During the operation of apple picking robots, it is necessary to accurately identify branches to prevent collisions with them. However, obtaining branch images in complex environments is often fragmented, making it difficult to reconstruct the entire tree. To solve this problem, this study obtained branch images by removing non-branch areas, and extract tree skeletons and endpoints based on 8-connection and thin line methods. This study investigates the growth characteristics of fruit tree branches and the distribution of endpoints between branches at the same level, using this as a constraint to connect broken branches. Finally, the reconstruction of the entire tree is achieved. The experimental results show that the algorithm has a branch recognition rate of 92.1% on sunny days and 84.2% on cloudy days. Therefore, the algorithm proposed in this study can provide accurate branch information for apple picking robots.
KEYWORDS: Roads, Mathematical optimization, Signals intelligence, MATLAB, Detection theory, Reflection, Data modeling, Control systems, Visual process modeling, Sun
With the rapid development of China’s economy, the number of motor vehicles continues to increase, and the phenomenon of road congestion is becoming increasingly serious. Compared with widening the road surface and adding lanes, it is more feasible to optimize the crossing signal timing scheme. Based on the real-time queue length at the intersection, this study dynamically adjusts the signal timing scheme to overcome the rigidity of the traditional fixed timing scheme with the intersection of Fengxi Avenue and Siyuan Huannan Road in Chang’an District of Xi 'an as an example. The traditional scheme and the optimized scheme are jointly simulated by VISSIM and MATLAB respectively, and the simulation results of the two schemes are compared and analyzed. The results show that the average queue length, average delay time and average stop time of the optimized scheme are significantly lower than those of the traditional scheme, which proves that this method can effectively improve the traffic efficiency of intersections and alleviate traffic congestion.
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