TY - JOUR
T1 - Orchard manoeuvring strategy for a robotic bin-handling machine
AU - Ye, Yunxiang
AU - He, Long
AU - Wang, Zhaodong
AU - Jones, Dylan
AU - Hollinger, Geoffrey A.
AU - Taylor, Matthew E.
AU - Zhang, Qin
N1 - Funding Information:
This research was partially supported in part by United States Department of Agriculture (USDA)’s Hatch and Multistate Project Funds (Accession No 1005756 and 1001246 ), USDA National Institutes for Food and Agriculture competitive grant (Accession No 1003828 ), and Washington State University (WSU) Agricultural Research Center (ARC). Part of this research has taken place in part at the Intelligent Robot Learning (IRL) Lab, Washington State University. IRL's support includes NASA NNX16CD07C, NSF IIS-1149917, NSF IIS-1643614, and USDA 2014-67021-22174. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or Washington State University.
Publisher Copyright:
© 2017 IAgrE
PY - 2018/5
Y1 - 2018/5
N2 - 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.
AB - 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.
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U2 - 10.1016/j.biosystemseng.2017.12.005
DO - 10.1016/j.biosystemseng.2017.12.005
M3 - Article
AN - SCOPUS:85042352265
SN - 1537-5110
VL - 169
SP - 85
EP - 103
JO - Biosystems Engineering
JF - Biosystems Engineering
ER -