2016
DOI: 10.1515/ata-2016-0004
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Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics

Abstract: The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot's behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our… Show more

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Cited by 10 publications
(4 citation statements)
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“…The fuzzy sets theory is based on a membership degree of elements to the set. The value of each element in set is between 0 and 1 (Cviklovič et al, 2016). Table 2 shows selected linguistic variables for the fuzzy controller observed.…”
Section: Comparison Of Control Algorithms By Simulating Power Consumption Of Differential Drive Mobile Robot Motion Control In Vineyard Rmentioning
confidence: 99%
See 1 more Smart Citation
“…The fuzzy sets theory is based on a membership degree of elements to the set. The value of each element in set is between 0 and 1 (Cviklovič et al, 2016). Table 2 shows selected linguistic variables for the fuzzy controller observed.…”
Section: Comparison Of Control Algorithms By Simulating Power Consumption Of Differential Drive Mobile Robot Motion Control In Vineyard Rmentioning
confidence: 99%
“…In addition to the robot's kinematics, this model includes a dynamic part describing the dependence of electric currents on the load and wheel velocities from the supplied motor voltages, respecting the dynamics of engine, construction, geometry and other parameters of chassis and engines. Parameters for the robot model observed are stated in Table 1 and were selected to approximate a real mobile robot EN20 described by Cviklovič et al (2016).…”
Section: Navigation Algorithmmentioning
confidence: 99%
“…Multiple researches developed new robots for cultivation of crops, such as apple (Lv et al, 2019), orange (Garner et al, 2006), tomato (Li et al, 2019), strawberry (Khosro Anjom and Vougioukas, 2019;Aliasgarian et al, 2015), kiwifruit (Williams et al, 2019), grape (Luo et al, 2018), heavy-weight crops (Roshanianfard et al, 2018;Kamata et al, 2018;Roshanianfard andNoguchi, 2017, 2018b;Roshanianfard, 2018), and pumpkin (Roshanianfard andNoguchi, 2016, 2018a;Roshanianfard et al 2020Roshanianfard et al , 2021. Certain researchers applied smart systems on commercialized platforms, such as tractors (Wang and Noguchi, 2019), combines (Zhang et al, 2013), boats (Liu et al, 2017), all-terrain-vehicles, utility vehicles (Cviklovič et al, 2016), drones (Kashkarov et al, 2018), and drones for digital farming applications (Roshanianfard et al, 2019).…”
mentioning
confidence: 99%
“…The precision reference voltage sources (RVS) are broadly used. However, their application is usually needed in creation of the analogue-to-digital and digital-to-analogue converters (ADC and DAC), which are a part of an inventory of electric devices, control systems power supply, automated process control systems of both production and agricultural objects (Cviklovič et al, 2016;Hsu et al, 2013).…”
mentioning
confidence: 99%