Agricultural robots are subject to a much harsher envi- ronment than those in the factory or lab and control strategies need to take this into account while maintaining a low cycle time. Three control strategies were tested on Vegebot, a lettuce-picking robot, in both simulation and on the real robot. Between a fast open loop that was vulnerable to environmental noise and a slow but robust visual servoing technique, a Learned Open Loop strategy was tested where the robot learned from successful picks to pick at an intermediate speed. This reduced the projected cycle time from 31s to 17.2s, a 45% reduction.This project was possible thanks to EPSRC Grant EP/L015889/1, the Royal Society ERA Foundation Translation Award (TA160113), EPSRC Doctoral Training Program ICASE AwardRG84492 (cofunded by G’s Growers), EPSRC Small Partnership AwardRG86264 (in collaboration with G’s Growers), and the BBSRC Small Partnership GrantRG81275. Special thanks to G Growers, George Walker and Josie Hughes for their invaluable assistance
