Texts

• Introduction to Autonomous Mobile Robots, Second Edition Roland Siegwart, Illah R. Nourbakhsh and Davide Scaramuzza, MIT Press 2011.

  Online version with Columbia ID, also available at Columbia Bookstore and other online retailers.

• Planning Algorithms by Steven LaValle. This book is online and free.
• Robotics, Vision and Control, Fundamental Algorithms in MATLAB by Peter Corke (available free through Columbia University SpringerLink). You can download the accompanying Robotics Toolbox for Matlab which has a set of functions for analyzing and displaying robotic arms.
• Springer Handbook of Robotics. This is also online and free to Columbia students using a Columbia IP address.

Robot

• Students will receive an iRobot Create robot for use in the class, usually in a team of 2 or 3 students.

Pre-requisites

• Data Structures
• Knowledge of at least one of the following: C, C++ or Java.
• Knowledge of elementary Linear Algebra

Course Overview

This course is an overview of the field of robotics. The intent of this course is to give students an in-depth understanding of how robots work, and the application and use of computers to typical robotic problems. Students will also be exposed to current research directions in robotics. A key component of the class is hands-on programming of small mobile robots to implement higher level robotic path planning and sensing algorithms. Students will work in teams to have their robotic platforms perform intelligent action using sensing-actuation feedback loops.

The course will be a lecture course meeting twice a week. There will be 4-5 homework assignments, a midterm, and a final exam required. The homework will include programming real robots. Grading is homework 50%, midterm 20%, final 30%.

Topics to be covered

• Coordinate frames and representations. Use of homogeneous transformations in robotics.
• Specification of position and orientation
• Manipulator forward and inverse kinematics
• Mobile Robots: Algorithms and methods for mobile robot navigation, path planning and sensing.
• Robotic sensing: Vision, touch, proximity, force/torque. Examination of sensor types, capabilities, design and integration of sensory data for robotics.
• Humanoid Robots
• Robotic Hands, Grasping and Manipulation
• Planning strategies in robotics. Application of Artificial Intelligence techniques to complex planning problems such as assembly, manipulation, locomotion and navigation.
• New and interesting Robotic Domains: Medicine, Space, Microscale