Design and Evaluation of End Effectors for a Vacuum-Based Robotic Apple Harvester

Abstract

HighlightsA critical torque of 0.257 N-m is required to detach 95% of apples, when the preferred twist picking mode is used.New silicone-based end effectors performed much better than the original, non-conformable end effector.The straight end effector had the best overall picking performance with 87% picking success rate.The new vacuum-based harvesting robot looks promising for automated harvesting of apples.Abstract. The end effector plays a critical role in fruit picking by a robotic fruit harvesting system. A newly developed vacuum-based robotic apple harvesting system, using the twist-and-pull fruit picking method, has shown promise in picking fruit from clusters and navigating through the tree canopies. The robot’s original thin foam end effector failed to achieve acceptable picking performance because it was unable to conform to fruit of different sizes and thus could not generate sufficient suction forces needed to detach fruit. This research was therefore aimed at developing new end effectors to greatly enhance the robot’s fruit picking performance. Field manual pulling and twisting experiments for three varieties of apples were conducted, and the critical pulling or suction force and twisting torque needed to detach 95% of apples were determined to be 28.3 N and 0.257 N-m (equivalent to a pulling force of 21.0 N for the current robot’s configuration), respectively. Three new silicone-based end effectors of different geometries (denoted as “Straight”, “Bellow” and “Curved”) were designed and fabricated, and they were evaluated in lab and field experiments. Results showed that the three new end effectors performed significantly better than the original, unconformable end effector based on multiple performance metrics, including vacuum pressure, overall picking success rate, picking rate by the rotation mechanism, and fruit attachment orientation. The “Straight” end effector performed consistently better than the other two new end effectors; it had 87% overall picking success rate, 65% success rate by the rotation mechanism alone, and 89% success rate when the middle section or cheek of fruit attached to the end effector. With further improvements, the “Straight” end effector should meet the apple picking performance requirement for the new vacuum-based robotic harvesting system. Keywords: Apple, End Effector, Fruit, Harvest, Robotics, Vacuum.

Design and experimental study of the end-effector for broccoli harvesting

“…The mass of the rod is transformed by the linear density and the length of the rod so that the external driving force P is a function of only the length of the three rods. The mass conversion formula is m = λl (12) λ where, is the linear density of the rod, and the linear density of each rod is listed in Table 5. According to the optimization function and constraint conditions, the genetic algorithm function in the MATLAB library is used to optimize the rod length.…”

“…The development of agricultural harvesting robots provides a material basis for improving production efficiency, changing the mode of development and enhancing the comprehensive agricultural production capacity [6][7][8][9] . As an important part of agricultural harvesting robots, the harvesting performance of harvesting endeffectors has an important influence on the overall efficiency and performance of harvesting robots [10][11][12] . Therefore, the development and design of an end-effector is of great significance to broccoli harvesting robots.…”

“…The cutting-off type is achieved by wrapping the fruitage and using the cutting tool to cut the stem to achieve harvesting. Li et al [12] proposed a fruit-closing apple picking end-effector, and the blade and the tooth-shaped fruit-closing device were used to cut the stem to achieve harvesting. Wang et al [15] proposed a bite-type endeffector for citrus picking by simulating snake beak swallowing, which realized citrus picking at different stem angles.…”

Robotic Multi-Boll Cotton Harvester System Integration and Performance Evaluation

“…The control systems, navigation algorithm, and objection detection algorithms utilized in various agricultural and non-agricultural robots [5][6][7][8][9][10][11][12][13] can also be adapted for cotton harvesting robots. Several research articles have focused on distinct sub-components of a robotic cotton harvesting system, such as the development of a cotton boll detection model [14][15][16][17][18][19], navigation and path planning algorithms [20][21][22][23][24][25], and end-effector designs [26][27][28][29][30].…”