An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation - Xirui Zhang; Yongqi Liu; Junxiao Liu; Xuanli Chen; Ruiwu Xu; Weiqiang Ma; Zhifu Zhang; Shaohua Fu (Scientific Reports)
Abstract The use of rubber-tapping robots capable of autonomous navigation in place of manual rubber-tapping is a growing trend, but the challenging multi-objective navigation task in forest environments impedes their autonomous operation. To tackle this issue, an autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation is designed. This navigation decision mechanism is comprised of obtaining coordinates of target points (OCTP), selecting the next coordinate (SNC), generating the additional coordinates (GAC), and optimizing the planned paths (OPP). By utilizing this mechanism, the robot can autonomously select the next target point based on its current position and the actual operating logic while navigating in the forest areas, adding additional coordinates during row or column changes, and planning and optimizing the path. The on-site experiments demonstrate that during autonomous navigation, the positioning accuracy is favorable and supports subsequent operations. The overall rationality of the planned path reaches 92.14%, further confirming its effectiveness.