Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 01, 2022 - June 04, 2022
Precision agriculture practices play a pivotal role in improving the crop yield and optimizing maximum output for quality products and profit. In recent years, mobile robots have been actively employed to take several jobs in the agriculture field, such as monitoring farmland and tracking crop growth over time. Recent advances in sensor technology, IoT, and small embedded systems have opened new research areas in precision agriculture. However, testing and deploying autonomous robots in an actual field environment is challenging, expensive, and demands much time and training. In addition, sensor failure, algorithm tuning, and new sensor integration can cause unwanted interruptions during the monitoring and tracking process. Simulation-based environments for training and testing can be an effective way to leverage the best of both sides. We developed an open-source ROS-based simulation model with a mobile robot for mapping, navigation, and monitoring the crop to solve this problem. We present our simulation test in a largely virtual field and show the results for autonomous navigation in an outdoor field environment.
