Multiple Methods of Data Acquisition for a LEGO NXT 2 Mobile Robot: The use of a Second NXT 2 Hardware Platform

Mechatronics is a multidisciplinary and application oriented science and a methodology used to achieve an optimal design of an electromechanical product. Education in mechatronics at the Politehnica University Timisoara is organized on three levels: bachelor, master and PhD studies. These activities refer to: mechatronic components, computer interfacing electronics, systems (modelling, analysis, simulation, and control). The project discussed in the paper is a Mechatronic Demonstrator using the LEGO NXT-2 Platform. This demonstrator, named humanoid robot, is built at a low price and is suitable for studying the key elements of mechatronic systems: mechanical system dynamics, sensors, computer interfacing, and application development. This paper describes how the demonstrator has been used to validate the methods for data acquisition under experimental conditions. The article aims to describe the demonstrator construction (1), (2) to present the methods for data acquisition (method using two NXT platforms, method using a NXT platforms and oscilloscope, method using Matlab-Simulink) and to formulate conclusions (3).

[1]  Alessandro Gasparetto,et al.  Model Predictive Control of a Flexible Links Mechanism , 2010, J. Intell. Robotic Syst..

[2]  Kiyoshi Hirose,et al.  A Study on the Estimation Method of 3D Posture in Body Motion Measurement Using Inertial Sensors , 2013 .

[3]  Mark Sherriff,et al.  Using LEGO MINDSTORMS NXT and LEJOS in an Advanced Software Engineering Course , 2010, 2010 23rd IEEE Conference on Software Engineering Education and Training.

[4]  Til Aach,et al.  MATLAB Meets LEGO Mindstorms—A Freshman Introduction Course Into Practical Engineering , 2010, IEEE Transactions on Education.

[5]  Bing-Fei Wu,et al.  Particle-Filter-Based Radio Localization for Mobile Robots in the Environments With Low-Density WLAN APs , 2014, IEEE Transactions on Industrial Electronics.

[6]  Karl A. Stol,et al.  Review of modelling and control of two-wheeled robots , 2013, Annu. Rev. Control..

[7]  James A. Reggia,et al.  A virtual demonstrator environment for robot imitation learning , 2015, 2015 IEEE International Conference on Technologies for Practical Robot Applications (TePRA).

[8]  Ching-Chih Tsai,et al.  Adaptive Robust Self-Balancing and Steering of a Two-Wheeled Human Transportation Vehicle , 2011, J. Intell. Robotic Syst..