Blinking and eye movement are one of the most important abilities that most people have, even people with spinal cord problem. By using this ability these people could handle some of their activities such as moving their wheelchair without the help of others. One of the most important fields in Human-Robot Interaction is the development of artificial limbs working with brain signals. The purpose of this project consists in detecting blinking and left and right eye movements via electroencephalogram signals which is also useful in determining sleepiness. Moving Window, Fast Fourier Transform and Wavelet Transform are the methods which are used in this project. Obtained results reveal that the most reliable method to recognize blinking and eye movements is Fast Fourier Transform since it is almost insensitive and invariant to the defined variables. After recognition of blinking and eye movement, these actions are transferred to a robot which is called the spherical 2-DOFparallel robot, built first at the Laval University.

For control robotics and mechatrnics systems a special glove is designed which cancontrol the robots by moving only two fingers and the wrist. Cheap and open source technology has also been used in TL-HCG(Taarlab-hand controlled glove) design.

Easy and innovative robot control is one of the advantages of this glove and also different actuators without the need of side controls like different kinds of joy sticks.

This creative control with the ability to exclude several hardware interfaces and real time performance enables the ability to create ideas and products across various industries for the humans and robots interaction. The performance of this glove has been tested on TL-OSR(Taarlab-Open Source Robots) and the robot is controlled by sensory data fusion and by using fuzzy logic by hand gestures. These technics can be used for helping the disabled and handicapped people, treatment for children with autism or making new control systems for mechatronic devices.

In this research, by means of the identified system derived from the common online recursive least square (RLS) method, 2 types of controllers, PID and Sliding mode Controller, were applied on the 2-DoF Agile Eye to track a ball. Some common algorithms in Image Processing (for for the purpose of color filteration, noise reduction and so on) were also hired to optimize ball detection in a common space with all noises and relatively close colors to the ball (also the other constrains forced from camera and even light in the environment). Furtheremore, an Auto Regressive(AR) model was used to predict the steps ahead of the ball movement to diminish the latency in response ,then approach to a relatively real-time system. Moreover, awared selection of existed C++ scripts and OpenCV libraries in this project, helped us to save time and never try to "reinvent a wheel again!". On another side, designing a GUI for this work was another barrior which finally ended up with a simple one just to show the all events together. As a conclusion, the results of this study were compared and published in ICROM 2014. 

Any robots after build and developed control systems must be tested on standard environment.

This platform are allow user test their robots and improve robots abilities in best way. This platform can permit researchers to test their robots on three rotational degrees of freedom as known as roll, pitch and yaw.

Low cost production is one of this mechanism’s feature. Researchers can choose any rotational degrees of freedom optional or use there combination to each other. For example use roll, pitch and yaw independently or combination roll-pitch and yaw-roll and etc.

On upper plate (robots stand on it) in this platform installed 6-DOF sensor to measure rotation and comparison with robots data and used for other types of researchers demand.

Until now this platform is used for 2-DOF spherical robot (agile-eye) and NAO.