Hongle Li¹, SeongKi Kim^2,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5571-5594, 2025, DOI:10.32604/cmc.2025.067424 - 23 October 2025

Abstract Path planning is a fundamental component in robotics and game artificial intelligence that considerably influences the motion efficiency of robots and unmanned aerial vehicles, as well as the realism and immersion of virtual environments. However, traditional algorithms are often limited to single-objective optimization and lack real-time adaptability to dynamic environments. This study addresses these limitations through a proposed real-time dynamic multiobjective (RDMO) path-planning algorithm based on an enhanced A* framework. The proposed algorithm employs a queue-based structure and composite multiheuristic functions to dynamically manage game tasks and compute optimal paths under changing-map-connectivity conditions in real… More >

Jie He, Dongmei Zhao, Tao Liu^*, Qingfeng Zou, Jian’an Xie

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2733-2749, 2025, DOI:10.32604/cmc.2025.065205 - 03 July 2025

Abstract Robot navigation in complex crowd service scenarios, such as medical logistics and commercial guidance, requires a dynamic balance between safety and efficiency, while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns. This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization, aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment. We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining… More >

Bin Jiang¹, Houbin Wang^2,*

Energy Engineering, Vol.122, No.5, pp. 2001-2057, 2025, DOI:10.32604/ee.2025.062765 - 25 April 2025

Abstract Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality, strong coupling, nonlinearity, and non-convexity, a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper. The algorithm is based on external elite archive and Pareto dominance, and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm. Average entropy and cubic chaotic mapping initialization strategies are proposed to increase population diversity. In the proposed method, we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.… More >

Fengju Zhang¹, Kai Zhu^2,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2353-2372, 2025, DOI:10.32604/cmc.2024.058944 - 17 February 2025

Abstract The Internet of Vehicles (IoV) has become an important direction in the field of intelligent transportation, in which vehicle positioning is a crucial part. SLAM (Simultaneous Localization and Mapping) technology plays a crucial role in vehicle localization and navigation. Traditional Simultaneous Localization and Mapping (SLAM) systems are designed for use in static environments, and they can result in poor performance in terms of accuracy and robustness when used in dynamic environments where objects are in constant movement. To address this issue, a new real-time visual SLAM system called MG-SLAM has been developed. Based on ORB-SLAM2,… More >

Ghulam E Mustafa Abro^1,*, Ayman M Abdallah^1,2, Faizan Zahid³, Saleem Ahmed⁴

Intelligent Automation & Soft Computing, Vol.40, pp. 99-123, 2025, DOI:10.32604/iasc.2025.060364 - 23 January 2025

Abstract This review synthesises and assesses the most recent developments in Unmanned Aerial Vehicles (UAVs) and swarm robotics, with a specific emphasis on optimisation strategies, path planning, and formation control. The study identifies key methodologies that are driving progress in the field by conducting a comprehensive analysis of seven critical publications. The following are included: sensor-based platforms that facilitate effective obstacle avoidance, cluster-based hierarchical path planning for efficient navigation, and adaptive hybrid controllers for dynamic environments. The review emphasises the substantial contribution of optimisation techniques, including Max-Min Ant Colony Optimisation (MMACO), to the improvement of convergence… More >

Mustafa Mohammed Alhassow^1,*, Oguz Ata², Dogu Cagdas Atilla¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 749-771, 2024, DOI:10.32604/cmc.2024.055592 - 15 October 2024

Abstract This study investigates robot path planning for multiple agents, focusing on the critical requirement that agents can pursue concurrent pathways without collisions. Each agent is assigned a task within the environment to reach a designated destination. When the map or goal changes unexpectedly, particularly in dynamic and unknown environments, it can lead to potential failures or performance degradation in various ways. Additionally, priority inheritance plays a significant role in path planning and can impact performance. This study proposes a Conflict-Based Search (CBS) approach, introducing a unique hierarchical search mechanism for planning paths for multiple robots.… More >

Jingtong Peng^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2275-2291, 2023, DOI:10.32604/csse.2023.039272 - 28 July 2023

Abstract When applied to Unmanned Aerial Vehicles (UAVs), existing Simultaneous Localization and Mapping (SLAM) algorithms are constrained by several factors, notably the interference of dynamic outdoor objects, the limited computing performance of UAVs, and the holes caused by dynamic objects removal in the map. We proposed a new SLAM system for UAVs in dynamic environments to solve these problems based on ORB-SLAM2. We have improved the Pyramid Scene Parsing Network (PSPNet) using Depthwise Separable Convolution to reduce the model parameters. We also incorporated an auxiliary loss function to supervise the hidden layer to enhance accuracy. Then… More >

Fatih Aydemir¹, Aydin Cetin^2,*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 215-230, 2023, DOI:10.32604/csse.2023.031116 - 16 August 2022

Abstract Dynamic area coverage with small unmanned aerial vehicle (UAV) systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process. Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved. In this paper, we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems. The proposed decentralized decision-making dynamic area coverage (DDMDAC) method utilizes reinforcement learning (RL) where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable… More >

Chanho Park^1,2, Hyunwoo Cho¹, Sangheon Park¹, Sung-Uk Jung¹, Suwon Lee^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 529-549, 2022, DOI:10.32604/cmes.2022.019214 - 24 January 2022

Abstract Recently, simultaneous localization and mapping (SLAM) has received considerable attention in augmented reality (AR) libraries and applications. Although the assumption of scene rigidity is common in most visual SLAMs, this assumption limits the possibilities of AR applications in various real-world environments. In this paper, we propose a new tracking system that integrates SLAM with a marker detection module for real-time AR applications in static and dynamic environments. Because the proposed system assumes that the marker is movable, SLAM performs tracking and mapping of the static scene except for the marker, and the marker detector estimates… More >

Raja Jarray¹, Mujahed Al-Dhaifallah^2,*, Hegazy Rezk^3,4, Soufiene Bouallègue^1,5

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 >