Vision‐based Obstacle Detection and Navigation for an Agricultural Robot. Issue 8 (13th January 2016) - Ball, David; Upcroft, Ben; Wyeth, Gordon; Corke, Peter; English, Andrew; Ross, Patrick; Patten, Tim; Fitch, Robert; Sukkarieh, Salah; Bate, Andrew
Abstract : This paper describes a vision‐based obstacle detection and navigation system for use as part of a robotic solution for the sustainable intensification of broad‐acre agriculture. To be cost‐effective, the robotics solution must be competitive with current human‐driven farm machinery. Significant costs are in high‐end localization and obstacle detection sensors. Our system demonstrates a combination of an inexpensive global positioning system and inertial navigation system with vision for localization and a single stereo vision system for obstacle detection. The paper describes the design of the robot, including detailed descriptions of three key parts of the system: novelty‐based obstacle detection, visually‐aided guidance, and a navigation system that generates collision‐free kinematically feasible paths. The robot has seen extensive testing over numerous weeks of field trials during the day and night. The results in this paper pertain to one particular 3 h nighttime experiment in which the robot performed a coverage task and avoided obstacles. Additional results during the day demonstrate that the robot is able to continue operating during 5 min GPS outages by visually following crop rows.