针对智能车因单条引导线信息量少而引起的误识别问题,设计一种能自动识别和跟踪双边引导线的智能车系统。智能车以Freescale公司MC9S12XSl28作为核心控制器,利用COMS(Complementary Metal OxideSemiconductor)摄像头OV7620作为路径信息...针对智能车因单条引导线信息量少而引起的误识别问题,设计一种能自动识别和跟踪双边引导线的智能车系统。智能车以Freescale公司MC9S12XSl28作为核心控制器,利用COMS(Complementary Metal OxideSemiconductor)摄像头OV7620作为路径信息采集装置,对采集图像进行二值化处理、去噪操作和边缘检测后提取路径信息、进而准确地判别跑道的形状,为舵机和电机提供控制依据,以使小车平稳快速地行驶。同时,提出将行驶状态与赛道信息综合考虑的措施,并通过PID(Proportional Integral Differential)控制策略以及实验测试,实现了对各种典型跑道的优化处理,使高速行进中的智能车具有良好的转向调节能力和加减速响应能力。智能车可以在以白色为底面颜色,两边有黑色引导线的跑道上运行,克服了因单条引导线信息量少而引起的误识别问题。展开更多
The structure, function and working principle of JLUIV-3, which is a new typeof auto-mated guided vehicle (AGV) with computer vision, is described. The white stripe line withcertain width is used as inductive mark for...The structure, function and working principle of JLUIV-3, which is a new typeof auto-mated guided vehicle (AGV) with computer vision, is described. The white stripe line withcertain width is used as inductive mark for JLUIV-3 automated navigation. JULIV-3 can automaticallyrecognize the Arabic numeral codes which mark the multi-branch paths and multi-operation buffers,and autonomously select the correct path for destination. Compared with the traditional AGV, it hasmuch more navigation flexibility and less cost, and provides higher-level intelligence. Theidentification method of navigation path by using neural network and the optimal control method ofthe AGV are introduced in detail.展开更多
文摘针对智能车因单条引导线信息量少而引起的误识别问题,设计一种能自动识别和跟踪双边引导线的智能车系统。智能车以Freescale公司MC9S12XSl28作为核心控制器,利用COMS(Complementary Metal OxideSemiconductor)摄像头OV7620作为路径信息采集装置,对采集图像进行二值化处理、去噪操作和边缘检测后提取路径信息、进而准确地判别跑道的形状,为舵机和电机提供控制依据,以使小车平稳快速地行驶。同时,提出将行驶状态与赛道信息综合考虑的措施,并通过PID(Proportional Integral Differential)控制策略以及实验测试,实现了对各种典型跑道的优化处理,使高速行进中的智能车具有良好的转向调节能力和加减速响应能力。智能车可以在以白色为底面颜色,两边有黑色引导线的跑道上运行,克服了因单条引导线信息量少而引起的误识别问题。
基金This project is supported by National Natural Science Foundation of China(No.50175046) Technology Foundation of Education Ministry of China(No.00037).
文摘The structure, function and working principle of JLUIV-3, which is a new typeof auto-mated guided vehicle (AGV) with computer vision, is described. The white stripe line withcertain width is used as inductive mark for JLUIV-3 automated navigation. JULIV-3 can automaticallyrecognize the Arabic numeral codes which mark the multi-branch paths and multi-operation buffers,and autonomously select the correct path for destination. Compared with the traditional AGV, it hasmuch more navigation flexibility and less cost, and provides higher-level intelligence. Theidentification method of navigation path by using neural network and the optimal control method ofthe AGV are introduced in detail.
