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• Trajectory Control of Designed Experimental Mobile Robot

  1-5.

  Şahin Yildirim

  Berkay Eren

  Views:

  255

  Due to advancing technology; nowadays mobile robot applications in hospitals have been increased. For that reason, it is very important and necessary to analyze the trajectory of such helping robotic system. However; there are many types of mobile robots have been utilized in hospital applications such as helping nurses. In this simulation study; a designed and controlled mobile robot was controlled by using standard feedback controllers. On the other hand, the robot was also tested with disturbances of ground surface roughness. The simulation results were improved that standard PID controller has superior performance to overcome surface roughness of the robot trajectory.

• ROS OS Based Environment Mapping of Cyber Physical System Lab by Depth Sensor

  1-6

  Rohit Singh Chauhan

  Timotei István Erdei

  Géza Husi

  Views:

  195

  The 21^st century is a century of Robotics and thus the appearance of robots in the industries made the “Industrial Revolution 4.0” in which we can control and analyse the system using HMI’s or wirelessly over network and it’s a great example of industry 4.0 component. Nowadays robots are very important part of industry’s processing unit as they have the tendency to work 24*7 thus increases the efficiency of processing and production unit.

   In our project a depth sensor (Microsoft’s Xbox Kinect) is mounted on a mobile robot whose main task is to map our Cyber Physical System Lab in 3-Dimensional which uses a ROS OS software installed on linux machine.

   The robot will use a Simultaneous localization and mapping (SLAM) process to map an environment while currently generating an estimate for the location of the Robot.

• A Review Regarding Deep Learning Technology in Mobile Robots

  1-5.

  Vlad Ovidiu Mihalca

  Flaviu Birouaș

  Florin Avram

  Arnold Nilgesz

  Views:

  89

  Deep Learning usage is spread across many fields of application. This paper presents details from a selected variety of works published in recent years to illustrate the versatility of the Deep Learning techniques, their potential in current and future research and industry applications as well as their state-of-the-art status in vision tasks, where their efficiency is experimentally proven to near 100% accuracy. The presented applications range from navigation to localization, object recognition and more advanced interactions such as grasping.

• Android Based Autonomous Mobile Robot

  1-4.

  Gergely Nagymáté

  Views:

  103

  The spreading of mobile robots is getting more significant nowadays. This is due to their ability to perform tasks that are dangerous, uncomfortable or impossible to people. The mobile robot must be endowed with a wide variety of sensors (cameras, microphones, proximity sensors, etc.) and processing units that makes them able to navigate in their environment. This generally carried out with unique, small series produced and thus expensive equipment. This paper describes the concept of a mobile robot with a control unit integrating the processing and the main sensor functionalities into one mass produced device, an Android smartphone. The robot is able to perform tasks such as tracking colored objects or human faces and orient itself. In the meantime, it avoids obstacles and keeps the distance between the target and itself. It is able to verbally communicate wit.