pgeedh/RoboticsSpecilization-UPenn-Computational-Motion-Planning

This Repository contains projects from Robotics specialization-Computational Motion Planning s from Coursera offered by the University of Pennsylvania- Instructor: Prof. CJ Taylor

Coursera Robotics Specialization- Computational Motion Planning

Instructor

Prof. CJ Taylor

Professor of Computer and Information Science This repository contains the solutions from all the programming assignements and quiz in this Coursera Course.

About This Course

Robotic systems typically include three components: a mechanism which is capable of exerting forces and torques on the environment, a perception system for sensing the world and a decision and control system which modulates the robot's behavior to achieve the desired ends. In this course we will consider the problem of how a robot decides what to do to achieve its goals. This problem is often referred to as Motion Planning and it has been formulated in various ways to model different situations. You will learn some of the most common approaches to addressing this problem including graph-based methods, randomized planners and artificial potential fields. Throughout the course, we will discuss the aspects of the problem that make planning challenging.

Mathematical Prerequisites

Mathematical prerequisites: Students taking this course are expected to have some familiarity with linear algebra, single variable calculus, and differential equations.

Programming Prerequisite

Some experience programming with MATLAB or Octave is recommended (we will use MATLAB in this course.) MATLAB will require the use of a 64-bit computer. You need to have Matlab installed if you want to run the programs on your machine with the appropriate libraries installed. The data used specifically for this course are not included but any similar data should work fine.