We are developing a new robotic system to assist or guide visually impaired people in unknown indoor and outdoor environments. The robotic system, which is equipped with a visual sensor, laser range finders, speaker, gives visually impaired people information about the environment around them. The laser data are analyzed using the clustering technique, making it possible to detect obstacles, steps and stairs. In addition, the robot can be switched to the guide mode. By selecting the target location, the robot starts guiding the user toward the goal. The PC analysis the sensors data and send information to the visually impaired people by natural language or beep signal. The usefulness of the proposed system is examined experimentally.
Multi Robot System
The goal of this work is to utilize multiobjective evolution for robot formation. The key focus is to develop an adaptive multi-robot formation algorithm, which means certain geometrical constrains on the relative positions and orientations of the robots throughout their travel. In this new method, we apply multiobjective evolutionary computation to generate the neural networks that control the robots to get to the target position relative to the leader robot. The advantage of the proposed algorithm is that in a single run of multiobjective evolution are generated multiple neural controllers. We can select neural networks that control each robot to get to the target position relative to the leader robot. In addition, the robots can switch to different neural controllers, resulting in multiple geometrical formations. We compare the performance of two formation algorithms: (a) leader based formation (LBF) and (b) follower based formation (FBF).
Humanoid Mobile Platform
We are developing a new mobile humanoid robot for assisting elderly people. The humanoid robot is equipped with a visual sensor to recognize objects. The Laser Range Finder placed in the lower part of mobile platform makes it possible to detect obstacles. After determining the target object, the robot starts moving toward it and then the grasping motion is generated. We address the kinematics, mechatronic and robot specifications. Our goal is to use the mobile humanoid robot for assisting the elderly and work interactively with humans in real environment such as hospitals or homes.
Upper Arm Rehabilitation System
We have developed a robot for human upper arm rehabilitation. The robot moves human arm in different patterns. In addition, by using the camera the human improves the arm motion by tracking the robot motion. Now we are working on learning by immitation, where the robot learns the best training technics.
Brain Machine Interface
The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. We propose a novel method for robot navigation based on rat`s brain signals (Local Field Potentials). We developed an algorithm by which the robot learned to imitate the rat`s decision-making by mapping the rat`s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.