توسعه یک ربات نمونه اولیه و الگوریتم راه اندازی سریع مسیر برای علف کش لیت استاتیک

To demonstrate the feasibility and improve the implementation of laser weeding, a prototype robot was built and equipped with machine vision and gimbal mounted laser pointers. The robot consisted of a mobile platform modified from a small commercial quad bike, a camera to detect the crop and weeds and two steerable gimbals controlling the laser pointers. Visible-one laser pointers were used to simulate the powerful laser trajectories. A colour segmentation algorithm was utilised to extract plants from the soil background; size estimation was used to differentiate crop from weeds; and an erosion and dilation algorithm was developed to separate objects that were touching. Conversely, another algorithm, which utilised shape descriptors, was able to distinguish plant species in non-touching status regardless of area difference. Next, in order to reduce route length and run time, a new path-planning algorithm for static weeding was proposed and tested. It was demonstrated to be more efficient especially when addressing a higher density of weeds. A model was then established to determine the optimal segmentation size, based on the route length for treatment. It was found that the segmentation algorithm has the potential to be widely used in fast path-planning for the travelling-salesman problem. Finally, performance tests in the indoor environments showed that the weeding mean positional error was 1.97 mm, with a 0.88 mm standard deviation. Another test indicated that with a laser traversal speed of 30 mm/s and a dwell time of 0.64 s per weed, it had a hit rate of 97%.