Description

— Course: Intelligent Robotics – Professor: Qi Hao
Coding Homeworks. Most of coding assignments will be done by Python(>=3.5) under a simple robotics simulator. You can follow the Coding instruction to use this simulator to complete the coding part in question1-3. Your final submission should be a compressed package with extension .zip, which includes your codes and explanations (you need to know how to write the manuscript with Markdown or LATEX). Your code should be run step-by-step without any error. Real-time animation is also recommended.
Question
Please find the optimal path under a given grid map with reward using Markov Decision Process (MDP) Note:
white: the start position red: the goal position green: the obstacle black: ground obstacle reward: -10 goal reward: 10 others: -1 over the bound: -5

Coding instruction
Install the intelligent robotics simulator
git clone -b edu https://github.com/hanruihua/intelligent-robot-simulator.git cd intelligent-robot-simulator pip install -e .
Note1: Please confirm that this repository is under the edu branch. You can use git branch to check current branch. If it is not under the edu branch, you can use git checkout edu to change current branch to edu branch.
Code for question
There are five files for this question in the source folder, question_run.py, mdp.py, grid_map.py, map_matrix.npy, and reward_matrix.npy
question_run.py is the main program you should run
mdp.py is the file to perform Markov Decision Process. You should complete the functions include value iteration and policy iteration in this file for the coding task. grid_map.py is the file that defines the class about the grid map for you to use. map_matrix.npy and reward_matrix.npy define the map and the reward in each grid.
You should complete the file mdp.py and run question_run.py to show the simulation results. You can set the parameter animation = True in question_run.py to generate the animation such as the follows.