Open-source Robot Operating System Research Articles

Research and Design of Intelligent Anti-epidemic Disinfection Robot Based on ROS

In the context of the global epidemic of COVID-19, in order to solve the problems of heavy disinfection and epidemic prevention tasks in densely populated indoor public places and a low degree of automation and intelligence, a smart anti-epidemic disinfection robot solution that integrates multiple disinfection methods is proposed. The solution is designed and developed based on the open-source robot operating system (ROS) with digital intelligent remote disinfection function, micron-level atomization disinfection function, and multi-angle ultraviolet light disinfection function, providing a full range of high-efficiency disinfection and disinfection for the air environment bacteria protection. It has the functions of autonomous positioning and navigation, intelligent path planning, and real-time perception of environmental parameters. It is also equipped with a remote monitoring platform to monitor the status of the disinfection robot itself and task execution in real time to ensure stable operation and to issue disinfection tasks at regular intervals or in certain areas. The practice has proved that this solution can effectively solve the problem of the high labor cost of manual disinfecting so that one person can quickly complete the whole-area disinfecting work, greatly improving work efficiency, and it has good application value and is worth promoting.

Survey Paper on Development of ROS for Fault Detection of Underwater Cables

An introduction to ROS, an open source robot operating system, is given in this paper. In terms of process management and scheduling, ROS is not an operating system. This study explains how Robotic Operating System (ROS) can be used to control items (such as vehicles) remotely and cautiously without human intervention at the location. Instead, it gives heterogeneous computing clusters a structured communication layer on top of the host operating system. This document gives a quick explanation of how ROS fits into the current robot software architecture and how we may utilize it for AUVs (Automated under water vehicle). One of the media that connects the entire world to the internet is optical cable, which is typically installed underground or under water. As a result, it is challenging to inspect them thoroughly because it costs more to do so. To address this issue, we are presenting a solution that involves developing a robotic operating system that would assist in checking the underwater/underground cables. To put this into practice, we have been utilizing VMWare Workstation to virtually install Ubuntu OS, where we will be installing ROS packages, with the ROS-Gazebo toolbox serving as one of the primary tools. We are testing the implemented software with the standard inputs. We are using light radiation as the primary factor to assess the condition of the optical cable.

Hand model with dependency constrained joints for applications in rehabilitation robotics

Aim: This work presents a method for developing a simplified but efficient model of the complex human hand kinematics with the aim of its implementation in rehabilitation robotics. Material and methods: The approach incorporates modularity by simplifying the available model comprising 24 degrees of freedom (DOFs) to 9 DOFs, with the introduction of additional joint coupling parameters specific to different grasp types. The effect of dependent joints to the ranges-of-motion (ROMs) of the model is investigated and compared to the anatomical one. The index, middle, ring and little finger solutions to forward and inverse kinematics problems are then acquired. The implementation of the model, based on the median male bones dimensions, is made available in the open-source Robot Operating System (ROS) framework. Results: By including additional four inclination angles per finger, the devised kinematic hand model encompasses also finger curvatures, resulting in significant positioning accuracy improvements compared to the conventional model. The used 3D spatial position improvement metrics are the mean absolute (MAE) and mean relative errors (MRE). The dependent joint position MAEs range from 0.22 to 0.34 cm, while MREs range from 2.8 and 3.5 %, whereas the highest absolute and relative errors during fingertip positioning can reach 0.5 cm and 10.5 %, respectively. Conclusion: The performed investigation allowed establishing that by modelling finger curvature and assuring the adaptability of the model to a variety of human hands and rehabilitation modalities through joint dependency, represents the best approach towards a relatively simple and applicable rehabilitation model with functional human-like hand movements.

On the Improvement of ROS-Based Control for Teleoperated Yaskawa Robots

This paper deals with Yaskawa robots controlling the Robot Operating System (ROS) for teleoperation tasks. The integration of an open-source ROS interface based on standard Motoman packages into control loop leads to large trajectory tracking errors and latency, which are unsuitable for robotic teleoperation. An improved version of the standard ROS-based control is proposed by adding a new velocity control mode into the standard Motoman ROS driver. These two approaches are compared in terms of response time and tracking delay. Investigations applied on the Yaskawa GP8 robot while using the proposed improved ROS-based control confirmed trajectory tracking and latency improvements, which can achieve 43% with respect to standard control.

