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Research on Vision System Calibration Method of Forestry Mobile Robots
Research on Vision System Calibration Method of Forestry Mobile Robots
- Source :
- International Journal of Circuits, Systems and Signal Processing. 14:1107-1114
- Publication Year :
- 2021
- Publisher :
- North Atlantic University Union (NAUN), 2021.
-
Abstract
- Forestry mobile robots can effectively solve the problems of low efficiency and poor safety in the forestry operation process. To realize the autonomous navigation of forestry mobile robots, a vision system consisting of a monocular camera and two-dimensional LiDAR and its calibration method are investigated. First, the adaptive algorithm is used to synchronize the data captured by the two in time. Second, a calibration board with a convex checkerboard is designed for the spatial calibration of the devices. The nonlinear least squares algorithm is employed to solve and optimize the external parameters. The experimental results show that the time synchronization precision of this calibration method is 0.0082s, the communication rate is 23Hz, and the gradient tolerance of spatial calibration is 8.55e−07. The calibration results satisfy the requirements of real-time operation and accuracy of the forestry mobile robot vision system. Furthermore, the engineering applications of the vision system are discussed herein. This study lays the foundation for further forestry mobile robots research, which is relevant to intelligent forest machines.
- Subjects :
- Computer science
Machine vision
Calibration (statistics)
010401 analytical chemistry
Real-time computing
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Mobile robot
04 agricultural and veterinary sciences
01 natural sciences
0104 chemical sciences
Signal Processing
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
Electrical and Electronic Engineering
Subjects
Details
- ISSN :
- 19984464
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- International Journal of Circuits, Systems and Signal Processing
- Accession number :
- edsair.doi...........0815f46c883bcef747cba51dfe35fb46
- Full Text :
- https://doi.org/10.46300/9106.2020.14.139