Performance Evaluation of a Harvesting Robot for Sweet Pepper

This paper evaluates a robot developed for autonomous harvesting of sweet peppers in a commercial greenhouse. Objectives were to assess robot performance under unmodified and simplified crop conditions, using two types of end effectors (Fin Ray; Lip type), and to evaluate the performance contribution of stem-dependent determination of the grasp pose. We describe and discuss the performance of hardware and software components developed for fruit harvesting in a complex environment that includes lighting variation, occlusions, and densely spaced obstacles. After simplifying the crop, harvest success significantly improved from 6% to 26% (Fin Ray) and from 2% to 33% (Lip type). We observed a decrease in stem damage and an increase in grasp success after enabling stem-dependent determination of the grasp pose. Generally, the robot had difficulty in successfully picking sweet peppers and we discuss possible causes. The robot's novel capability of perceiving the stem of a plant may serve as useful functionality for future robots.