Search Results - (( mobile optimization path algorithm ) OR ( parameter optimization based algorithm ))
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…Due to the importance of global path planning in mobile robot navigation systems, the research presented herewith focused on the optimization problem of path planning for mobile robots. …”
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Thesis -
2
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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3
Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Proceedings -
4
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2022“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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10
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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11
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments
Published 2013“…The recent development of its variant: RRT* is considered as a major breakthrough as it makes it possible to achieve optimality in paths planning. However, its limitations include the infinite time it takes to reach the optimal solution and a very slow rate of convergence. …”
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Optimised multi-robot path planning via smooth trajectory generation
Published 2024“…Particle swarm optimization (PSO) outperforms conventional methods like artificial potential fields (APF), the Dijkstra algorithm, and the A* algorithm in path planning for mobile robots. …”
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Final Year Project / Dissertation / Thesis -
15
Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network
Published 2020“…The proposed Quality of Path QoP metric is incorporated into the modified relay selection algorithm, which improves the efficiency of relay selection mechanism to find optimal path with high link quality. …”
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16
Efficient and scalable ant colony optimization based WSN routing protocol for IoT
Published 2020“…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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A novel bio-inspired routing algorithm based on ACO for WSNs
Published 2019“…A novel approach of ant colony optimization (ACO) algorithm for discovering the optimum route for information transmission in the WSNs is proposed here for optimization and enhancement. …”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
Published 2015“…One of the solutions to this problem is by using mobile robots with concern on exploration algorithm for mobile robot. …”
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Thesis -
19
Resource Efficient For Hybrid Fiber-Wireless Communications Links In Access Networks With Multi Response Optimization Algorithm
Published 2021“…This work proposes a Multi response Optimization (MO) algorithm, named MO-LMMHOWAN that apply in Last Mile Mobile Hybrid Optical Wireless Access Network (LMMHOWAN). …”
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Comparison of DSR, AODV and DSDV routing protocols in mobile ad-hoc networks: A survey
Published 2014“…A mobile ad hoc network (MANET) is a collection of mobile nodes that is connected through a wireless medium forming rapidly changing topologies.Mantes are infrastructure less and can be set up anytime, anywhere.We have conducted survey of protocol properties of various MANET routing algorithms and analyzed them.The routing algorithms considered are classified into three categories proactive (table driven) , reactive (on demand) and Hybrid protocol.The algorithms considered are Dynamic Source Routing (DSR), Ad-hoc On-Demand Distance Vector Routing (AODV) and Destination sequence Vector (DSDV) have been proposed to solve the multi hop routing problem in Ad-hoc networks.The comparison among three routing protocols are based on the various protocol property parameters such as Routing overhead, packet delivery ratio, end-to-end delay, path optimality, and throughput are some metrics commonly used in the comparisons.…”
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