We propose a two-stage method for detecting circular objects in this paper. In the first stage, curves are divided as linear segments or nonlinear segments. A least square estimator is used to find the estimated cente...We propose a two-stage method for detecting circular objects in this paper. In the first stage, curves are divided as linear segments or nonlinear segments. A least square estimator is used to find the estimated centers and radii of the nonlinear segments in the second stage. The found centers and radii are then evaluated to see if there exist circles in the nonlinear segments. Both of the broken and occluded circular objects are evaluated for the proposed method. From the experimental results, it is seen that the proposed method is efficient.展开更多
Path planning for field agricultural robots must satisfy several criteria:establishing feeding routes,maintaining gentle slopes,approaching multiple livestock observation points,ensuring timely environmental monitorin...Path planning for field agricultural robots must satisfy several criteria:establishing feeding routes,maintaining gentle slopes,approaching multiple livestock observation points,ensuring timely environmental monitoring,and achieving high efficiency.The complex terrain of outdoor farming areas poses a challenge.Traditional A*algorithms,which generate only the shortest path,fail to meet these requirements and often produce paths that lack smoothness.Therefore,identifying the most suitable path,rather than merely the shortest one,is essential.This study introduced a path-planning algorithm tailored to field-based livestock farming environments,building upon the traditional A*algorithm.It constructed a digital elevation model,integrated an artificial potential field for evaluating multiple target points,calculated terrain slope,optimized the search neighborhood based on robot traversability,and employed Bézier curve segmentation for path optimization.This method segmented the path into multiple curves by evaluating the slopes of the lines connecting adjacent nodes,ensuring a smoother and more efficient route.The experimental results demonstrate its superiority to traditional A^(*),ensuring paths near multiple target points,significantly reducing the search space,and resulting in over 69.4%faster search speeds.Bézier curve segmentation delivers smoother paths conforming to robot trajectories.展开更多
基金supported by the I-Shou University under Grant No.ISU 102-05-01
文摘We propose a two-stage method for detecting circular objects in this paper. In the first stage, curves are divided as linear segments or nonlinear segments. A least square estimator is used to find the estimated centers and radii of the nonlinear segments in the second stage. The found centers and radii are then evaluated to see if there exist circles in the nonlinear segments. Both of the broken and occluded circular objects are evaluated for the proposed method. From the experimental results, it is seen that the proposed method is efficient.
基金supported by the Subject construction projects in specific universities(Grant No.2023B10564003)the Science and Technology Rural Commissioner Project of Guangzhou(Grant No.20212100026).
文摘Path planning for field agricultural robots must satisfy several criteria:establishing feeding routes,maintaining gentle slopes,approaching multiple livestock observation points,ensuring timely environmental monitoring,and achieving high efficiency.The complex terrain of outdoor farming areas poses a challenge.Traditional A*algorithms,which generate only the shortest path,fail to meet these requirements and often produce paths that lack smoothness.Therefore,identifying the most suitable path,rather than merely the shortest one,is essential.This study introduced a path-planning algorithm tailored to field-based livestock farming environments,building upon the traditional A*algorithm.It constructed a digital elevation model,integrated an artificial potential field for evaluating multiple target points,calculated terrain slope,optimized the search neighborhood based on robot traversability,and employed Bézier curve segmentation for path optimization.This method segmented the path into multiple curves by evaluating the slopes of the lines connecting adjacent nodes,ensuring a smoother and more efficient route.The experimental results demonstrate its superiority to traditional A^(*),ensuring paths near multiple target points,significantly reducing the search space,and resulting in over 69.4%faster search speeds.Bézier curve segmentation delivers smoother paths conforming to robot trajectories.
