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  • 标题:K-means Partitioned Space Path Planning (KPSPP) for Autonomous Robotic Harvesting
  • 本地全文:下载
  • 作者:Christopher Vincent Meaclem ; XiaoQi Chen ; Stefanie Gutschmidt
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2015
  • 卷号:12
  • DOI:10.5772/61816
  • 语种:English
  • 出版社:SAGE Publications
  • 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.
  • 关键词:Route Planning; Harvesting; Robotics
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