Instructor: Dr. Henry Hexmoor

Spring 2010
Instructor office hours: Tu/Th 2:00-3:00PM

Lecture times: MW 4:00-5:15PM
Laboratory: TBD
Place: Parkinson 107

Course Description:

This course is a comprehensive introduction to modern robotics with an emphasis on autonomous mobile robotics. Fundamentals of sensors and actuators as well as algorithms for top level control are discussed. Multi-robotics and human-robot interaction issues are explored. A term project is an integral part of this course. Class lectures will closely track outline of the course textbook. Lectures and exams are theoretical. Class project is hands on, pragmatic and research oriented.

Projects:

A- Hardware track:

Students will use a physical robot kit to replicate a recently published work. This will be fully discussed in class. Milestones: CS day, Semester end. The following are idea suggestions:

1. Develop a mobile robot to navigate building corridors using human provided, visual sensory data. I.e., Human eyes and visual processes are used as remote sensors. This is incorporsted in a fancy GUI.

2. A mobile robot can use sonar sensor sampling to sense speeds of people crossing hallways and aviods them. The robot can build collision envelops as
described in this report.

3. Develop a mobile robot that predicts human crowd motion and avoids them. See Amalia Foka's thesis or short paper at http://www.ics.forth.gr/~foka/fokaIROS02.pdf

B- Software track:

You may use Pyro or write your own code from scratch.

Students will work in groups to replicate a recently published multirobotics research. This will be fully discussed in class.

(A) Human-Robot interaction, (B) Human-Swarm interaction. The following are idea suggestions:

1. artificial swarm control, 2. modeling dynamics of team sports, 3. modeling a big man society (aka Dr. Paul Welch's reciprocity game), 4. modeling crowds (see Andrew Fell's Keith Still's , Henein's), and 5. Modeling airport traffic. Modeling swarms to exhibit emergent phenoma is not acceptable.

C- Language track

Students design and implement a programming language for autonomous robot control.

Pre-requisites:

CS 330 with a grade of C or better or graduate standing. Seek permission of instructor if you need clarifications. Please Be aware that this is a programming intensive and a hands on course, requiring basic C programming skills.

What this course is NOT: a lower division CS course.

Graduate and undergraduate students are welcome.

Objectives:

To have a rich understanding of robotic platforms and their limitations
To be able to program mobile robots
To be able to design automation solutions using mobile robots

You are expected to know or learn programming language on your own.

Grading: Term project at 40%, and three exams worth 20% each, class participation and attendance will help determine borderline grades.

Class Project: Hunter-Gatherer: Teams of up to 5 students will design and build an autonomous robot that can detect and transport a container from 4 corners of a color-coded table to the assigned square area in the center of the table. The robot must visit all 4 corners and transport all 4 cargo containers to their correct positions with a parametric order of visitation.
50 points are divided into (a) 15 points for the design merit, (b) 15 points for project implementation, (c) 10 points for class presentation/demonstration, and (d) 10 points for final report.

**Important Dates (To be finalized in class)**
Week 1	1st wek of classes	Locomotion, maps, affect, control
Week 2		Locomotion, maps, affect, potential fields, control	Project proposals are reeived and ratified
Week 3		Fuzzy logic,
Week 4	Exam I
week 5
Week 6
Week 7
Week 8	Exam II
Week 9
Week 10
Week 11
week 12

Recommended textbook:
Howard Choset, et. al. 2005. Principles of Robot Motion: Theory, Algorithms, and Implementations, The MIT Press, ISBN-10: 0262033275.

Required, Supplemental Reading:
The following links and papers are limited to education purposes by our local students. All rights remain with original sources. This list is updated as needed.

1. Principles of Robot Locomotion
2. Howard Choset's textbook Chapter 5 slides
3. roadmap slides
4. Howard Choset's textbook Chapter 2 slides (Bug Algorithms)
5. Potential Fields Tutorial
6. Rodney A. Brooks' original subsumption paper
7. The Subsumption Architecture
8. Affect based Computing
9. Robin Murphy's Emotion-based Control
10. Bayesian Filters for Location Estimation
11. Jong and Stone paper: RL and MDP
12. Henry Hexmoor's High Level Control Loop
13. Hagit Shatkay on HMMs
14. Andrew Moore's HMM Tutorial Slides
15. POMDP FAQ
16. A Fuzzy logic based Navigation System for a Mobile Robot
17. Hexmoor's Fuzzy logic
18. Coverage and Search
19. Brick and Mortar
17. The Scalar Kalman Filter
18. Multirobotics
19. Diana Spears' Swarms paper
20. Alife