Orchard manoeuvring strategy for a robotic bin-handling machine

Yunxiang Ye, Long He, Zhaodong Wang, Dylan Jones, Geoffrey A. Hollinger, Matthew E. Taylor, Qin Zhang

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Unlike a car-like vehicle manoeuvring its way in an open field, a four-wheel-independent-steered robotic machine placed in an orchard must operate in a very confined working space between tree rows. Because the machine is subject to the unique constraints of the worksite space and operation limits, multiple steering modes are often required to effectively accomplish the desired bin-handling manoeuvers. In this study, we created a multi-mode manoeuvring strategy selection method to generate strategies that can guide the robotic platform to accomplish bin handling tasks, such as correcting pose error between tree rows, entering a tree lane from the headland, and loading a bin between tree rows, effectively. The method determines the manoeuvring strategies based on the situation among four steering modes: 1) Ackermann steering, 2) coordinated four wheel steering, 3) crab steering, and 4) spinning. The study first evaluated applicable strategies and selected the best of these strategies for different bin handling scenarios. Then, the selected strategies were implemented to drive a four-wheel-independent-steering (4WIS) system to complete the tasks in a commercial orchard in order to validate the method. Obtained results showed that the system could navigate the platform on desired trajectories to complete bin-handling tasks with a root mean square errors less than 0.06 m.

Original languageEnglish (US)
Pages (from-to)85-103
Number of pages19
JournalBiosystems Engineering
StatePublished - May 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Food Science
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • Soil Science


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