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  • Open Access

    ARTICLE

    3D Path Optimisation of Unmanned Aerial Vehicles Using Q Learning-Controlled GWO-AOA

    K. Sreelakshmy1, Himanshu Gupta1, Om Prakash Verma1, Kapil Kumar2, Abdelhamied A. Ateya3, Naglaa F. Soliman4,*

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2483-2503, 2023, DOI:10.32604/csse.2023.032737 - 21 December 2022

    Abstract Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general More >

  • Open Access

    ARTICLE

    An Efficient Path Planning Strategy in Mobile Sink Wireless Sensor Networks

    Najla Bagais*, Etimad Fadel, Amal Al-Mansour

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1237-1267, 2022, DOI:10.32604/cmc.2022.026070 - 18 May 2022

    Abstract Wireless sensor networks (WSNs) are considered the backbone of the Internet of Things (IoT), which enables sensor nodes (SNs) to achieve applications similarly to human intelligence. However, integrating a WSN with the IoT is challenging and causes issues that require careful exploration. Prolonging the lifetime of a network through appropriately utilising energy consumption is among the essential challenges due to the limited resources of SNs. Thus, recent research has examined mobile sinks (MSs), which have been introduced to improve the overall efficiency of WSNs. MSs bear the burden of data collection instead of consuming energy… More >

  • Open Access

    ARTICLE

    Improved Dijkstra Algorithm for Mobile Robot Path Planning and Obstacle Avoidance

    Shaher Alshammrei1, Sahbi Boubaker2,*, Lioua Kolsi1,3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5939-5954, 2022, DOI:10.32604/cmc.2022.028165 - 21 April 2022

    Abstract Optimal path planning avoiding obstacles is among the most attractive applications of mobile robots (MRs) in both research and education. In this paper, an optimal collision-free algorithm is designed and implemented practically based on an improved Dijkstra algorithm. To achieve this research objectives, first, the MR obstacle-free environment is modeled as a diagraph including nodes, edges and weights. Second, Dijkstra algorithm is used offline to generate the shortest path driving the MR from a starting point to a target point. During its movement, the robot should follow the previously obtained path and stop at each… More >

  • Open Access

    ARTICLE

    A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms

    Mahmoud Ragab1,2,3,*, Ali Altalbe1, Abdullah Saad Al-Malaise ALGhamdi4, S. Abdel-khalek5,6, Rashid A. Saeed7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 365-380, 2022, DOI:10.32604/cmc.2022.024932 - 24 February 2022

    Abstract The smart city comprises various interlinked elements which communicate data and offers urban life to citizen. Unmanned Aerial Vehicles (UAV) or drones were commonly employed in different application areas like agriculture, logistics, and surveillance. For improving the drone flying safety and quality of services, a significant solution is for designing the Internet of Drones (IoD) where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones, where the drones were utilized for collecting the data, and communicate with More >

  • Open Access

    ARTICLE

    Enhancing Task Assignment in Crowdsensing Systems Based on Sensing Intervals and Location

    Rasha Sleem1, Nagham Mekky1, Shaker El-Sappagh2,3, Louai Alarabi4,*, Noha A. Hikal1, Mohammed Elmogy1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5619-5638, 2022, DOI:10.32604/cmc.2022.023716 - 14 January 2022

    Abstract The popularity of mobile devices with sensors is captivating the attention of researchers to modern techniques, such as the internet of things (IoT) and mobile crowdsensing (MCS). The core concept behind MCS is to use the power of mobile sensors to accomplish a difficult task collaboratively, with each mobile user completing much simpler micro-tasks. This paper discusses the task assignment problem in mobile crowdsensing, which is dependent on sensing time and path planning with the constraints of participant travel distance budgets and sensing time intervals. The goal is to minimize aggregate sensing time for mobile… More >

  • Open Access

    ARTICLE

    Path Planning Based on the Improved RRT* Algorithm for the Mining Truck

    Dong Wang1,*, Shutong Zheng1, Yanxi Ren2, Danjie Du3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3571-3587, 2022, DOI:10.32604/cmc.2022.022183 - 07 December 2021

    Abstract Planning a reasonable driving path for trucks in mining areas is a key point to improve mining efficiency. In this paper, a path planning method based on Rapidly-exploring Random Tree Star (RRT*) is proposed, and several optimizations are carried out in the algorithm. Firstly, the selection process of growth target points is optimized. Secondly, the process of selecting the parent node is optimized and a Dubins curve is used to constraint it. Then, the expansion process from tree node to random point is optimized by the gravitational repulsion field method and dynamic step method. In the… More >

  • Open Access

    ARTICLE

    Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

    Aisha Muhammad1,5, Mohammed A. H. Ali2,*, Sherzod Turaev3, Ibrahim Haruna Shanono4,5, Fadhl Hujainah6, Mohd Nashrul Mohd Zubir2, Muhammad Khairi Faiz2, Erma Rahayu Mohd Faizal1, Rawad Abdulghafor8

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2697-2719, 2022, DOI:10.32604/cmc.2022.020873 - 07 December 2021

    Abstract This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested… More >

  • Open Access

    ARTICLE

    Vision-Aided Path Planning Using Low-Cost Gene Encoding for a Mobile Robot

    Wei-Cheng Wang, Chow-Yong Ng, Rongshun Chen*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 991-1006, 2022, DOI:10.32604/iasc.2022.022067 - 17 November 2021

    Abstract Path planning is intrinsically regarded as a multi-objective optimization problem (MOOP) that simultaneously optimizes the shortest path and the least collision-free distance to obstacles. This work develops a novel optimized approach using the genetic algorithm (GA) to drive the multi-objective evolutionary algorithm (MOEA) for the path planning of a mobile robot in a given finite environment. To represent the positions of a mobile robot as integer-type genes in a chromosome of the GA, a grid-based method is also introduced to relax the complex environment to a simple grid-based map. The system architecture is composed of More >

  • Open Access

    ARTICLE

    Optimal Path Planning for Intelligent UAVs Using Graph Convolution Networks

    Akshya Jothi, P. L. K. Priyadarsini*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1577-1591, 2022, DOI:10.32604/iasc.2022.020974 - 09 October 2021

    Abstract Unmanned Aerial Vehicles (UAVs) are in use for surveillance services in the geographic areas, that are very hard and sometimes not reachable by humans. Nowadays, UAVs are being used as substitutions to manned operations in various applications. The intensive utilization of autonomous UAVs has given rise to many new challenges. One of the vital problems that arise while deploying UAVs in surveillance applications is the Coverage Path Planning(CPP) problem. Given a geographic area, the problem is to find an optimal path/tour for the UAV such that it covers the entire area of interest with minimal… More >

  • Open Access

    ARTICLE

    Path Planning of Quadrotors in a Dynamic Environment Using a Multicriteria Multi-Verse Optimizer

    Raja Jarray1, Mujahed Al-Dhaifallah2,*, Hegazy Rezk3,4, Soufiene Bouallègue1,5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2159-2180, 2021, DOI:10.32604/cmc.2021.018752 - 21 July 2021

    Abstract Paths planning of Unmanned Aerial Vehicles (UAVs) in a dynamic environment is considered a challenging task in autonomous flight control design. In this work, an efficient method based on a Multi-Objective Multi-Verse Optimization (MOMVO) algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving obstacles. Such a path planning task is formulated as a multicriteria optimization problem under operational constraints. The proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving obstacles. The vehicle… More >

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