Relay navigation strategy study on intelligent drive on urban roads

In order to solve navigation problem of intelligent vehicle driving on urban roads and to achieve the navigation in intersection area, intersection transition area and section area. The relay navigation strategy and algorithm can solve the navigation problem of intelligent vehicle driving in typical urban roads such as intersection area, intersection transition area and section area, realizing seamless handover among different typical areas. Bezier curve function model was introduced to different typical areas, which solved the self-adaption recognition problem in different typical areas and revised positional accuracy with the help of cloud computing positioning service. In order to explain the strategy implement, an instance based on the strategy was adopted. Instance analysis indicates that as for the navigation problem in intersection area, intersection transition area and section area, if the relay navigation strategy is utilized, the self-adaption recognition problem in different typical areas can be handled. Based on the relay navigation strategy, the drive of intelligent vehicle on urban roads can effectively solve the self-adaption recognition problem in different typical areas in urban and further solve driving problems of intelligent vehicle of the same category in urban roads.

Automatic navigation path detection method for tillage machines working on high crop stubble fields based on machine vision

Due to the influence of complex working environment and artificial factors,it is easy to cause crop up over or less tillage problem when straw returning machine is working in paddy field.A new method for path detection suitable for rice,rape and wheat high crop stubble tilling environments was proposed.First the distribution characteristics of rice,rape and wheat high crop stubble images in paddy field based on RGB color model were analyzed,and rice,the color images of rape and wheat high crop stubble were converted into gray ones using custom factor combination R+G-2B;Then,the gray images of rice,rape and wheat high crop stubble were segmented from soil background by means of luminance mean texture descriptor;Next,the binary image through custom shear-binary-image algorithm was cut to remove big noise blobs in high crop stubble’s tilled area;Finally,navigation path from navigation points by using the least square method was derived.The experimental results indicated that the navigation path detection algorithm was fast and effective to obtain navigation path in rice,rape and wheat high crop stubble tilling environments with up to 96.7% of segmentation accuracy within 0.6 s of processing time.