Research and development of autonomous mobile robotic solutions that can perform
several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots …

This paper surveys the supportive technologies currently available for ground mobile robots
used for autonomous map** in agriculture. Unlike previous reviews, we describe state-of …

Computer vision is a key technique to make agricultural machinery smart. Deep neural
network has achieved great success in computer vision. How to use it at a small size, low …

Deep Learning has been successfully applied to image recognition, speech recognition, and
natural language processing in recent years. Therefore, there has been an incentive to …

The agricultural sector plays a fundamental role in our society, where it is increasingly
important to automate processes, which can generate beneficial impacts in the productivity …

During the last decades, researchers have developed novel computing methods to help
viticulturists solve their problems, primarily those linked to yield estimation of their crops …

Smart agricultural machinery is emerging as the future trend for field robots, and the fully
automatic robot has a great application prospect. However, it is a big challenge for robots to …

Mobile robotics in forests is currently a hugely important topic due to the recurring
appearance of forest wildfires. Thus, in-site management of forest inventory and biomass is …

Develo** ground robots for agriculture is a demanding task. Robots should be capable of
performing tasks like spraying, harvesting, or monitoring. However, the absence of structure …

In this paper, a Model Predictive Control (MPC)-based approach for vineyard spraying is
presented, able to adapt to different vine row structures and suitable for real-time …