Abstract:
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 progr...Show MoreMetadata
Abstract:
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.
Published in: IEEE Transactions on Education ( Volume: 55, Issue: 1, February 2012)
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- IEEE Keywords
- Index Terms
- Kalman Filter ,
- Mobile Robot ,
- Extended Kalman Filter ,
- Mobile Robot Localization ,
- Real Scenarios ,
- Computer Technology ,
- Electrical Engineering ,
- Faculty Of Engineering ,
- Kinematic ,
- Covariance Matrix ,
- Undergraduate Students ,
- Infrared Imaging ,
- Gaussian Noise ,
- Simulation Scenarios ,
- Control Mode ,
- Path Planning ,
- Probabilistic Method ,
- Particle Filter ,
- Pose Estimation ,
- Odometry ,
- Year Of Curriculum ,
- Automated Guided Vehicles ,
- Estimation Module ,
- Prediction Step ,
- Kalman Gain ,
- Practical Lessons ,
- Nonlinear Estimation ,
- Sensor Readings ,
- Mechatronic
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Kalman Filter ,
- Mobile Robot ,
- Extended Kalman Filter ,
- Mobile Robot Localization ,
- Real Scenarios ,
- Computer Technology ,
- Electrical Engineering ,
- Faculty Of Engineering ,
- Kinematic ,
- Covariance Matrix ,
- Undergraduate Students ,
- Infrared Imaging ,
- Gaussian Noise ,
- Simulation Scenarios ,
- Control Mode ,
- Path Planning ,
- Probabilistic Method ,
- Particle Filter ,
- Pose Estimation ,
- Odometry ,
- Year Of Curriculum ,
- Automated Guided Vehicles ,
- Estimation Module ,
- Prediction Step ,
- Kalman Gain ,
- Practical Lessons ,
- Nonlinear Estimation ,
- Sensor Readings ,
- Mechatronic
- Author Keywords