The growing popularity of kiwifruit orchards in New Zealand is increasing the already high demand for seasonal labourers. A novel robotic kiwifruit harvester has been designed and built to help meet this demand [H. A. Williams et al. Biosystems Eng. 181 (2019), pp. 140–156]. Early evaluations of the platform have shown good results with the system capable of harvesting 51.0% of 1,456 kiwifruit in four bays with an average cycle‐time of 5.5 s/fruit. However, the harvester's high cycle‐time, and high fruit loss rate at 23.4%, prevent it from being commercially viable. This paper presents two new developments for the harvesting system, a new vision system and two new gripper variations designed to overcome the harvester's previous limitations. Furthermore, we have designed and conducted the largest real‐world evaluation of a robotic fruit harvesting system published to date with over 12,000 kiwifruit involved. The results of this trial demonstrated that our kiwifruit harvester is one of the most effective selective fruit harvesters in the world capable of successfully harvesting 86.0% of reachable fruit, and 55.8% of all kiwifruit with a cycle‐time of 2.78 s/fruit.

Stereo vision system and manipulator are two major components of an autonomous fruit harvesting system. In order to raise the fruit-harvesting rate, stereo vision system calibration and kinematic calibration are two significant processes to improve the positional accuracy of the system. This article reviews the mathematics of these two calibration processes and presents an integrated approach for acquiring calibration data and calibrating both components of an autonomous kiwifruit harvesting system. The calibrated harvesting system yields good positional accuracy in the laboratory tests, especially in harvesting individual kiwifruit. However, the performance is not in line with the outcomes in the orchard field tests due to the cluster growing style of kiwifruit. In the orchard test, the calibrations reduce the fruit drop rate but it does not impressively raise the fruit harvesting rate. Most of the fruit in the clusters remain in the canopy due to the invisibility of the stereo vision system. After analyzing the existing stereo vision system, a future visual sensing system research direction for an autonomous fruit harvesting system is justified.