Robot Operating System Node Research Articles

An Indoor Localization System for Automotive Driving Competitions

Localization, in both indoor and outdoor settings, represents a problem that has received increased attention lately. This paper presents the development, testing, and validation of an indoor localization system for 1/10 scale vehicles based on the Robot Operating System (ROS) and ArUco marker detection. It has a distributed architecture, consisting of tens of Raspberry Pi (RPi) singleboard computers running ROS nodes and fitted with cameras, that monitor a certain area of the 14x14 m plane. The developed system has been successfully used in three editions of Bosch Future Mobility Challenge, an international student competition, where the participants are required to implement autonomous driving functionalities in an environment resembling a real-life city on small-scale automated vehicles.

Kinematics Calibration and Validation Approach Using Indoor Positioning System for an Omnidirectional Mobile Robot.

Monitoring and tracking issues related to autonomous mobile robots are currently intensively debated in order to ensure a more fluent functionality in supply chain management. The interest arises from both theoretical and practical concerns about providing accurate information about the current and past position of systems involved in the logistics chain, based on specialized sensors and Global Positioning System (GPS). The localization demands are more challenging as the need to monitor the autonomous robot's ongoing activities is more stringent indoors and benefit from accurate motion response, which requires calibration. This practical research study proposes an extended calibration approach for improving Omnidirectional Mobile Robot (OMR) motion response in the context of mechanical build imperfections (misalignment). A precise indoor positioning system is required to obtain accurate data for calculating the calibration parameters and validating the implementation response. An ultrasound-based commercial solution was considered for tracking the OMR, but the practical observed errors of the readily available position solutions requires special processing of the raw acquired measurements. The approach uses a multilateration technique based on the point-to-point distances measured between the mobile ultrasound beacon and a current subset of fixed (reference) beacons, in order to obtain an improved position estimation characterized by a confidence coefficient. Therefore, the proposed method managed to reduce the motion error by up to seven-times. Reference trajectories were generated, and robot motion response accuracy was evaluated using a Robot Operating System (ROS) node developed in Matlab-Simulink that was wireless interconnected with the other ROS nodes hosted on the robot navigation controller.

ReconfROS: An approach for accelerating ROS nodes on reconfigurable SoCs

In this paper, we present an approach to integrate reconfigurable SoCs into the well known Robot Operating System (ROS) called ReconfROS. Our method allows to implement hardware-accelerated algorithms on FPGAs and integrates them directly into the ROS ecosystem. This allows to combine the established and well tested ROS infrastructure together with low-power hardware acceleration. As a proof-of-concept for this novel integration, we ported an existing image-based path-following algorithm onto an FPGA and tested it on an unmanned ground vehicle (UGV). Evaluations utilizing the FPGA-accelerator directly synthesized from C-code show a three times performance improvement combined with a 15 times reduction of energy per frame. The approach can be easily ported to different hardware platforms based on Xilinx reconfigurable SoCs.

Bio-inspired navigation and exploration system for a hexapod robotic platform

This paper presents a biologically inspired system for guiding and controlling a virtual hexapod robot. Our navigation and exploration system is composed of subsystems that execute processes of path integration, action selection, actuator control and correction of the robot’s orientation. For the subsystem that serves the path integration function we modified an existing model of bio-inspired vector summation by adding the capability of performing online calculation. For the action selection subsystem that allows to switch between the behaviors of exploration, approaching a target and homing we modified an existing model of decision making for mediating social behaviors in mice. We added an additional circuit that projects a signal to the units representing each of the behaviors. In the case of the actuator control subsystem, the structure of a central pattern generator model that incorporates feedback and adaptation was used as the base for generating and transforming signals for the actuators. Finally, the orientation correction subsystem is a novel model that determines an error value from a desired and the current orientations. The proposed models were simulated as independent scripts and then implemented as ROS (Robot Operating System) nodes for controlling a robot simulation in Gazebo.

