Design of Distributed Reconfigurable Robotics Systems with ReconROS

Robotics applications process large amounts of data in real time and require compute platforms that provide high performance and energy efficiency. FPGAs are well suited for many of these applications, but there is a reluctance in the robotics community to use hardware acceleration due to increased design complexity and a lack of consistent programming models across the software/hardware boundary. In this article, we present ReconROS , a framework that integrates the widely used robot operating system (ROS) with ReconOS, which features multithreaded programming of hardware and software threads for reconfigurable computers. This unique combination gives ROS 2 developers the flexibility to transparently accelerate parts of their robotics applications in hardware. We elaborate on the architecture and the design flow for ReconROS and report on a set of experiments that underline the feasibility and flexibility of our approach.

Survey on Cloud Robotics and Robot Operating System

The paper proposes cloud robotics which intends five parts which are for software architecture, trends and challenges, design based on a web technology, cloud computing platforms and cloud robotics in practical smart city applications. Software architecture involves lots of different cloud technologies like cloud storage and shared services for robotics for Robot Operating System. There are lots of trends in cloud robotics as it uses cloud technologies for robotics. The use of the cloud for automation brings some largely ameliorating the performance of robotics. Besides, the trends, there are some challenges in cloud robotics. Robot Operating System has been a standard tool in the design for cloud robotics. It always runs at the on-board computer but some resources of CPU do not allow the ability of robotics. In this problem, a good solution is to transfer the task to the cloud. Hence, the design of a cloud robotics middleware is based on web technology. Robotics with cloud computing gives lots of research scopes and research fields. In Smart City Applications, Real-Time Cloud Robotics is present. Real Time Cloud Robotics has emerged as an efficient computing means in data processing applications. By this we introduce CR20 cloud robotics platform that uses real time stream technology virtually to connect to different devices.

An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment

In recent decades, the Timed Elastic Band (TEB) algorithm is widely used for the AGV local path panning because of its convenient and efficiency. However, it may make a local detour when encountering a curve turn and cause excessive energy consumption. To solve this problem, this paper proposed an improved TEB algorithm to make the AGV walk along the wall when turning, which shortens the planning time and saves energy. Experiments were implemented in the Rviz visualization tool platform of the robot operating system (ROS). Simulated experiment results reflect that an amount of 5% reduction in the planning time has been achieved and the velocity curve implies that the operation was relatively smooth. Practical experiment results demonstrate the effectiveness and feasibility of the proposed method that the robots can avoid obstacles smoothly in the unknown static and dynamic obstacle environment.

Implementation and Application of Fall Detection on Mobile Perception Robot

With the rapid increase in the number of people living in the elderly population, reducing and dealing with the problem of falls in the elderly has become the focus of research for decades. It is impossible to completely eliminate falls in daily life and activities. Detecting a fall in time can protect the elderly from injury as much as possible. This article uses the Turtlebot robot and the ROS robot operating system, combined with simultaneous positioning and map construction technology, Monte Carlo positioning, A* path planning, dynamic window method, and indoor map navigation. The YOLO network is trained using the stance and fall data sets, and the YOLOv4 target detection algorithm is combined with the robot perception algorithm to finally achieve fall detection on the turtlebot robot, and use the average precision, precision, recall and other indicators to measure.

