Agriculture is humankind’s oldest and still its most important economic activity, providing the food, feed, fiber, and fuel necessary for our survival. Robotics and automation can play a significant role in society meeting 2050 agricultural production needs. For six decades robots have played a fundamental role in increasing efficiency and reducing the cost of industrial production and products. In the past twenty years, a similar trend has started to take place in agriculture, with GPS- and vision-based self-guided tractors and harvesters already being available commercially. More recently, farmers have started to experiment with autonomous systems that automate or augment operations such as pruning, thinning, and harvesting, as well as mowing, spraying, and weed removal. The mission of the AGRicultural INteligent Systems (AGRINS) Laboratory is to promote research, development, innovation, and standardization in robotics and automation to enable safe, efficient, and economical agricultural production. AGRINS Lab. is a forum where academic and industrial researchers and engineers meet to advance the state-of-the-art in sensing, mobility, manipulation, and management technologies applied to the production of grains, fruits, vegetables, nuts, and horticulture and nursery crops. We welcome anyone interested in this exciting area to join and contribute to our mission.

Key objectives

The laboratory mission is to research to develop new field robotics and intelligent systems theories and methods and apply them in agriculture.

We are committed to developing technologies in four core areas:

  • Design and development of intelligent systems for agricultural use
  • Dynamic modeling of these intelligent systems
  • Planning to automate them
  • Intelligent and automatic control of them to perform tasks

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Swing Pruning Cutter along Power Lines

This research presents a solution to prune trees near the power lines using a robotic system. Tree branches have more growth toward power lines and then, they contact power towers. This contact is one of the major reasons which interrupt power transmission services. To control the growth of trees branches along the power lines, the pruning task must be regularly done. To this end, an autonomous robotic system can be considered. Using this system, the accuracy and quickness of operation are also obtained.

Dredger Robot for Irrigation Canals

This research presents a solution for dredging irrigation canals using a robotic system. Irrigation canals are artificial linear structures in fields that are used for water transition. One important problem in this issue is the waste materials flowing inside the water causing a blockage against the mainstream and then, this can affect the actual capacity of the canal. The removal operation could be conducted using chemical, biological, ecological, and physical methods using complex systems. So, a robotic system as such a complex system is proposed and designed for dredging irrigation canals.

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A Coaxial Quadrotor Flying Robot

The design and fabrication procedure of a new Octorotor Miniature Aerial Vehicle (MAV) is presented. This rotorcraft setup can act as an autonomous robot in outdoor environments to carry and move high payloads, and can thus also be used in object manipulation tasks. It should be noted that the presented MAV is based on the Quadrotor principle – but expands upon it, hence it is named Octorotor. The system design, dynamic modeling, control system design, and its implementation for such flying robots are elaborated in this research. Since the MAV flies in outdoor environments, it additionally has to cope with windy conditions. Hence, the stabilization control scheme is considered along the lines of usual PID controllers, however, the attitude controller as well as the inner and outer control loops are fully studied.

The Most Effective for Cooperative Object Manipulation

Cooperative manipulation occurs when manipulators are mechanically coupled to the object being manipulated and the manipulators may not be treated as an isolated system. The most important and basic impedance control strategies for an assumed cooperative object manipulation task are the Augmented Object Model (AOM) control and the Multiple Impedance Controller (MIC) which are founded based on the Impedance Control (IC), where the former is designed based on the object movement, and the latter is designed based on the whole robot movement. Thus, the basis of these two algorithms is fully studied.

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