At the University of Nevada, Reno, researchers have developed an innovative solution to address labor shortages and improve precision in soft fruit cultivation. The SARAL-Bot, a robot designed for tunnel or greenhouse environments, is set to revolutionize the way growers manage their crops.
The SARAL-Bot is engineered to autonomously navigate between raised beds, identifying and removing withered or diseased leaves with a robotic arm. This automation of repetitive manual trimming tasks offers significant labor savings and allows growers to focus on other critical aspects of their operations. The robot’s ability to work around the clock ensures that time-consuming tasks are consistently addressed, even outside of standard working hours.
One of the key advantages of the SARAL-Bot is its precision in detecting and removing diseased leaves. Early intervention helps prevent the spread of fungal infections and other plant health issues, ultimately leading to healthier crops and improved yields. The robot’s sensors collect valuable data on leaf color, blooming stage, moisture stress, and plant development. This information can be integrated into crop registration systems or used with site-specific crop management tools, providing growers with actionable insights to optimize their cultivation practices.
The SARAL-Bot’s mobility and precision are facilitated by its unique design. Equipped with four aluminum mecanum wheels featuring rubber grippers, the robot can turn in place and move accurately even on plastic mulch. Navigation is achieved through a RealSense 3D camera and RTAB-SLAM, an open-source mapping and localization system. A liftable camera at the rear scans the crop canopy, and once abnormal leaves are detected, a five-degree-of-freedom robotic arm with a gripper and small blade carefully removes them without disturbing healthy foliage.
The robot operates on open-source ROS 2 software and is powered by three separate battery units, ensuring continuous operation with minimal downtime. In test trials, the SARAL-Bot demonstrated a positioning accuracy of about 2 centimeters and a leaf detection accuracy exceeding 95%, even under variable light conditions. The robot can prune one leaf approximately every 12 seconds, and a full battery charge allows for about two hours of continuous operation. The design also supports a quick battery swap in just 30 seconds, further minimizing downtime.
The SARAL-Bot is particularly beneficial for growers facing labor shortages during trimming season. It offers a pathway to automation without the need for a complete overhaul of existing cropping systems. The prototype was built on a relatively low budget, with an estimated unit cost of around €35,000 ($37,500) for small-scale production. The developers are now seeking grower partners and industry collaborators for commercial pilot trials in standard 120 cm-wide strawberry beds.
As the agricultural industry continues to evolve, innovations like the SARAL-Bot play a crucial role in addressing labor challenges and enhancing precision in crop management. By automating repetitive tasks and providing valuable data, the SARAL-Bot empowers growers to make informed decisions and improve overall crop health and productivity. The upcoming pilot trials will be a significant step in validating the robot’s effectiveness in real-world scenarios, paving the way for broader adoption in the agritech sector.