K-Means Partitioned Space Path Planning (KPSPP) for Autonomous Robotic Harvesting

摘要

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.