New! Robotics Programming
Partnership with Miller Fabrication Solutions
The Department of Computer Information Science has a robotics partnership with Miller Fabrication Solutions. Miller Fabrication Solutions employs robot programmers and helped to shape the robotics programming courses in the CIS department so that Computer Science graduates will be employable at their company. How does Computer Science fit into robotics? A robot is a computer that can move. Thus, Computer Science is clearly applicable. A robotics program is written on a computer (like any other program), and then downloaded into the robot.
A new robotics lab is scheduled to be completed by Spring, 2022. The robotics lab will include computers used to program robots and a large area for robots to move around in. The robotics lab will be in room 142 Becker Hall.
Courses in the Robotics Programming Concentration
Miller Fabrication Solutions has agreed that those students who take the following courses in the Robotics Programming concentration will be employable as Robotics Programmers in their company.
CIS 208 Introduction to Robotics Programming. A lab-based course that uses a hands-on approach to introduce the basic concepts of robotic in conjunction with the programming skills learned in previous courses through programming of autonomous mobile robots. Course information will be tied to lab experiments: students will work in groups to build and test increasingly more complex mobile robotic algorithms,
CIS 305 Artificial Intelligence in Decision Making. Surveys the thinking and some of the pioneering efforts in the area of artificial intelligence (AI), integrated with more traditional approaches to decision-making. Applies AI principles through the use of logic programming languages.
CIS 310 Natural Language Processing. The natural language processing field is the intersection between human language and computer science. This course provides an introduction to the field of natural language processing. Students will learn how computers acquire, understand and generate human language. How can computers translate text between different languages? How can google find the web page that you ask for? How do email systems filter junk mail?. How can voice recognition software and text to speech software work? This course will expose students to those techniques using a range of statistical methods and machine learning methods. Students will also practice writing NLP software.
CIS 318 Autonomous Robotics. This course aims to introduce students into the holistic design of autonomous robots to include sensors and intelligence. The course contains modules state estimation robot vision, Simultaneous Localization and Mapping and object detection, and path planning. A semester-long student project helps to equip student with robot development skills.
CIS 435 Machine Learning. This course introduces various machine learning concepts and algorithms. Students will learn about the basics of machine learning as well as how machine learning is used during interactions in their everyday lives. Students will also be exposed to machine learning through a programming framework of GUI application (for example, Weka). Although machine learning is inherently mathematical, this course focuses on understanding algorithms at a high level and being able to apply and compare them rather that the low-level mathematics or implementations.