Humanoid Robotics

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  1. Recent updates
  2. Course description
  3. Schedule
  4. Problem sets
  5. Exams
  6. Links

  

1. Recent updates

This course is held is during study period 1 and starts next in September 2014.

 

2. Course description

 

Examiner:

Senior Lecturer Dr. Krister Wolff

 

Eligibility:


In order to be eligible for a second cycle course the applicant needs to fulfil the general and specific entry requirements of the programme that owns the course. (If the second cycle course is owned by a first cycle programme, second cycle entry requirements apply.)
Exemption from the eligibility requirement: Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling these requirements.

Course specific prerequisites

Basic mathematical and programming skills are required. It is recommended to be familiar with programming of microcontrollers. In addition, it is advantageous (but not absolutely necessary) to have taken the course FFR125 Autonomous Agents, or similar.

Aim

The course aims at giving the students (1) a basic understanding of the theory of humanoid robots, i.e. bipedal walking robots with an approximately humanlike shape, and (2) practical knowledge concerning humanoid robots, through a robot construction project.

Learning outcome (after completion of this course, the student should be able to)

 

  • Understand and describe the specific properties of humanoid robots, and state-of-the-art.
  • Derive and apply the kinematic equations for a basic robot system.
  • Understand the different methods for bipedal gait generation, i.e. zero moment point, central pattern generators and linear genetic programming.
  • Describe other motor behaviours (such as e.g. dexterous manipulation) for humanoid robots.
  • Apply algorithms for computer vision.
  • Have a basic understanding of sensors, actuators and other hardware in connection with humanoid robots.
  • Discuss and describe the advantages and disadvantages of humanoid robotics in relation to other kinds of robots.
  • Describe the potential roles of humanoid robots in society, w.r.t. social and ethical aspects, and applications.
  • Understand and discuss technical challenges with humanoid robots.
  • Apply the course knowledge in connection with a humanoid project

 

Content

 

  • Introduction to humanoid robots
  • State of the art
  • Kinematics
  • Synthetization of bipedal gait; CPGs, ZMP, LGP
  • Other motor behaviours
  • Robot vision
  • Behavior based robotics
  • Hardware for humanoid robots
  • Applications
  • Robot interaction
  • Humanoid robots in society
  • Project planning

 

Organisation

 

The course consist of lectures and lab sessions. In the lectures, the theory of humanoid robotics is covered and some (individual) assignments are given out. Next, the students select a humanoid robot project which is carried out in groups of 2-4 students. The results obtained in the different projects should be demonstrated in the class and a written report must be handed in.

For further details, please refer to the course home page.

 

Literature

 

Lecture notes, scientific papers, and handouts. The material will be made available via the course web page.

 

Examination

The examination consists of a graded take-home exam and a project report. The obtained partial grades will weighted together for a final course grade. For the project grade the total accomplishment of the project, as well as organization and structure, and documentation (planning report and final report) contribute. Oral presentation of the project is mandatory, but not included in the grade.

3. Schedule

Please have a look on the external course webpage for more information.

4. Problem sets

Please have a look on the external course webpage for more information.

5. Exams

Please have a look on the external course webpage for more information.

6. Links

External course webpage: http://www.am.chalmers.se/~wolff/Courses/TIF160/

Krister Wolff

Senior lecturer

Krister Wolff is doing research within bio-inspired computational methods for optimization in connection with autonomous robots and intelligent vehicle technologies, e.g. development of active safety systems for vehicles and driver modeling.