Automated harvesting by a dual-arm fruit harvesting robot

Abstract

Abstract In this study, we propose a method to automate fruit harvesting with a fruit harvesting robot equipped with robotic arms. Given the future growth of the world population, food shortages are expected to accelerate. Since much of Japan’s agriculture is dependent on imports, it is expected to be greatly affected by this upcoming food shortage. In recent years, the number of agricultural workers in Japan has been decreasing and the population is aging. As a result, there is a need to automate and reduce labor in agricultural work using agricultural machinery. In particular, fruit cultivation requires a lot of manual labor due to the variety of orchard conditions and tree shapes, causing mechanization and automation to lag behind. In this study, a dual-armed fruit harvesting robot was designed and fabricated to reach most of the fruits on joint V-shaped trellis that was cultivated and adjusted for the robot. To harvest the fruit, the fruit harvesting robot uses sensors and computer vision to detect and estimate the position of the fruit and then inserts end-effectors into the lower part of the fruit. During this process, there is a possibility of collision within the robot itself or with other fruits depending on the position of the fruit to be harvested. In this study, inverse kinematics and a fast path planning method using random sampling is used to harvest fruits with robot arms. This method makes it possible to control the robot arms without interfering with the fruit or the other robot arm by considering them as obstacles. Through experiments, this study showed that these methods can be used to detect pears and apples outdoors and automatically harvest them using the robot arms.

Keywords

• Harvesting robot
• Robot manipulation
• Deep learning