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Vision‐based Obstacle Detection and Navigation for an Agricultural Robot
Author(s) -
Ball David,
Upcroft Ben,
Wyeth Gordon,
Corke Peter,
English Andrew,
Ross Patrick,
Patten Tim,
Fitch Robert,
Sukkarieh Salah,
Bate Andrew
Publication year - 2016
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21644
Subject(s) - obstacle , artificial intelligence , computer vision , robot , robotics , computer science , inertial navigation system , machine vision , navigation system , global positioning system , engineering , orientation (vector space) , geography , mathematics , geometry , archaeology , telecommunications
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.