Generic Development of Bin Pick-and-Place System Based on Robot Operating System

Bin pick-and-place is an important topic in factory automation and warehouse automation. In this paper, a bin pick-and-place system based on robot operating system (ROS) is implemented to make a six-degree-of-freedom (6-DOF) robot manipulator to complete multiple pick-and-place tasks. The proposed system uses ROS to integrate an object perception module and a pick-and-place module, where the former uses an RGB-D camera to capture images inside the bin, and the latter controls a 6-DOF robot manipulator and two self-made vacuum tools. To estimate the pose of the target object, a YOLOv4 object detector is implemented, and an object sorting method is proposed to find the target object in the image. Then, a pose estimation method based on computer aided design (CAD) is proposed to estimate the pose of target object. To perform the object pick-and-place operations, a coordinate transformation node is designed to transfer the pose of the target object into the workspace. Then, a link distance-based bin collision avoidance method is proposed to avoid collisions. Finally, the angle of the 1-DOF vacuum tool and the picking and placement poses of the robot manipulator are obtained from the result of the bin collision avoidance and the pose of the target object. In this study, a total of ten ROS nodes are designed, and the solutions that make each function easier to implement and reproduce are proposed. In the experiments, we set up four experiments with two task types and two object types to verify the effectiveness of the implemented bin pick-and-place system.

Design and Testing of Two Haptic Devices Based on Reconfigurable 2R Joints

This paper presents the design and testing of two haptic devices, based on reconfigurable 2R joints: an active 2R spherical mechanism-based joint and a differential gear-based joint. Based on our previous works, in which the design and kinematic analysis of both reconfigurable joints were developed, the experimental setup and the various tasks intended to test the reconfigurability, precision, force feedback system and general performance, are presented herein. Two control modes for the haptic device operation are proposed and studied. The statistical analysis tools and their selection principles are described. The mechanical design of two experimental setups and the main elements are considered in detail. The Robot Operating System nodes and the topics that are used in the software component of the experimental setup are presented and explained. The experimental testing was carried out with a number of participants and the corresponding results were analyzed with the selected statistical tools. A detailed interpretation and discussion on of the results is provided.

The Integration of GPS/BDS Real-Time Kinematic Positioning and Visual–Inertial Odometry Based on Smartphones

The real-time kinematic positioning technique (RTK) and visual–inertial odometry (VIO) are both promising positioning technologies. However, RTK degrades in GNSS-hostile areas, where global navigation satellite system (GNSS) signals are reflected and blocked, while VIO is affected by long-term drift. The integration of RTK and VIO can improve the accuracy and robustness of positioning. In recent years, smartphones equipped with multiple sensors have become commodities and can provide measurements for integrating RTK and VIO. This paper verifies the feasibility of integrating RTK and VIO using smartphones, and we propose an improved algorithm to integrate RTK and VIO with better performance. We began by developing an Android smartphone application for data collection and then wrote a Python program to convert the data to a robot operating system (ROS) bag. Next, we established two ROS nodes to calculate the RTK results and accomplish the integration. Finally, we conducted experiments in urban areas to assess the integration of RTK and VIO based on smartphones. The results demonstrate that the integration improves the accuracy and robustness of positioning and that our improved algorithm reduces altitude deviation. Our work can aid navigation and positioning research, which is the reason why we open source the majority of the codes at our GitHub.

Design of Autonomous Mobile Robot for Cleaning in the Environment with Obstacles

This paper describes the design and development of a cleaning robot, using adaptive manufacturing technology and its use with a control algorithm for which there is a stability proof. The authors’ goal was to fill the gap between theory and practical implementation based on available low-cost components. Adaptive manufacturing was chosen to cut down the cost of manufacturing the robot. Practical verification of the effectiveness of the control algorithm was achieved with the experiments. The robot comprises mainly three assemblies, a four-wheel-drive platform, a four-degrees-of-freedom robotic arm, and a vacuum system. The inlet pipe of the vacuum system was attached to the end effector of the robotic arm, which makes the robot more flexible to clean uneven areas, such as skirting on floors. The robot was equipped with a LIDAR sensor and web camera, giving the opportunity to develop more complex methods. A low-level proportional–integral–derivative (PID) speed controller was implemented, and a high-level controller that uses artificial potential functions to generate repulsive components, which avoids collision with obstacles. Robot operating system (ROS) was installed in the robot’s on-board system. With the help of the ROS node, the high-level controller generates control signals for the low-level controller.

