Práctica 4: Global Navigation using Teletaxi
Welcome! Picture 1. Taxi in New York Goal: In this exercise we are going to implement the logic of a Gradient Path Planning (GPP) algorithm, which consists of: - Selecting a destination, the GPP algorithm is responsible for finding the shortest path to it, avoiding, in the case of this practice, everything that is not road. - Once the path has been selected, the logic necessary to follow this path and reach the objective must be implemented in the robot. Explanation: First, we have to built a gradient map assigning weights to every cell between the beginning and the target we want to reach. I have choose 2 different values for the weights: 1 for cardinal directions (north, south, east and west) and 1.25 for the intermediate directions (north-east, south-east, north-west and south-west). Next, we have to binarize the map (binarize_map() method) from where we obtain only 2 values, 0 if it´s an obstacle and 255 if it´s road. All the data obtained is copied into a numpy array o...