Adaptive Systems Research Group

Autonomous agents (FFR125), LP3-4 (third and fourth quarters), 2016

Lecturer (third quarter) and examiner: Professor Mattias Wahde, Tel: 772 3727, e-mail: mattias.wahde@chalmers.se
Lecturer (fourth quarter): Dr. Krister Wolff, Tel: 772 3625, e-mail: krister.wolff@chalmers.se
Course assistant: Luca Caltagirone, e-mail: luca.caltagirone@chalmers.se

Literature: Wahde, M., Introduction to Autonomous Robots, Compendium, Chalmers, 2016

Preliminary program

Note: The very first lecture, on Jan. 18, starts at 08.00, not 10.00, and in a different room (HB3) than the other Mondays!

Date

Time

Room

Contents

20160118

08.00-09.45

HB3

Course introduction and motivation

20160121

08.00-09.45

KC

Autonomous robots: Background and introduction. Sensors, actuators, and processors,
pp. 1-20

20160125

10.00-11.45

KB

Kinematics and dynamics of wheeled robots, pp. 21-28

20160128

08.00-09.45

KC

Simulation of autonomous robots, pp. 29-44

20160201

 10.00-11.45 KB

Animal behavior: Lessons for robotics, pp. 45-54. Handout of home problem 1

20160204

 08.00-09.45 KC

Approaches to robot intelligence. Basic robotic brain processes, pp. 55-66

20160208

10.00-11.45

KB

Robotic behaviors I. Exploration and navigation (1), pp. 67-77

20160211

08.00-09.45

KC

Robotic behaviors II. Exploration and navigation (2), pp. 77-84.
Deadline for home problem 1

20160215

10.00-11.45

KB

 Robotic behaviors III. Localization, pp. 85-92. Handout of home problem 2

20160218



No lecture

20160222

10.00-11.45

KB

Behavioral economics: The concept of utility, pp. 93-104.

20160225

08.00-09.45

KC

Decision-making in autonomous robots, pp. 105-112

20160229

10.00-11.45

 KB

Applications: Autonomous vehicles, software agents, financial agents etc.

20160303



No lecture

20160307

10.00-11.45

KB

Course summary, Deadline for home problem 2

20160310

08.00-09.45

KC

Introduction to the robotics projects (4th quarter)

Slides, other handouts, home problems, web links, demonstration programs, and videos

20160118 Course memo (kurs-pm)
20160118 Slides from Lecture 1
20160121 Slides from Lecture 2
20160121 Quiz from Lecture 2
20160125 Slides from Lecture 3
20160126 Quiz from Lecture 3
20160128 Slides from Lecture 4
20160128 Quiz from Lecture 4
20160201 Slides from Lecture 5
20160201 Scientific paper relevant for Lecture 5:
                   Wehner, R. Desert and navigation: how miniature brains solve complex tasks, J. Comp. Physiol, 189, pp. 579-588, 2003
20160201 Quiz from Lecture 5
20160201 Home problem 1 (Deadline: 20160211)
20160201 ARSim_HP1.2.zip (needed for HP1.2)
20160201 ARSim_HP1.3.zip (needed for HP1.3)
20160201 Matlab coding standard (read carefully before starting with the home problems!
20160201 Checklist for home problem submission (read carefully before submitting your solutions!)
20160204 Slides from Lecture 6
20160204 (No quiz today, but do implement the two simple robot behaviors in Chapter 5).
20160208 Slides from Lecture 7
20160208 Quiz from lecture 7
20160211 Slides from Lecture 8
20160211 Quiz from Lecture 8
20160215 Home problem 2 (Deadline 20160307)
20160215 Video illustrating Dijkstra's method
20160215 ColorGrid.m (needed for HP2.1)
20160215 EColiSimulator.zip (needed for HP2.2)
20160215 ARSim_HP2.3.zip (needed for HP2.3)
20160215 ARSim_HP2.4.zip (needed for HP2.4)
20160215 Slides from Lecture 9
20160215 Quiz from Lecture 9
20160222 Slides from Lecture 10
20160222 Quiz from Lecture 10
20160225 Slides from Lecture 11
20160225 Quiz from Lecture 11
20160229 Slides from Lecture 12
20160229 (No quiz today)
20160229 Practice exam questions
20160229 Solutions to the practice exam questions
20160307 Slides from Lecture 13
20160307 (No quiz today)
20160307 Link to the web page for the robotics work (fourth quarter)
Examination and grade requirements

Exam: 20160315 Maximum score: 25p.
Home problems: Maximum (total) score: 25p

Grade requirements: A minimum of 10p is required on the exam for a passing grade. In addition, you must (as a minimum) correctly solve the mandatory home problems (which will be marked on the problem sheets) and complete the robotics projects in the fourth quarter. The requirements for the various grades are as follows (the numbers refer to the sum of the exam result and the results on the two home problems, maximum 50 p in total)

Chalmers:
5   Total score in [42,50]
4   Total score in [33,41.5]
3   Total score up to 32.5 (but note also the minimum requirements listed above)

GU:
VG: Total score in [39,50]
G: Total score up to 38.5 (but note also the minimum requirements listed above)

ECTS grades: A=5, B=4, C=3, D = weak 3 (total score below 25).
FAQ

Q1. In HP1.2, must we handle the case when the robot reaches the end of the wall?
A1. No. For the purpose of this problem, you can just assume that the wall is infinite.

Q2. When will the exam take place?
A2. The exam will take place on March 15, 14.00-18.00.

Q3. When will HP1 be returned?
A3. Hopefully on Thursday (Feb. 25). At the latest on Monday (Feb. 29)

Q4. Will you provide some practice exams?
A4. Yes, I will upload some old exam questions (and solutions) on Monday (Feb. 29).

Q5. In HP2.4, how can one recalibrate the odometer when BrainStep only returns b (the brain) rather than the robot (r)?
A5. A simple solution, of course, is to modify BrainStep so that it does return the robot instead of the brain. However, one should normally not modify a given interface (Imagine a situation where several people are developing program code for a robot - one must then be able to rely on everyone following the defined interfaces). An alternative solution is to append the odometer to the Localization struct (i.e. Localization.Odometer ...). In that case, this must be done in each step of the main loop (in RunRobot), which may be modified. I prefer the second solution, but I will allow the first solution as well.

Q6. How does one get the feedback from HP1?
A6. The results have been handed out in class, and there have been several opportunities to obtain the results. Those who have missed those opportunities can either (i) obtain the results in class (for example today (20160307) or on Thursday), (ii) pass by my office to pick up the results.
Last update: 20160307, 09.45