Develop Real-Time Robot Control Architecture Using Robot Operating System and EtherCAT

This paper presents the potential of combining ROS (Robot Operating System), its state-of-art software, and EtherCAT technologies to design real-time robot control architecture for human–robot collaboration. For this, the advantages of an ROS framework here are it is easy to integrate sensors for recognizing human commands and the well-developed communication protocols for data transfer between nodes. We propose a shared memory mechanism to improve the communication between non-real-time ROS nodes and real-time robot control tasks in motion kernel, which is implemented in the ARM development board with a real-time operating system. The jerk-limited trajectory generation approach is implemented in the motion kernel to obtain a fine interpolation of ROS MoveIt planned robot path to motor. EtherCAT technologies with precise multi-axis synchronization performance are used to exchange real-time I/O data between motion kernel and servo drive system. The experimental results show the proposed architecture using ROS and EtherCAT in hard real-time environment is feasible for robot control application. With the proposed architecture, a user can efficiently send commands to a robot to complete tasks or read information from the robot to make decisions, which is helpful to reach the purpose of human–robot collaboration in the future.

Hardware in the Loop Topology for an Omnidirectional Mobile Robot Using Matlab in a Robot Operating System Environment

The symmetry of the omnidirectional robot motion abilities around its central vertical axis is an important advantage regarding its driveability for the flexible interoperation with fixed conveyor systems. The paper illustrates a Hardware in the Loop architectural approach for integrated development of an Ominidirectional Mobile Robot that is designed to serve in a dynamic logistic environment. Such logistic environments require complex algorithms for autonomous navigation between different warehouse locations, that can be efficiently developed using Robot Operating System nodes. Implementing path planning nodes benefits from using Matlab-Simulink, which provides a large selection of algorithms that are easily integrated and customized. The proposed solution is deployed for validation on a NVIDIA Jetson Nano, the embedded computer hosted locally on the robot, that runs the autonomous navigation software. The proposed solution permits the live connection to the omnidirectional prototype platform, allowing to deploy algorithms and acquire data for debugging the location, path planning and the mapping information during real time autonomous navigation experiments, very useful in validating different strategies.

A Backseat Control Architecture for a Slocum Glider

Adaptive sampling provides an innovative and favorable method of improving the effectiveness of underwater vehicles in collecting data. Adaptive sampling works by controlling an underwater vehicle by using measurements from sensors and states of the vehicle. A backseat driver system was developed in this work and installed on a Slocum glider to equip it with an ability to perform adaptive sampling tasks underwater. This backseat driver communicated with the main vehicle control system of the glider through a robot operating system (ROS) interface. The external control algorithms were implemented through ROS nodes, which subscribed simulated sensor measurements and states of the glider and published desired states to the glider. The glider was set up in simulation mode to test the performance of the backseat driver as integrated into the control architecture of the glider. Results from the tests revealed that the backseat driver could effectively instruct the depth, heading, and waypoints as well as activate or deactivate behaviors adaptively. The developed backseat driver will be tested in future field experiments with sensors included and safety rules implemented before being applied in adaptive sampling missions such as adaptive oil spill sampling.

