Learning Control of Robotic Arm Using Deep Q-Neural Network

Enabling robotic systems for autonomous actions such as driverless systems, is a very complex task in real-world scenarios due to uncertainties. Machine learning capabilities have been quickly making their way into autonomous systems and industrial robotics technology. They found many applications in every sector, including autonomous vehicles, humanoid robots, drones and many more. In this research we will be implementing artificial intelligence in robotic arm to be able to solve a complex balancing control problem from scratch, without any feedback loop and using state of the art deep reinforcement learning algorithm named DQN. The benchmark problem that is considered as case study, is balancing an inverted pendulum upward using a six-degrees freedom robot arm. Very simple form of this problem has been solved recently using machine learning however under this thesis we made a very complex system of inverted pendulum and implemented in Robot Operating System (ROS) which is very realistic simulation environment. We have not only succeeded to control the pendulum but also added turbulences on the learned model to study its robustness. We observed how the initial learned model is unstable at the presence of turbulence and how random turbulences helps the system to transform to a more robust model. We have also used the robust model in different environment and showed how the model adopt itself with the new physical properties. Using orientation sensor on the tip of the inverted pendulum to get angular velocity, simulation in ROS and having inverted pendulum on ball joint are few highlighted novelties in this thesis in compare previous publications

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

Indoor Geo-location And Tracking Of Mobile Autonomous Robot

The field of robotics has always been one of fascination right from the day of Terminator. Even though we still do not have robots that can actually replicate human action and intelligence, progress is being made in the right direction. Robotic applications range from defense to civilian, in public safety and fire fighting. With the increase in urban-warfare robot tracking inside buildings and in cities form a very important application. The numerous applications range from munitions tracking to replacing soldiers for reconnaissance information. Fire fighters use robots for survey of the affected area. Tracking robots has been limited to the local area under consideration. Decision making is inhibited due to limited local knowledge and approximations have to be made. An effective decision making would involve tracking the robot in earth co-ordinates such as latitude and longitude. GPS signal provides us sufficient and reliable data for such decision making. The main drawback of using GPS is that it is unavailable indoors and also there is signal attenuation outdoors. Indoor geolocation forms the basis of tracking robots inside buildings and other places where GPS signals are unavailable. Indoor geolocation has traditionally been the field of wireless networks using techniques such as low frequency RF signals and ultra-wideband antennas. In this thesis we propose a novel method for achieving geolocation and enable tracking. Geolocation and tracking are achieved by a combination of Gyroscope and encoders together referred to as the Inertial Navigation System (INS). Gyroscopes have been widely used in aerospace applications for stabilizing aircrafts. In our case we use gyroscope as means of determining the heading of the robot. Further, commands can be sent to the robot when it is off balance or off-track. Sensors are inherently error prone; hence the process of geolocation is complicated and limited by the imperfect mathematical modeling of input noise. We make use of Kalman Filter for processing erroneous sensor data, as it provides us a robust and stable algorithm. The error characteristics of the sensors are input to the Kalman Filter and filtered data is obtained. We have performed a large set of experiments, both indoors and outdoors to test the reliability of the system. In outdoors we have used the GPS signal to aid the INS measurements. When indoors we utilize the last known position and extrapolate to obtain the GPS co-ordinates

Unmanned Robotic Systems and Applications

This book presents recent studies of unmanned robotic systems and their applications. With its five chapters, the book brings together important contributions from renowned international researchers. Unmanned autonomous robots are ideal candidates for applications such as rescue missions, especially in areas that are difficult to access. Swarm robotics (multiple robots working together) is another exciting application of the unmanned robotics systems, for example, coordinated search by an interconnected group of moving robots for the purpose of finding a source of hazardous emissions. These robots can behave like individuals working in a group without a centralized control

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)

Case Study on Human-Robot Interaction of the Remote-Controlled Service Robot for Elderly and Disabled Care

The tendency of continuous aging of the population and the increasing number of people with mobility difficulties leads to increased research in the field of Assistive Service Robotics. These robots can help with daily life tasks such as reminding to take medications, serving food and drinks, controlling home appliances and even monitoring health status. When talking about assisting people in their homes, it should be noted that they will, most of the time, have to communicate with the robot themselves and be able to manage it so that they can get the most out of the robot's services. This research is focused on different methods of remote control of a mobile robot equipped with robotic manipulator. The research investigates in detail methods based on control via gestures, voice commands, and web-based graphical user interface. The capabilities of these methods for Human-Robot Interaction (HRI) have been explored in terms of usability. In this paper, we introduce a new version of the robot Robco 19, new leap motion sensor control of the robot and a new multi-channel control system. The paper presents methodology for performing the HRI experiments from human perception and summarizes the results in applications of the investigated remote control methods in real life scenarios

A path planning and path-following control framework for a general 2-trailer with a car-like tractor

Maneuvering a general 2-trailer with a car-like tractor in backward motion is a task that requires significant skill to master and is unarguably one of the most complicated tasks a truck driver has to perform. This paper presents a path planning and path-following control solution that can be used to automatically plan and execute difficult parking and obstacle avoidance maneuvers by combining backward and forward motion. A lattice-based path planning framework is developed in order to generate kinematically feasible and collision-free paths and a path-following controller is designed to stabilize the lateral and angular path-following error states during path execution. To estimate the vehicle state needed for control, a nonlinear observer is developed which only utilizes information from sensors that are mounted on the car-like tractor, making the system independent of additional trailer sensors. The proposed path planning and path-following control framework is implemented on a full-scale test vehicle and results from simulations and real-world experiments are presented.Comment: Preprin

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion