智慧校园导向标识机器人步态自动化控制方法

机器人行驶的校园路面存在颠簸和有障碍物的情况,导致导向标示机器人的步行出现误差,机器人步态自动化控制效果差,针对此问题设计一个智慧校园导向标识机器人步态自动化控制方法。建立稳定性控制方程,构建自主控制函数决定导向标示机器人行走的方向与路线,建立步行控制模型,结合姿态控制器,矫正导向标示机器人行走的姿态与稳定性,找到固定的行走规律,实现导向标示机器人步态自动化控制,完成校园内导向任务。实验结果表明,所提出的方法髋关节同步控制准确性高、干扰情况下导向标示机器人恢复稳定速度快,并且在干扰情况下控制偏差小,提高了校园导向标示机器人步态自动化控制有效性。     

Research and Implementation of Algorithm for Image Enhancement and Unwrapped Distortion Correction for SLVF Panoramic Night Vision Image

Abstract： Based on digital signal processor（DSP） and field programmable gate array（FPGA） techniques, the architecture of super large view field（SLVF） panoramic night vision image processing hardware platform was established. The panoramic unwrapping and correcting algorithm, up to a full 360°, based on coordinate rotation digital computer （CORDIC） and night vision image enhancement algorithm, based on histogram equalization theory and edge detection theory, was presented in this paper, with the purpose of processing night vision dynamic panoramic annular image. The annular image can be unwrapped and corrected to conventional rectangular panorama by the panoramic image processing algorithm, which uses the pipelined CORDIC configuration to realize a trigonometric function generator with high speed and high precision. Histogram equalization algorithm can perfectly enhance the contrast of the night vision image. Edge detection algorithm can be propitious to find and detect small dim dynamic targets in night vision circumstances. After abundant experiment, the al- gorithm for panoramic image processing and night vision image enhancement is successfully implemented in FPGA and DSP. The panoramic night vision image system is a compact device, with no external rotating parts. And the system can reliably and dynamically detect 360＊ SLVF panoramic night vision image.