AustinTX78712 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

We report a new approach to generate waveguide-coupled emission from deterministically implanted boron vacancy spin defects in hBN using single-crystal AlN-on-sapphire ring resonators. This facilitates the eventual development of hBN-based integrated quantum technologies. © Optica Publishing group 2024

关键词： Single crystals

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Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexagonal Boron Nitride for Integrated Quantum Photonics

Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexa...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Roberts, Henry C. Waseem, Aadil Wicker, Scott A. Abudayyeh, Hamza Kim, Dong Seob Liu, Zhida Randolph, Steven Li, Xiaoqin Li, Xiuling Department of Electrical and Computer Engineering Microelectronics Research Center The University of Texas at Austin 10100 Harry Ransom Trail AustinTX78758 United States Department of Physics Center for Complex Quantum Systems Center for Dynamics and Control of Materials Texas Materials Institute The University of Texas at Austin 2515 Speedway AustinTX78712 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

ISBN: (纸本)9781957171395

关键词： Aluminum nitride

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Learning Unknown Lagrange Dynamical systems with Guaranteed Persistency of Excitation

Learning Unknown Lagrange Dynamical Systems with Guaranteed ...

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International Conference on systems and control (ICSC)

作者： A. Samanis P. S. Trakas X. Papageorgiou K. J. Kyriakopoulos C. P. Bechlioulis Control Systems Lab School of Mechanical Engineering National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras Greece

ISBN: (数字)9781665465076

ISBN: (纸本)9781665465083

In this paper, we present a methodology that ensures a priori that all possible unknown dynamics of the system within a compact set of operation will be excited. A controller is used to make sure that the system with unknown dynamics will follow the reference trajectory and Radial Basis Function (RBF) neural networks are employed to estimate the unknown nonlinearities. The persistency of excitation condition is guaranteed as a prerequisite to achieve accurate estimation of the unknown nonlinear terms and efficient learning. A simulation example clarifies the proposed approach and verifies the aforementioned assertions.

关键词： Neural networks Estimation control systems Trajectory Nonlinear dynamical systems

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Robust Prescribed Performance control and Adaptive Learning for the Longitudinal Dynamics of Fixed-Wing UAVs

Robust Prescribed Performance Control and Adaptive Learning ...

引用

International Conference on systems and control (ICSC)

作者： S. Tzeranis P. S. Trakas X. Papageorgiou K. J. Kyriakopoulos C. P. Bechlioulis Control Systems Lab School of Mechanical Engineering National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras Greece

ISBN: (数字)9781665465076

ISBN: (纸本)9781665465083

The objective of this work is to simultaneously control and identify the nonlinear longitudinal dynamics of small-scale fixed-wing Unmanned Aerial Vehicles (UAVs). The main difficulty in this endeavor lies in the satisfaction of the Persistence of Excitation (PE) condition, which eventually ensures accurate learning. Towards this direction, our key components comprise Radial Basis Function - Neural Networks (RBF-NNs), which are suitable mathematical models for universal function approximation, alongside with: i) the recently developed Dynamic Regression Extension and Mixing (DREM) technique; a new procedure for designing parameter estimators with enhanced performance, as well as ii) a novel control design for the longitudinal UAV dynamics utilizing the Prescribed Performance control (PPC) methodology, which enables robust trajectory tracking with predetermined transient and steady state quality, even in the presence of model uncertainties.

关键词： Uncertainty Trajectory tracking Neural networks Autonomous aerial vehicles Mathematical models Steady-state Object recognition

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Learning of Nash Equilibria in Risk-Averse Games

Learning of Nash Equilibria in Risk-Averse Games

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American control Conference (ACC)

作者： Zifan Wang Yi Shen Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology and also with Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper considers risk-averse learning in convex games involving multiple agents that aim to minimize their individual risk of incurring significantly high costs. Specifically, the agents adopt the conditional value at risk (CVaR) as a risk measure with possibly different risk levels. To solve this problem, we propose a first-order risk-averse leaning algorithm, in which the CVaR gradient estimate depends on an estimate of the Value at Risk (VaR) value combined with the gradient of the stochastic cost function. Although estimation of the CVaR gradients using finitely many samples is generally biased, we show that the accumulated error of the CVaR gradient estimates is bounded with high probability. Moreover, assuming that the risk-averse game is strongly monotone, we show that the proposed algorithm converges to the risk-averse Nash equilibrium. We present numerical experiments on a Cournot game example to illustrate the performance of the proposed method.

关键词： Reactive power Costs Estimation Games Nash equilibrium Numerical simulation Cost function

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UAV-Based Optimization for Fruit Counting in Greenhouses

UAV-Based Optimization for Fruit Counting in Greenhouses

引用

International Conference on Unmanned Aircraft systems (ICUAS)

作者： João Vítor R. Vasconcelos Thayron M. Hudson André G. dos Santos Martin Saska Alexandre S. Brandão Department of Electrical Engineering Núcleo de Especialização em Robótica Graduate Program on Computer Science Federal Univer-sity of Vicosa Vicosa MG Brazil Graduate Program on Computer Science Federal University of Vicosa Vicosa MG Brazil Department of Cybernetics Multi-robot Systems Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper presents a solution for counting fruit in agricultural greenhouses using Unmanned Aerial Vehicles (UAV s). Initially, a heuristic based on Simulated Annealing was used to optimize the UAV's trajectory, ensuring efficient coverage of the beds. Next, digital image processing (DIP) techniques were implemented to count the fruit, including depth segmentation, application of bounding boxes, color filtering, and element counting. The DIP accuracy was evaluated in multiple scenarios and the results indicate high reliability in fruit counting, with the potential to optimize agricultural operations and provide valuable information to producers. Possible future improvements could include further refinements in image processing to increase the accuracy of counting other fruits. Ultimately, this work contributes to the advancement of automation in agriculture by offering a viable and efficient solution for counting fruit in greenhouses using UAV s.

关键词： Image segmentation Accuracy Image color analysis Greenhouses Simulated annealing Autonomous aerial vehicles Trajectory

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