Button mushrooms (Agaricus bisporus) are picked by hand individually, which is time consuming and labor intensive. Robotic harvesting is an alternative method to address this issue. Picking force and motion are critical for developing an effective robotic mushroom picking end-effector. Mushrooms are typically growing in a cluster. Conventional manual mushroom picking comprises a combination motion of twisting, bending, and lifting. To find an effective and simple picking method for robotic harvesting, a series of tests were conducted to compare the picking force and motion among the conventional method and three simplified methods, i.e., bending, twisting, and lifting. A sensor system was developed to measure the picking force and motion with three force sensors and an inertial measurement unit (IMU). The results showed that the conventional picking method required the most orientation changes to detach a mushroom, which could generate complexity for designing a robotic end-effector with the equivalent dexterity. The bending method was simple and effective with the least force compared to the other three methods, with the operation time, detachment angle, and peak force of 0.9 ± 0.5 s,13.6 ± 6.7°, and 3.3 ± 2.4 N respectively. A vacuum picking end-effector was then designed and evaluated with the three simplified methods. The results of picking end-effector evaluation also indicated that the bending motion achieved the best performance, with the picking rate of 100% for these target mushrooms, especially for the clustered ones. The developed picking end-effector can be further improved for an automatic mushroom picking system in the future.
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science
- Computer Science Applications