Research on Vision System Calibration Method of Forestry Mobile Robots

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.

Detection and Modeling of Unstructured Roads in Forest Areas Based on Visual-2D Lidar Data Fusion

“…The information flow is aligned along the time axis by extracting the message time-stamp. Detailed information regarding the calibration methods can be found in our previous study [35]. rounding environment more accurately, as well as to realize the UGV's motion planning and obstacle avoidance.…”

“…The information flow is aligned along the time axis by extracting the message time-stamp. Detailed information regarding the calibration methods can be found in our previous study [35]. For meeting the needs of forest operations, as shown in Figure 2, the UGV platform used in the research is a self-built Ackerman chassis platform.…”