K-Means Partitioned Space Path Planning (KPSPP) for Autonomous Robotic Harvesting. (19th November 2015)

• Record Type: Journal Article
• Authors: Meaclem, Christopher Vincent; Chen, XiaoQi; Gutschmidt, Stefanie; Hann, Chris; Parker, Richard
• Is Part Of: International journal of advanced robotic systems. Volume 12:Number 11(2015)
• Publication Date: 2015-11-19
• Subjects: Route Planning -- Harvesting -- Robotics; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/61816
• Languages: English
• ISSNs: 1729-8806

Abstract

A three-dimensional coverage path-planning algorithm is proposed for discrete harvesting machines. Although prior research has developed methods for coverage planning in continuous-crop fields, no such algorithm has been developed for discrete crops such as trees. The problem is formulated as a graph traversal problem and solved using graph techniques. Paths to facilitate autonomous operation are generated. A case study is formed around the novel tree-to-tree felling system developed by the University of Canterbury and Scion. This machine is being developed to manoeuvre through New Zealand's plantation forest to fell Pinus radiata trees on steep (≤ 45°) terrain. Algorithm performance is evaluated in 14 commercial plantation forests. Results indicate that a mean coverage of 84.43% was achieved.