Search Results - (( simulation optimization sensor algorithm ) OR ( motion optimization _ algorithm ))
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1
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…The simulation and comparison results indicate the superiority of the proposed algorithm. …”
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2
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
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Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms
Published 2012“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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4
Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing
Published 2015“…The Pareto optimal set of solutions are the smallest SAWR with least climbing ability to biggest SAWR with the best climbing motion. …”
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5
PID-PSO DC motor position controller design for ankle rehabilitation system
Published 2023“…The transfer function is a model in Matlab software to validate the performance of the control system through simulation compared with real-time experiments. Next, the control algorithms are proposed to design and implement the Proportional-Integral-Derivative (PID) with Particle Swarm Optimization (PSO) controller technique for optimal Proportional (Kp), Integral (Ki) and Derivative (Kd) gains. …”
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6
Error driven Fuzzy Logic Controller (FLC) for spherical mobile robot: simulation & experimental performance analysis
Published 2022“…The challenge for spherical mobile robot falls within control algorithm aspects, where it is nonlinear and highly under-actuated increases the difficulties to control its motion. …”
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Proceeding Paper -
7
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…In addition, a simple procedure is proposed to determine the optimal solution and predict the correlation factor and the frequency of the damaged communication tower by using the particle swarm optimization (PSO) method. …”
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8
Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…The durability and movement capability of the structure were evaluated through Static analysis (simulation), and validate it through the Load test and Motion capture analysis. …”
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9
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks
Published 2024“…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
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Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space
Published 2015“…The simulated robot is equipped with a sonar sensor and several infrared sensors on its chassis. …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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13
Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior
Published 2023“…This paper proposes a sensor node placement algorithm that utilizes a new biologically inspired optimization algorithm that imitates the behaviour of territorial predators in marking their territories with their odours known as Territorial Predator Scent Marking Algorithm (TPSMA). …”
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Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement
Published 2023Conference Paper -
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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16
Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network
Published 2014“…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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17
Multi-objective biological mimicry optimization algorithm for WSN sensor node placement
Published 2023Conference Paper -
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Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks
Published 2023“…Keywords: anchor nodes; metaheuristic optimization algorithm; node localization; tent chaotic mapping; wireless sensor networks…”
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Wireless sensor network deployment performance based on FOA, PSO and TPSMA / Nurhidayah Kamal Akbar, Husna Zainol Abidin, and Ahmad Ihsan Mohd Yassin
Published 2019“…This paper compares the random deployment with other two algorithms known as Fruit Fly Optimization (FOA) and Particles Swarm Optimization (PSO) Territorial Predator Scent Marking Algorithm (TPSMA) to solve the coverage hole problem. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
Published 2015“…We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. …”
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