A ROS-Based Open Tool for Intelligent Robotics Education

This paper presents an open-access platform for practical learning of intelligent robotics in engineering degrees: Robotics-Academy. It comprises a collection of exercises including recent service robot applications in real life, with different robots such as autonomous cars, drones or vacuum cleaners. It uses Robot Operating System (ROS) middleware, the de facto standard in robot programming, the 3D Gazebo simulator and the Python programming language. For each exercise, a software template has been developed, performing all the auxiliary tasks such as the graphical interface, connection to the sensors and actuators, timing of the code, etc. This also hosts the student’s code. Using this template, the student just focuses on the robot intelligence (for instance, perception and control algorithms) without wasting time on auxiliary details which have little educational value. The templates are coded as ROS nodes or as Jupyter Notebooks ready to use in the web browser. Reference solutions for illustrative purposes and automatic assessment tools for gamification have also been developed. An introductory course to intelligent robotics has been elaborated and its contents are available and ready to use at Robotics-Academy, including reactive behaviors, path planning, local/global navigation, and self-localization algorithms. Robotics-Academy provides a valuable complement to master classes in blended learning, massive online open courses (MOOCs) and online video courses, devoted to addressing theoretical content. This open educational tool connects that theory with practical robot applications and is suitable to be used in distance education. Robotics-Academy has been successfully used in several subjects on undergraduate and master’s degree engineering courses, in addition to a pre-university pilot course.

PUT-Hand—Hybrid Industrial and Biomimetic Gripper for Elastic Object Manipulation

In this article, the design of a five-fingered anthropomorphic gripper is presented specifically designed for the manipulation of elastic objects. The manipulator features a hybrid design, being equipped with three fully actuated fingers for precise manipulation, and two underactuated, tendon-driven digits for secure power grasping. For ease of reproducibility, the design uses as many off-the-shelf and 3D-printed components as possible. The on-board controller circuit and firmware are also presented. The design includes resistive position and angle sensors in each joint, resulting in full joint observability. The controller has a position-based controller integrated, along with USB communication protocol, enabling gripper state reporting and direct motor control from a PC. A high-level driver operating as a Robot Operating System node is also provided. All drives and circuitry of the PUT-Hand are integrated within the hand itself. The sensory system of the hand includes tri-axial optical force sensors placed on fully actuated fingers’ fingertips for reaction force measurement. A set of experiments is provided to present the motion and perception capabilities of the gripper. All design files and source codes are available online under CC BY-NC 4.0 and MIT licenses.

Bootstrapping MDE Development from ROS Manual Code

Ten years after its rst release, the Robot Operating System (ROS) is arguably the most popular software framework used to pro- gram robots. It achieved such status despite its shortcomings compared to alternatives similarly centered on manual programming and, perhaps surprisingly, to model-driven engineering (MDE) approaches. Based on our experience, we identied possible ways to leverage the accessibility of ROS and its large software ecosystem, while providing quality assurance measures through selected MDE techniques. After describing our vision on how to combine MDE and manually written code, we present the rst technical contribution in this pursuit: a family of three metamodels to respectively model ROS nodes, communication interfaces, and sys- tems. Such metamodels can be used, through the accompanying Eclipse- based tooling made publicly available, to model ROS systems of arbitrary complexity and generate with correctness guarantees the software arti- facts for their composition and deployment. Furthermore, they account for specications on these aspects by the Object Management Group (OMG), in order to be amenable to hybrid systems coupling ROS and other frameworks. We also report on our experience with a large and complex corpus of ROS software including the shortcomings of standard ROS tools and of previous eorts on ROS modeling.

Implementation of Nonlinear Adaptive U-Model Control Synthesis Using a Robot Operating System for an Unmanned Underwater Vehicle

This paper presents the development of unmanned marine robotic control modelling and control synthesis using a coupled multivariable underactuated nonlinear adaptive U-model approach. The proposed controller was developed using thru an open source robot operating system (ROS) platform. The new adaptive coupled U-model based internal model control (IMC) node was successfully developed and tested. The proposed controller demonstrated the simplicity of the control synthesis process and the implementation of the mathematical algorithm in real-time. The controller was compared with the proven existing GIRONA 500 UUV for real-time performance. The ROS environment provides fast and reliable controller design and development compared to conventional software architecture. Simulation and real-time experiment were conducted using ROS via the GIRONA 500 UUV platform and compared with a PID mission controller. A new ROS node of nonlinear adaptive U-model based IMC was developed using ROS. The results showed good control signal convergence and tracking performance between the plant or system model with the proposed method.

