Search Results - (( motion optimization path algorithm ) OR ( using optimization path algorithm ))
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article -
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization
Published 2018“…To choose a best solution among many possible solutions, meta-heuristic optimizations, namely, a Genetic Algorithm (GA), a Particle Swarm Optimization (PSO), and a Grey Wolf Optimizer (GWO) will be employed with an optimization objective to minimize a joint angle travelling distance. …”
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Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization
Published 2018“…To choose a best solution among many possible solutions, meta-heuristic optimizations, namely, a Genetic Algorithm (GA), a Particle Swarm Optimization (PSO), and a Grey Wolf Optimizer (GWO) will be employed with an optimization objective to minimize a joint angle travelling distance. …”
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Intelligent motion planning of a mobile robot by using convolutional neural network / Siti Asmah Abdullah
Published 2019“…By the path reference created by A* algorithm the robot is capable in optimizing its path to reach the designated destination. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation
Published 2017“…The present algorithm exhibits attractive features such as high optimality, high stability, low running cost and zero failure rates. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Articulated robots motion planning using foraging ant strategy
Published 2008“…However, the performance of this method is sub-optimal in terms of the number of configurations generated, length of path, amount of collision checking and computational time. …”
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Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system
Published 2019“…Furthermore, a heuristic dataset generator is implemented to provide enough data for the ANFIS using a randomized procedure. The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2006“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Theoretical study of elliptic drum of vertical spindle cotton picker
Published 2025“…An analytical expression is obtained, and a convenient calculation algorithm is developed to automate the investigation of the influence of the dimensions of drum mechanism parts onthe directional path shape and its dimensions. …”
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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…These robots are commonly operated using knobs, joysticks or wearable motion sensors. …”
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Runtime reduction in optimal multi-query sampling-based motion planning
Published 2023“…Algorithms; Dispersions; Manufacture; Query processing; Robotics; High-dimensional; Low dispersions; Optimal solutions; Path length; Planning tasks; Sampling-based; Sampling-based algorithms; Sampling-based motion planning; Motion planning…”
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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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