基于OpenCv、Numpy、matplotlib等实现的NAO机器人识别物体算法 .zip

# NAO-autoSearching It's a object recognition algorithm based on NAO robot by using naoqi、OpenCv、Numpy、matplotlib etc.. ### Intro It's a robotic searching and recognition algorithn by Python.And it's mainly based on OpenCV、Naoqi、Numpy、PIL module. #### The process : Open the robot's head camera --> Get image --> Binary image --> Morphology --> Get 2D locate --> Transform to 3D locate --> Go to the target --> Pick it --> Go to another target position --> Drop it #### The process's detail : The process has many part: * Adjusting NAO robot, preparing for getting the image. Open the robot's camera ,using naoqi to get the image, get robot's current parameter likes head angle or pitch angle. * Recognition ... Binary the image to a two color image by HSV color space which in the opencv library.After that , using numpy or something like matrix calculator to calculate the image's location.Finally ,transform the 2D location to a absolutely distance by the principle of ranging(it's not so accurate because the robot's move can change itself's parameter). * Moving After getting the distance between robot and the target,using the 3D measure algorithm to transfer it to 3D locate which needs many joint's parameter. * Picking and Dropping How to control the hand to the target? I use the Cartesian algorithm to handle it. (The algo is based on the dynamic 3D robotic model which provide a Array contains six angel.) #### The result: - Original image <img src="https://s1.ax1x.com/2018/11/28/FZnN5Q.png" width="400" height="310" /> - After HSV binary: <img src="https://s1.ax1x.com/2018/11/18/izofDU.png" width="400" height="310" /> - After Morphology : <img src="https://s1.ax1x.com/2018/11/28/FZnRPJ.png" width="400" height="310" /> - Calculate the locate: <img src="https://s1.ax1x.com/2018/11/18/izohbF.png" width="400" height="310" /> - Another image to calculate the locate: <img src="https://s1.ax1x.com/2018/11/18/izoIUJ.png" width="400" height="310" /> - Get the center : <img src="https://s1.ax1x.com/2018/11/18/izoWuT.png" width="400" height="310" /> - Using the bottom camera: <img src="https://s1.ax1x.com/2018/11/28/FZntUg.png" /> - Do it selt: <img src="https://s1.ax1x.com/2018/11/29/FZKoND.gif" />