Security for the Networked Robot Operating System for Biomedical Applications

Future mechanical frameworks will be arranged in exceptionally organized conditions in which they speak with modern control frameworks, cloud administrations or various other systems at distant areas. In this pattern of solid digitization of modern frameworks (likewise some of the time alluded to as Industry 4.0), digital assaults are an in-wrinkling danger to the uprightness of the automated frameworks at the center of this unique turn of events. It is normal, that the ROS shall assume a significant function in advanced mechanics outside of unadulterated exploration situated situations. ROS anyway has noteworthy security issues which should be tended to before such items should arrive at mass business sectors. Robot Operating System has emerged promptly as an alluring production method at micro and nano scales, particularly in the area of biomedical applications because of its flexibility and condensed size. As disputed to conventional grippers in the field of biomedical applications where mobility is less and show size restriction threats, ROS based micro-grippers are clear from outside power input and yield better mobility. It also has a significant impact on the field of biomedical surgery, where security is a major threat. With the current improvements in wireless communications, Tactile Internet has endorsed a dominant impact. It is regarded as the future huge development which can give current-time regulation in industrial systems, especially in the field of tele surgery. Even though, in remote-surgery environment the data transfer is subjected to various attack points. Hence, in order to understand the real capacity of safe tele-surgery, it is needed to develop a safe verification and key agreement protocol for tele-surgery. We offer here an effective, secure and common verification method in the field of biomedical application in the field of robotic tele-operation. The developed protocol ensures safe interaction samidst the surgeon, robotic arm, and the devoted jurisdiction; The results obtained express the flexibility of the protocol against offline password assuming attacks, replay attacks, imitation attacks, man-in-the-middle attacks, DoS attacks, etc.

Cascaded PID Control System for UAV with Gain Factor Prediction Using ML

Drones are not inherently stable, necessitating the use of a flight controller. If the UAV is properly tuned, the drone will fly steadily; otherwise, it won’t. Hence, we have used a PID (proportional, integral, differential) controller for a stable flight. A well-functioning PID controller should enable amazing climbs and long-range flights. But, when used singly, PID controllers can provide poor performance, resulting in a long settling time, overshoot, and oscillation. Here, we propose a new approach to maneuver UAVs using a PID control system and overcome the shortcomings of using PID controllers in UAVs. This disadvantage is resolved using the Machine Learning polynomial regression model. The gain factors in a PID control system, which is otherwise ideally constant, should be changed in order to reduce the minor instabilities for a smooth flight. Our method has been elaborated and illustrated with suitable diagrams in the following work. When simulated in Gazebo on a Robot Operating System (ROS), our technique is proven to be successful. Keywords: Control Systems, PID, UAV, Drones, Polynomial Regression, Gain Factor, Prediction Algorithm.

A detailed approach to autonomous vehicle control through Ros and Pixhawk controllers

A Polaris MRZR military utility vehicle was used as a testing platform to develop a novel, low cost yet feature-rich, approach to adding remote operation and autonomous driving capability to a military vehicle. The main concept of operation adapts steering and throttle output from a low cost commercially available Pixhawk autopilot controller and translates the signal into the necessary inputs for the Robot Operating System (ROS) based drive by wire system integrated into the MRZR. With minimal modification these enhancements could be applied to any vehicle with similar ROS integration. This paper details the methods and testing approach used to develop this autonomous driving capability.

OntoSLAM: An Ontology for Representing Location and Simultaneous Mapping Information for Autonomous Robots

Autonomous robots are playing an important role to solve the Simultaneous Localization and Mapping (SLAM) problem in different domains. To generate flexible, intelligent, and interoperable solutions for SLAM, it is a must to model the complex knowledge managed in these scenarios (i.e., robots characteristics and capabilities, maps information, locations of robots and landmarks, etc.) with a standard and formal representation. Some studies have proposed ontologies as the standard representation of such knowledge; however, most of them only cover partial aspects of the information managed by SLAM solutions. In this context, the main contribution of this work is a complete ontology, called OntoSLAM, to model all aspects related to autonomous robots and the SLAM problem, towards the standardization needed in robotics, which is not reached until now with the existing SLAM ontologies. A comparative evaluation of OntoSLAM with state-of-the-art SLAM ontologies is performed, to show how OntoSLAM covers the gaps of the existing SLAM knowledge representation models. Results show the superiority of OntoSLAM at the Domain Knowledge level and similarities with other ontologies at Lexical and Structural levels. Additionally, OntoSLAM is integrated into the Robot Operating System (ROS) and Gazebo simulator to test it with Pepper robots and demonstrate its suitability, applicability, and flexibility. Experiments show how OntoSLAM provides semantic benefits to autonomous robots, such as the capability of inferring data from organized knowledge representation, without compromising the information for the application and becoming closer to the standardization needed in robotics.