This repository is my submission of Search and Sample Return project for Robotics Nano Degree program from Udacity.
1. Provide a Writeup / README that includes all the rubric points and how you addressed each one. You can submit your writeup as markdown or pdf.
This is the Writeup/README file.
1. Run the functions provided in the notebook on test images (first with the test data provided, next on data you have recorded). Add/modify functions to allow for color selection of obstacles and rock samples.
The first problem I ran into was updating the Rover in perception_step function in perception.py. After days of googling, I found out that I have to call Rover instance/object from driving_rover.py file and define it with whatever of the rover it was that I had to update. Knowing that, I had to do perspect_transform() only once, but I had to perform color_thresh() function couple times. I updated the perspect_transform() by adding in another cv2.warpPerspective just like one for warped, but this time I merely created a copy of the image array with red color channel. When defining color threshold for obstacle(wall) I subtracted 1 from the first color_thresh at rgb = (160, 160, 160), which represents none-lit part of the binary image, and set that as the obstacle.
2. Describe in your writeup how you modified the process_image() to demonstrate your analysis and how you created a worldmap. Include your video output with your submission.
I initially did not modify process_image(), and when I later did, I ran into multiple errors. I keep running into "Value Error: operands could not be broadcast together with shapes (3406,) (418,)", but nobody was there to help me.