TY - GEN
T1 - Fruit mapping mobile robot on simulated agricultural area in Gazebo simulator using simultaneous localization and mapping (SLAM)
AU - Habibie, Novian
AU - Nugraha, Aditya Murda
AU - Anshori, Ahmad Zaki
AU - Ma'sum, M. Anwar
AU - Jatmiko, Wisnu
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Precision Agriculture using mobile robot aimed to increase efficiency and quality of crops treatment and monitoring, since robot can produce better result in term of data quality and accuracy than manual treatment by human labor. Limited by technology development and complexity of agricultural environment, precision agriculture nowadays is still not fully-autonomous, but partially autonomous to handle more simpler - but need high accuracy - tasks. Some of them is mapping and monitoring task. This research proposed a method for generating map in simulated agricultural area using Simultaneous Localization And Mapping (SLAM), by generating grid-based/volumetric map using fine-tuned SLAM-Gmapping algorithm and combine it with properties/informations obtained from each detected crops/plants using fruit detection with visual sensor and tree location detection using 2D laser scanner sensor. Experiment conducted in simulation environment Gazebo and Robot Operation System (ROS) for scenario of simulated fruit mapping in apple farm, and give a good result with a good accuracy.
AB - Precision Agriculture using mobile robot aimed to increase efficiency and quality of crops treatment and monitoring, since robot can produce better result in term of data quality and accuracy than manual treatment by human labor. Limited by technology development and complexity of agricultural environment, precision agriculture nowadays is still not fully-autonomous, but partially autonomous to handle more simpler - but need high accuracy - tasks. Some of them is mapping and monitoring task. This research proposed a method for generating map in simulated agricultural area using Simultaneous Localization And Mapping (SLAM), by generating grid-based/volumetric map using fine-tuned SLAM-Gmapping algorithm and combine it with properties/informations obtained from each detected crops/plants using fruit detection with visual sensor and tree location detection using 2D laser scanner sensor. Experiment conducted in simulation environment Gazebo and Robot Operation System (ROS) for scenario of simulated fruit mapping in apple farm, and give a good result with a good accuracy.
UR - http://www.scopus.com/inward/record.url?scp=85050489647&partnerID=8YFLogxK
U2 - 10.1109/MHS.2017.8305235
DO - 10.1109/MHS.2017.8305235
M3 - Conference contribution
AN - SCOPUS:85050489647
T3 - MHS 2017 - 28th 2017 International Symposium on Micro-NanoMechatronics and Human Science
SP - 1
EP - 7
BT - MHS 2017 - 28th 2017 International Symposium on Micro-NanoMechatronics and Human Science
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2017
Y2 - 3 December 2017 through 6 December 2017
ER -