Credits and Contact Hours

3 credits, 43 hours

Course Instructor Name

Dr. Abbas Fairouz

Textbook

Mobile Robotics: A Practical Introduction, Ulrich Nehmzow, 2nd Edition

Catalog Description

The nature of robotics and the role of intelligence in the context of robotics. Overview of robotic systems: state-of-the-art robot systems; planning vs. reactive control, uncertainty in control, sensing, and world models. Configuration space. The role of planning in robotics and relevant techniques. Robot programming; the range of software that supports robotic activity. Navigation and control; strategies for particular environments. Ethical issues associated with robotics and intelligent behavior.

Prerequisite

CpE-363

Specific Goals for the Course

Upon successful completion of this course, students will be able to:

Program a robot to perform a specified task (e.g. obstacle avoidance or wall following) in a target environment. (Student outcomes: 1, 2)

Describe different mechanical configurations of robot manipulators. (Student outcomes: 1, 2)

Know ethical issues when building a robot agent.

Have an understanding of the functionality and limitations of robot actuators and sensors. (Student outcomes: 2)

Undertake kinematics analysis of robot manipulators. (Student outcomes: 1, 2)

Understand the importance of robot dynamics. (Student outcomes: 1, 2)

Understand and be able to apply a variety of techniques to solve problems in areas such as robot control and navigation. (Student outcomes: 1, 2)

Work in group to design and implement a robot in a specified environment to perform a certain task. (Student outcomes: 2, 4, 5)

Appreciate the current state and potential for robotics in new application areas. (Student outcomes: 4, 7)

Topics to Be Covered

Introduction to Robotics, history and state of art

Definitions of Robotics terms

Agents and performance measure

Robot ethics and rules

Robot state and environment

Control architectures

Effectors and actuators

Sensors (basic and complex)

Locomotion

Artificial intelligence (AI) for Robotics: Machine Learning (ML).

Robot design

Feedback control

Behavior coordination

Emergent behavior and learning