Autonomous Object Pick-and-Sort Procedure for Industrial Robotics Application

This paper describes an industrial robotics application, named Gilbreth, for autonomously picking up objects of different types from a moving conveyor belt and sorting the objects into bins according to their type. The environment, which consists of a moving conveyor belt, a break beam sensor, a 3D camera Kinect sensor, a UR10 industrial robot arm with a vacuum gripper, and different object types such as pulleys, disks, gears, and piston rods, is inspired by the NIST ARIAC competition. A first version of the Gilbreth application is implemented leveraging a number of Robot Operating System (ROS) and ROS-Industrial (ROS-I) packages. The Gazebo package is used to simulate the environment, and six external ROS nodes have been implemented to execute the required functions. Experimental measurements of CPU usage and processing times of the ROS nodes are discussed. In particular, the object recognition ROS package requires the highest processing times and offers an opportunity for designing an iterative method with the aim to fasten completion time. Its processing time is found to be on par with the time required by the robot arm to execute its movement between four poses: pick approach, pick, pick retreat and place.

PEMANFAATAN MIDDLEWARE ROBOT OPERATING SYSTEM (ROS) DALAM MENJAWAB TANTANGAN REVOLUSI INDUSTRI 4.0

The industrial revolution 4.0 is the development of industrial based on the internet, control, robotics, and networking. This study describes the usage of a Robot Operating System (ROS) middleware to answer the challenges of the industrial revolution 4.0 for control the industrial electronic devices and household electronic equipment using Raspberry Pi. ROS has nodes, topics and messages that can be used to manage the Raspberry Pi GPIO pins to be active high (1) or active low (0). The result of this study is the system be able to control the on and off electronic devices through the GPIO pins of Raspberry Pi and relay module based on message commands from the ROS node. The electronic devices had controlled in this study are a fan, light, air conditioner, and room heater that have 110/220 AC voltage.

Web-Based Robot Control Interface

A web-based robot control system interface is designed. This interface can be used by users to control the motion of target robot, observe 3D model, and monitor the real-time value of the robot joints through PC or mobile device. The advantage of this system lies in its versatility and portability, allowing users to open the interface to control target robot in any place. This system mainly uses robot operating system (ROS), Html 5, C++, JavaScript and PHP technology. JavaScript library provided by ROS authority is used to build the front-end interface. PHP is used to create a user registration login system. Ros3djs is used to realize the establishment of dynamic model of robot simulation. The C++ library provided by ROS is used to synchronize the communication between the ROS node and the robot. Finally, the human-computer interaction system of the 16-DOF robotic hand is successfully implemented. According to the results, the system has good interactivity, versatility and portability.

Pound: A multi-master ROS node for reducing delay and jitter in wireless multi-robot networks

The Robot Operating System (ROS) is a popular and widely used software framework for building robotics systems. With the growth of its popularity, it has started to be used in multi-robot systems as well. However, the TCP connections that the platform relies on for connecting the so-called ROS nodes presents several issues regarding limited-bandwidth, delays, and jitter, when used in wireless multi-hop networks. In this paper, we present a thorough analysis of the problem and propose a new ROS node called Pound to improve the wireless communication performance by reducing delay and jitter in data exchanges, especially in multi-hop networks. Pound allows the use of multiple ROS masters (roscores), features data compression, and importantly, introduces a priority scheme that allows favoring more important flows over less important ones. We compare Pound to the state-of-the-art solutions through extensive experiments and show that it performs equally well, or better in all the test cases, including a control-over-network example.

Field Navigation Using Fuzzy Elevation Maps Built with Local 3D Laser Scans

The paper describes the case study of the mobile robot Andabata navigating on natural terrain at low speeds with fuzzy elevation maps (FEMs). To this end, leveled three-dimensional (3D) point clouds of the surroundings are obtained by synchronizing ranges obtained from a 360 ∘ field of view 3D laser scanner with odometric and inertial measurements of the vehicle. Then, filtered point clouds are employed to produce FEMs and their corresponding fuzzy reliability masks (FRMs). Finally, each local FEM and its FRM are processed to choose the best motion direction to reach distant goal points through traversable areas. All these tasks have been implemented using ROS (Robot Operating System) nodes distributed among the cores of the onboard processor. Experimental results of Andabata during non-stop navigation on an urban park are presented.