|
|
|||||||||||||||||
Course Catalog 2013-2014
IHA-3256 Autonomous Mobile Machines, 7 cr |
Additional information
The course is multidisciplinary and demands analytical problem solving, and programming as well. Priory knowledge about all the fields is not required. The term project will be selected based on the background of the group and their interest. The number of students is limited to 14. If the class is full and you are really interested, you can send us email to put you in the reserve list.
Suitable for postgraduate studies
Person responsible
Reza Ghabcheloo, Kalevi Huhtala
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
|
|
|
|
|
|
|
|
Requirements
Requirements will be redefined for year 2013-2014. Last season requirements were: "Completion of homework, presentations, and final paper"
Completion parts must belong to the same implementation
Learning Outcomes
Students learn different challenges in automation of mobile machines. Course is mainly concern with hydraulic mobile machines and is composed of two parts: teaching and student work and emphasis will be on students group work. Teaching starts with commercial state of the art in automation of mobile work machines. It is followed by scientific state of the art, which addresses autonomy and robotics. We will introduce the subsystems of such autonomous machines, problems involved, and solutions. We will then learn how to simulate mechanical mechanisms special to mobile machines. We then cover sensory system used to estimate the state of the machine (location and attitude) as well as the environment (humans, obstacles,...); namely Inertial sensors, wheel odometry, GPS, range sensors, cameras. We will then give some insight to the most common sensor fusion techniques (least square and Kalman Filtering). Some basic motion control techniques are also introduced. The teaching will be concluded by introducing issues related to energy specially Hybrid. However, most of the course will be based on term project. Students will be divided into groups of two, and each group will concentrate on certain problem. Students with special interest are encouraged to work out their ideas. Subjects can also be given by the lecturers. Students will make presentations and discuss their problems, and report the results in a paper format at the end of the course. Development of functional computer codes is the goal of this course. Course demands analytical problem solving, and programming likewise. Real data and simulator will be available.
Instructions for students on how to achieve the learning outcomes
20% presentations + 80 % term project paper and project deliverables
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Partial passing:
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Book | Introduction to Autonomous Mobile Robots | Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza | No | English | |||
| Book | Probabilistic Robotics | Sebastian Thrun, Wolfram Burgard, Dieter Fox | 2005 | No | English | ||
| Book | Springer Handbook of Robotics | Bruno Siciliano, Oussama Khatib (Eds.) | 2008 | No | English | ||
| Book | Where am I? Sensors and Methods for Mobile Robot Positioning | J. Borenstein , H. R. Everett , and L. Feng | 1996 | No | English |
Prerequisites
| Course | Mandatory/Advisable | Description |
| IHA-3506 Robotics and Teleoperation | Advisable | |
| MAT-60606 Mathematics for Positioning | Advisable |
Additional information about prerequisites
The course is multidisciplinary. Priory knowledge about all the fields is not required. The term project will be selected based on the background of the group and their interest.
Prerequisite relations (Requires logging in to POP)
Correspondence of content
| Course | Corresponds course | Description |
|
|
|
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| Students learn different challenges in automation of mobile machines. Course is mainly concern with hydraulic mobile machines and is composed of two parts: teaching and student work and emphasis will be on students group work. Teaching starts with commercial state of the art in automation of mobile work machines. It is followed by scientific state of the art, which addresses autonomy and robotics. We will introduce the subsystems of such autonomous machines, problems involved, and solutions. We will then learn how to simulate mechanical mechanisms special to mobile machines. We then cover sensory system used to estimate the state of the machine (location and attitude) as well as the environment (humans, obstacles,...); namely Inertial sensors, wheel odometry, GPS, range sensors, cameras. We will then give some insight to the most common sensor fusion techniques (least square and Kalman Filtering). Some basic motion control techniques are also introduced. The teaching will be concluded by introducing issues related to energy specially Hybrid. However, most of the course will be based on term project. Students will be divided into groups of two, and each group will concentrate on certain problem. Students with special interest are encouraged to work out their ideas. Subjects can also be given by the lecturers. Students will make presentations and discuss their problems, and report the results in a paper format at the end of the course. Development of functional computer codes is the goal of this course. Course demands analytical problem solving, and programming likewise. Real data and simulator will be available. |
Documents
WhereAmI.pdf ch20.pdf ch22.pdf Autonomous Mobile Machines.pdf Complementary_KF_MotionControl.zip