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Article
Computer Science, Artificial Intelligence
Ahmed Awad et al.
Summary: The use of binary decision diagrams (BDDs) has been widely adopted in various fields. Constructing the BDD of a Boolean function allows for its analysis. However, the size of the BDD can be reduced by applying proper variable reordering and reduction rules while preserving its fidelity. Algorithms have been proposed for finding optimal variable orders, but their scalability is limited in complex systems. This article proposes a BDD optimizer driven by either a genetic algorithm or swarm engines, which effectively reduces the BDD size with linear computational complexity.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2023)
Article
Computer Science, Artificial Intelligence
Ziheng Qi et al.
Summary: In this article, a path planning and control framework for autonomous vehicles with low-cost positioning is proposed. It utilizes a potential field and reinforcement learning agent to generate collision-free paths, and a model predictive control algorithm for vehicle dynamics is designed. Simulation results demonstrate the effectiveness of the proposed algorithm in avoiding obstacles and meeting real-time navigation requirements.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Computer Science, Artificial Intelligence
Claudiu Pozna et al.
Summary: This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The algorithm is applied to the optimal tuning of proportional-integral-fuzzy controllers for position control of integral-type servo systems, resulting in reduced energy consumption. A comparison with other metaheuristic algorithms is provided at the end of the article.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Mudasir Ahmed Memon et al.
Summary: This article proposes a hybrid asynchronous particle swarm optimization-genetic algorithm (APSO-GA) for the removal of unwanted lower order harmonics in the cascaded H-bridge multilevel inverter. The APSO-GA combines the exploration capability of APSO with the exploitation capability of GA, and is capable of easily finding feasible solutions with low computational complexity.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Haishi Liu et al.
Summary: This article discusses the importance of using drones equipped with RFID readers for inventory management in the tobacco industry. It proposes a task planning model for UAV inventory library and introduces a hybrid algorithm based on lion swarm optimization to address the limitations of traditional algorithms. The proposed algorithm is validated through environmental modeling using real data from a tobacco warehouse.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Xiaohuan Liu et al.
Summary: The hybrid path planning algorithm in this paper combines optimized reinforcement learning and improved particle swarm optimization to achieve efficient path planning results. By optimizing RL hyperparameters, designing a pre-set operation for PSO, and proposing a correction variable, the algorithm selects the optimal path effectively.
ENGINEERING COMPUTATIONS
(2022)
Article
Robotics
Ziang Zhang et al.
Summary: This study proposes a general robust reference path selection method (RPSM) to improve the mobile performance of autonomous patrol robots. The experiments confirm that RPSM enriches the diversity and robustness of reference paths, and significantly improves the execution efficiency.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Engineering, Civil
Songtao Xie et al.
Summary: This paper proposes a distributed motion planning algorithm for safe overtaking of autonomous vehicles in a dynamic environment. By introducing the concepts of velocity difference potential field and acceleration difference potential field, a multi-vehicle system consisting of both autonomous and human-operated vehicles is modeled, and an optimization-based algorithm is proposed to solve the overtaking problem.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Qinqin Fan et al.
Summary: The paper introduces an automatic selection strategy of multiobjective evolutionary algorithms based on performance indicators (MOEAS-PI). This strategy can effectively improve the efficiency and robustness of solving multiobjective optimization problems.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Civil
Van-Linh Nguyen et al.
Summary: This study proposes a path planning and traffic clear-out scheduling scheme to reduce the travel time of emergency vehicles. By controlling dynamic traffic and coordinating traffic lights, the system outperforms traditional methods in simulation, especially in congested or heavily trafficked road segments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Zi-Jia Wang et al.
Summary: This article presents a parameter-free niching method based on adaptive estimation distribution (AED) and develops a distributed differential evolution (DDE) algorithm, called AED-DDE, for solving multimodal optimization problems (MMOPs). The algorithm improves population diversity through a multiniche co-evolution mechanism and refines solution accuracy through probabilistic local search.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Muleilan Pei et al.
Summary: This article introduces an improved Dyna-Q algorithm for mobile robot path planning in unknown environments with static and dynamic obstacles, utilizing heuristic search strategies, simulated annealing mechanism, and reactive navigation principle to enhance performance. The method effectively tackles the exploration-exploitation dilemma and demonstrates superior performance in simulations with multiple dynamic obstacles. Additionally, practical experiments on a physical robot platform show successful autonomous navigation results in real-world scenarios.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Robotics
Zhongqiang Ren et al.
Summary: Path planning among dynamic obstacles is a fundamental problem in Robotics. In this work, we propose an algorithm called MO-SIPP that efficiently solves the problem of Multi-Objective Path Planning with Dynamic Obstacles by combining the ideas from SIPP and multi-objective A* algorithms.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Computer Science, Information Systems
Zhenhua Yu et al.
Summary: This article proposes a novel hybrid particle swarm optimization (PSO) algorithm, SDPSO, for the automatic path planning problem of unmanned aerial vehicles (UAVs). The algorithm improves the update strategy of the global optimal solution in the PSO algorithm by merging the simulated annealing algorithm, and integrates the beneficial information of the optimal solution according to the dimensional learning strategy for each particle. Simulation results show that the SDPSO algorithm can quickly plan higher quality paths for UAVs and has better robustness in complex 3-D environments compared to other algorithms.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Habib Mohammed Hussein et al.
Summary: This article presents a modified PSO approach for reducing the sidelobe level of UHA antennas in HAP wireless networks using the TVWS spectrum. Simulation results show that the proposed approach outperforms the standard PSO algorithm and uniform weighting scheme in terms of sidelobe reduction and CIR performance improvement.
IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY
(2022)
Article
Mathematics, Applied
Vladimir V. Bogdanov et al.
Summary: The paper presents an algorithm for selecting tension parameters of generalized splines for convexity preserving interpolation. Specific algorithms for different generalized cubic splines are considered, including rational, exponential, variable power, hyperbolic splines, and splines with additional knots.
NUMERICAL ALGORITHMS
(2021)
Article
Computer Science, Artificial Intelligence
Faiza Gul et al.
Summary: The article presents a multi-objective path planning algorithm that combines different optimization techniques to address the challenges in mobile robot path planning. By integrating Grey Wolf optimizer, particle swarm optimization, and local search, the algorithm effectively overcomes the limitations of conventional techniques.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Robotics
Vishnu S. Chipade et al.
Summary: This article introduces a method for herding adversarial agents in a 2-D obstacle environment, utilizing closed formation of defenders to guide attackers toward a safe area. The efficacy of the approach is demonstrated through formal proofs of collision-free trajectory generation and convergence of defenders to desired formations in simulations. Additionally, an implementation on quadrotor vehicles in the Gazebo simulator is provided.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Review
Engineering, Marine
Anete Vagale et al.
Summary: This paper reviews the guidance and path planning algorithms of autonomous surface vehicles, highlighting the need for new regulations in the field. The analysis of terminology used in the literature aims to clarify ambiguities in commonly used terms related to path planning.
JOURNAL OF MARINE SCIENCE AND TECHNOLOGY
(2021)
Article
Automation & Control Systems
Shengchao Zhou et al.
Summary: This article discusses a single BPM scheduling problem with unequal release times and job sizes, proposing a self-adaptive differential evolution algorithm to address the issue. Experimental results show that the proposed algorithm is more effective in solving the scheduling problem compared to other existing algorithms.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Chenhui Zhao et al.
Summary: This article presents an integrated algorithm that uses the Nash equilibrium strategy combined with the PSO algorithm and SOM neural network to solve multiobjective optimization problems. The algorithm effectively addresses MOPs by comparing decision variables one by one and adjusting inertia weight using a nonlinear recursive function. Additionally, it utilizes SOM to construct neighborhood relations and select leading particles for local and global search, achieving superior performance compared to other advanced algorithms.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Review
Automation & Control Systems
Jun Tang et al.
Summary: Swarm intelligence algorithms are a subset of artificial intelligence that has gained popularity for solving optimization problems and has been widely utilized in various applications. This review summarizes the most representative swarm intelligence algorithms and their successful applications in engineering fields, providing insights into future trends and prospects for development.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Automation & Control Systems
Mohamed A. Kamel et al.
Summary: The proposed fault-tolerant formation control strategy addresses severe actuator faults by reconfiguring the formation for healthy robots, planning trajectories using a hybrid genetic algorithm and particle swarm optimization. The integration of control parameterization and time discretization with GA-PSO minimizes time of achieving configuration while considering WMR constraints and collision avoidance. Real-time experiments validate effectiveness compared to other optimization techniques.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2021)
Article
Robotics
Alberto Favaro et al.
Summary: The study presents a three-dimensional path planner for neurosurgical applications, which balances obstacle avoidance, reduction of insertion length, and fine-tuning of pathways to meet multiple optimization objectives.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Article
Engineering, Electrical & Electronic
Jiabao Wen et al.
Summary: Research on path planning for AUVs has rapidly progressed, with traditional heuristic algorithms facing issues of slow convergence speed and premature convergence. To address these problems, a new heuristic algorithm combining genetic, ant colony optimization, and simulated annealing algorithms is proposed, alongside additional techniques to accelerate convergence and expand search space. The advantages of the proposed algorithm are demonstrated through simulated comparative experiments, along with the introduction of ocean current and kinematics models for AUV path planning under the influence of ocean currents.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Review
Computer Science, Information Systems
Faiza Gul et al.
Summary: This paper presents a review of three important communication techniques for ground, aerial, and underwater vehicles, focusing on trajectory planning, optimization, and related issues. Efforts have been made to fill the knowledge gap in path planning by exploring various optimization techniques suitable for implementing these vehicles. The paper provides a consolidated platform for research on autonomous vehicles and trajectory optimization, extending to aerial and underwater vehicles.
Article
Robotics
Zhiqiang Jian et al.
Summary: This study introduces a global-local Coupling Two-Stage Path Planning (CTSP) method, which improves path planning effectiveness through collaboration between global and local planning, and the effectiveness of the method is verified through testing in a simulation environment.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
Biwei Tang et al.
NEURAL COMPUTING & APPLICATIONS
(2020)
Article
Robotics
Peng Chen et al.
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
(2019)
Review
Engineering, Multidisciplinary
B. K. Patle et al.
DEFENCE TECHNOLOGY
(2019)
Article
Automation & Control Systems
Cheng-Jian Lin et al.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2019)
Article
Computer Science, Information Systems
Guangsheng Li et al.
SCIENCE CHINA-INFORMATION SCIENCES
(2018)
Article
Multidisciplinary Sciences
Han-ye Zhang et al.
Article
Computer Science, Artificial Intelligence
Ritambhar Burman et al.
Article
Engineering, Aerospace
Runqi Chai et al.
Article
Computer Science, Artificial Intelligence
Dervis Karaboga et al.
ARTIFICIAL INTELLIGENCE REVIEW
(2014)
