Robot Path Planning Navigation for Dense Planting Red Jujube Orchards Based on the Joint Improved A* and DWA Algorithms under Laser SLAM

Yufeng Li, Jingbin Li (), Wenhao Zhou, Qingwang Yao, Jing Nie and Xiaochen Qi
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Yufeng Li: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Jingbin Li: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Wenhao Zhou: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Qingwang Yao: School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
Jing Nie: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Xiaochen Qi: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China

Agriculture, 2022, vol. 12, issue 9, 1-24

Abstract: High precision navigation along specific paths is required for plant protection operations in dwarf and densely planted jujube orchards in southern Xinjiang. This study proposes a robotic path planning and navigation method for dense planting of red jujube orchards based on the improved A* and dynamic window approach (DWA) algorithms using Laser Radar to build maps. First, kinematic and physical robot simulation models are established; a map of the densely planted jujube orchard is constructed using Laser Radar. The robot’s position on the constructed map is described using an adaptive Monte Carlo positioning algorithm. Second, a combination of the improved A* and DWA algorithms is used to implement global and real-time local path planning; an evaluation function is used for path optimisation. The proposed path planning algorithm can accurately determine the robot’s navigation paths, with the average error U, average linear path displacement error, and L-shaped navigation being 2.69, 2.47, and 2.68 cm, respectively. A comparison experiment is set up in the specific path navigation section. The experimental results show that the improved fusion algorithm reduces the average navigation positioning deviation by 0.91cm and 0.54 cm when navigating L and U-shaped specific paths. The improved fusion algorithm is superior to the traditional fusion algorithm in navigation accuracy and navigation stability. It can improve the navigation accuracy of the dense planting jujube garden and provide a reference method for the navigation of the plant protection operation in the densely planted jujube orchards.

Keywords: motion perception; navigation and obstacle; avoidance path planning; SLAM (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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