80 research outputs found
Odor Localization using Gas Sensor for Mobile Robot
This paper discusses the odor localization using Fuzzy logic algorithm. The concentrations of the source that is sensed by the gas sensors are used as the inputs of the fuzzy. The output of the Fuzzy logic is used to determine the PWM (Pulse Width Modulation) of driver motors of the robot. The path that the robot should track depends on the PWM of the right and left motors of the robot. When the concentration in the right side of the robot is higher than the middle and the left side, the fuzzy logic will give decision to the robot to move to the right. In that condition, the left motor is in the high speed condition and the right motor is in slow speed condition. Therefore, the robot will move to the right.  The experiment was done in a conditioned room using a robot that is equipped with 3 gas sensors. Although the robot is still needed some improvements in accomplishing its task, the result shows that fuzzy algorithms are effective enough in performing odor localization task in mobile robot
Data Optimization on Multi Robot Sensing System with RAM Based Neural Network Method
Monitoring the environment activities is an attractive Abstract— Monitoring the environment activities is an attractive thing for development. That is because the human life would affect the surrounding environtment. There\u27s a lot of research of environment has been done, one of those is the changes of air quality in urban areas. To measure the level of air quality, the data and information from field measurements and laboratory analysis result was needed. This paper review the research result that focus on sensor data processing in multi robot using RAM based neural network. There are 11 pattern input data were processed by temperature data optimization from 250C until 350C, humadity data from 20% until 60% and gas data from 350ppm until 450ppm. The obtained result is from 8 bits and 9 bits become 6 bits in certain level with optimazion percentage is25% and 33,3%. This result effect to the computationan load, it\u27s become more simple, the execution time and data communication becomes faster
Optimal Gas Sensors Arrangement in Odor Searching Robot
This paper presents an analysis of an optimal
sensor arrangement in Odor Searching Robot (OSR). 5 gas
sensors integrated in OSR can help the OSR to navigate to the
source. Since low cost, low computation and robust robot is
preferred in swarm robot application, the OSR, as an
individual robot of swarm in this study, is designed to be able
to switch into the mode 3 or the mode 5 in order to analyze the
optimal distance of the gas sensors arrangement that can be
integrated in the OSR. By knowing the optimal sensor
arrangement, the low cost and or the low computation OSR
can be established. Algorithms of fuzzy logic for 3 and 5 gas
sensors are tested in open environment. The concentration of
gas is used as the input of the fuzzy logic. The robot uses the
concentration, as its parameters in determining which way that
it should take. From this research, it can be concluded that
there was no significant difference between using 3 gas sensors
or 5 gas sensors
Data Optimization on Multi Robot Sensing System with RAM based Neural Network Method
Monitoring the environment activities is an attractive Abstract— Monitoring the environment activities is an attractive thing for development. That is because the human life would affect the surrounding environtment. There’s a lot of research of environment has been done, one of those is the changes of air quality in urban areas. To measure the level of air quality, the data and information from field measurements and laboratory analysis result was needed. This paper review the research result that focus on sensor data processing in multi robot using RAM based neural network. There are 11 pattern input data were processed by temperature data optimization from 250C until 350C, humadity data from 20% until 60% and gas data from 350ppm until 450ppm. The obtained result is from 8 bits and 9 bits become 6 bits in certain level with optimazion percentage is25% and 33,3%. This result effect to the computationan load, it’s become more simple, the execution time and data communication becomes faster.  Â
Odor Localization Sub Tasks: A Survey
This paper discusses about the sub tasks of odor localization research. Three steps of odor localization, i.e. Plume finding, plume tracking/tracing, and source declaration are explained. The difficulty of plume finding is discussed. Farrell’s Filamentous and Pseudo-Gaussian plume models that have been analyzed by previous researcher are presented. Some approaches used in plume tracking/tracing based on advection/turbulent and the estimation of odors’ distribution are provided. The advantages of source declaration are showed. Some problems occur in plume finding become a great consideration for the future research
Odor Localization using Gas Sensor for Mobile Robot
This paper discusses the odor localization using
Fuzzy logic algorithm. The concentrations of the source that is
sensed by the gas sensors are used as the inputs of the fuzzy.
The output of the Fuzzy logic is used to determine the PWM
(Pulse Width Modulation) of driver motors of the robot. The
path that the robot should track depends on the PWM of the
right and left motors of the robot. When the concentration in
the right side of the robot is higher than the middle and the left
side, the fuzzy logic will give decision to the robot to move to
the right. In that condition, the left motor is in the high speed
condition and the right motor is in slow speed condition.
Therefore, the robot will move to the right. The experiment
was done in a conditioned room using a robot that is equipped
with 3 gas sensors. Although the robot is still needed some
improvements in accomplishing its task, the result shows that
fuzzy algorithms are effective enough in performing odor
localization task in mobile robot
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