Brown University Robotics:Cs148 Course Development Book
From Brown University Robotics
Revision as of 18:15, 4 May 2010 by Bkorel
CS148: Building Intelligent Robots is an introduction to fundamental topics in autonomous robot control. This course focuses on the development of "brains" for robots. That is, given a machine with sensing, actuation, and computation, how do we develop programs that allow the machine to function autonomously? The course development book is meant to be a resource for anyone interested in teaching a similar undergraduate robotics course or for robot hobbyists who want to get up and running with both a robot hardware and software platform. CS148 projects center on a "robot soccer" task, where students program the Brown iRobot Create/ASUS robots using either the Player/Stage/Gazebo (PSG) or the Robot Operating System (ROS) middleware framework.
The following outlines each of the chapters in the book.
Chapter 1: Course Objectives - An introduction to the course, a motivation for robotics, the concepts taught and 148 projects.
Chapter 2: Getting Started - The steps for assembling and remotely controlling a low-cost mobile robot, which we call the "SmURV", from "commercial off-the-shelf" (COTS) components.
Chapter 3: Robot Middleware - Introductions to Player and ROS, two middleware packages that provide an abstraction between the hardware and the robot client. This chapter walks through the steps of writing a simple client application in both middleware systems.
Chapter 4: Create Spotting - The first project for students to become familiar with the Create hardware functionality and introduce/highlight the importance of scientific writing.
Chapter 5: Enclosure Escape - This project acquaints students with writing robot clients that control basic planar movement using either Player or ROS. The students are tasked with implementing either a reactive or deliberative robot control policy to escape from an arbitrary static enclosure.
Chapter 6: Object Seeking -
Chapter 7: Path Planning
Chapter 8: Localization
Chapter 9: Subsumption
Chapter 10: Multi-Robot Coordination
Chapter 11: Learning