Evaluation of End Effectors for Robotic Harvesting of Mango Fruit

Abstract

The task of gripping has been identified as the rate-limiting step in the development of tree-fruit harvesting systems. There is, however, no set of universally adopted ‘specifications’ with standardized measurement procedures for the characterization of gripper performance in the harvest of soft tree fruit. A set of metrics were defined for evaluation of the performance of end effectors used in soft tree-fruit harvesting based on (i) laboratory-based trials using metrics termed ‘picking area’, which was the cross-sectional area in a plane normal to the direction of approach of the gripper to the fruit in which a fruit was successfully harvested by the gripper; ‘picking volume’, which was the volume of space in which fruit was successfully harvested by the gripper; and ‘grasp force’, which was the peak force involved in removing a fruit from the grasp of a gripper; (ii) orchard-based trials using metrics termed ‘detachment success’ and ‘harvest success’, i.e., the % of harvest attempts of fruit on tree (of a given canopy architecture) that resulted in stalk breakage and return of fruit to a receiving area, respectively; and (iii) postharvest damage in terms of a score based on the percentage of fruit and severity of the damage. Evaluations were made of external (skin) damage visible 1 h after gripping and of internal (flesh) damage after ripening of the fruit. The use of the metrics was illustrated in an empirical evaluation of nine gripper designs in the harvest of mango fruit in the context of fruit weight and orientation to the gripper. A design using six flexible fingers achieved a picking area of ~150 cm2 and a picking volume of 467 cm3 in laboratory trials involving a 636 g phantom fruit as well as detachment and harvest efficiency rates of 74 and 65%, respectively, in orchard trials with no postharvest damage associated with the harvest of unripe fruit. Additional metrics are also proposed. Use of these metrics in future studies of fruit harvesting is recommended for literature–performance comparisons.

Design and Simulation of Three-Degree-of-Freedom Wrist Structure of Picking Manipulator

“…Yu et al, (2022), developed a tomato picking robot with autonomous recognition capability and soft three-finger gripping jaws capable of non-destructive picking. To evaluate the performance of end effectors used in soft tree fruit harvesting, Goulart et al, (2023), has defined a set of measurement standards. Stevanović et al, (2023), designed a composite 6-DOF robot harvester with telescopic robot arm for plum farmyards, it can carry the picked fruits to the designated location.…”

“…Combined with Equation(7)(8), known lKM is 31, it can be seen that the difference in the length change of tendon ropes Ⅳ and V is affected by  ,  and KO l , and is also not constant to zero. Establish a function for the maximum value of the difference in tendon rope changes during wrist rotation,…”

A Visual Method of Hydroponic Lettuces Height and Leaves Expansion Size Measurement for Intelligent Harvesting

“…The end effector is an important component of intelligent harvesters [28], and its function is to clamp onto target objects by grabbing or picking. To reduce the injury of fruit and vegetables during harvesting, flexible end effectors have been used to harvest apple, tomato [29], and mango [30]. Goulart et al [30] used six flexible fingers to fully wrap mangoes in order to reduce their damage during harvesting.…”

“…To reduce the injury of fruit and vegetables during harvesting, flexible end effectors have been used to harvest apple, tomato [29], and mango [30]. Goulart et al [30] used six flexible fingers to fully wrap mangoes in order to reduce their damage during harvesting. These end effectors were suitable for harvesting spherical fruits or vegetables.…”