Localization of Mobile Robots Using an Extended Kalman Filter in a Lego NXT
Bibliographic Data
| ID | 20296558 |
|---|---|
| Authors | Miguel Pinto (0000-0003-4472-3238, Universidade do Porto), António Paulo Moreira (0000-0001-8573-3147, Universidade do Porto), Aníbal Matos, Anı́bal Matos (0000-0002-9771-002X, Universidade do Porto) |
| Year | 2012 |
| Volume | 55 |
| Issue | 1 |
| Pages | 135-144 |
| Publication date | 2012-02-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Education (JOURNAL) |
| Journal identifiers | ISSN: 0018-9359 • E-ISSN: 1557-9638 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/te.2011.2155066 |
| OpenAlex | W1970610490 |
| Language | EN |
| Citations received | 2 |
| References cited | 16 |
The inspiration for this paper comes from a successful experiment conducted with students in the “Mobile Robots” course in the fifth year of the integrated Master's program in the Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. One of the topics in this Mobile Robots course is “ Localization of Mobile Robots using the Extended Kalman Filter in a LEGO NXT,” which gives the students the opportunity to study the concepts of localization. This experiment comes within the framework of teaching localization concepts in mobile robotics and focuses primarily on explaining the Kalman filter concept. It involves a specific tool developed by the authors and based on LEGO NXT technology. The work presented here could be a helpful guide for teaching concepts related to localization in mobile robotics to ensure adequate understanding of the concept and of the use of the extended Kalman filter (EKF). The LegoFeup robot described here was built using a LEGO Mindstorms NXT and tested both in simulation and in real scenarios. Based on the results obtained, the authors concluded that the developed tool is effective in motivating students. The implementation of the tool, the structure of the Mobile Robots course, and the criteria for student assessment are described in this paper
Extended Kalman filter · Human–computer interaction · Kalman filter · Mobile robot · Robot · Robotics · Artificial Intelligence · Computer Science · Educational Tools and Methods · Engineering · Mobile Learning in Education · Open Education and E-Learning
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| Citations per year | 0.17 |
|---|---|
| Citation span | 2014 - 2015 (2) |
| Highly cited | No |