Sensor-Guided Assembly of Segmented Structures with Industrial Robots

This paper presents a robotic assembly methodology for the manufacturing of large segmented composite structures. The approach addresses three key steps in the assembly process: panel localization and pick-up, panel transport, and panel placement. Multiple stationary and robot-mounted cameras provide information for localization and alignment. A robot wrist-mounted force/torque sensor enables gentle but secure panel pick-up and placement. Human-assisted path planning ensures reliable collision-free motion of the robot with a large load in a tight space. A finite state machine governs the process flow and user interface. It allows process interruption and return to the previous known state in case of error condition or when secondary operations are needed. For performance verification, a high resolution motion capture system provides the ground truth reference. An experimental testbed integrating an industrial robot, vision and force sensors, and representative laminated composite panels demonstrates the feasibility of the proposed assembly process. Experimental results show sub-millimeter placement accuracy with shorter cycle times, lower contact force, and reduced panel oscillation than manual operations. This work demonstrates the versatility of sensor guided robotic assembly operation in a complex end-to-end tasks using the open source Robot Operating System (ROS) software framework.

Ford Multi-AV Seasonal Dataset

This article presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles (AVs) at different days and times during 2017–2018. The vehicles traversed an average route of 66 km in Michigan that included a mix of driving scenarios such as the Detroit airport, freeways, city centers, university campus, and suburban neighborhoods. Each vehicle used in this data collection was a Ford Fusion outfitted with an Applanix POS-LV GNSS/INS system, four HDL-32E Velodyne 3D-lidar scanners, six Point Grey 1.3 MP cameras arranged on the rooftop for 360° coverage, and one Point Grey 5 MP camera mounted behind the windshield for the forward field of view. We present the seasonal variation in weather, lighting, construction, and traffic conditions experienced in dynamic urban environments. We also include data from multiple AVs that were driven in close proximity. This dataset can help design robust algorithms for AVs and multi-agent systems. Each log in the dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground-truth pose, and 3D maps. All data is available in rosbag format that can be visualized, modified, and applied using the open-source Robot Operating System (ROS). We also provide the output of reflectivity-based localization for bench-marking purposes. The dataset can be freely downloaded at avdata.ford.com.

Parameter Optimization Analysis of Gmapping Algorithm Based on Improved RBPF Particle Filter

Aiming at the problem of inaccurate mapping caused by the robot hardware configuration that cannot meet the needs when the Gmapping algorithm is used for indoor mapping, a method for optimizing algorithm parameters is proposed. First, the principle of the Gmapping algorithm based on improved Rao-Blackwellised particle filtering is analyzed. By using the open source robot operating system (ROS) to run the Gmapping algorithm on a mobile robot, an indoor map is constructed. Then, by configuring different parameters, the accuracy of map construction is optimized. The experimental results show that by optimizing the algorithm parameters in an indoor environment, the algorithm can better adapt to the hardware configuration and improve the quality of the map.

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.

Research on simultaneous localization and mapping of indoor mobile robot

Simultaneous localization and mapping (SLAM) is the key technology to fulfill mobile robot obstacle avoidance and autonomous navigation. As cameras such as binocular cameras or RGB-D cameras exist wide-angle limitations, the use of such sensors prone to map mismatches and localization errors. In order to solve the aforementioned problems, 2D laser radar and odometer are used as the core sensor to design an experimental system for indoor SLAM, which is configured on a mobile robot to examine the effect of indoor SLAM. Through the Rao-Blackwellized [1] particle filter algorithm, the data of laser radar and odometer are fused with real-time processing, which realizes the construction of map as well as localization and navigation of the mobile robot in the unknown environment. Experiments on simulation and physical verification were carried out with open source robot operating system (ROS). The simulation and experimental results confirm the feasibility and practicability of the platform.

Toward Socially Aware Robot Navigation in Dynamic and Crowded Environments: A Proactive Social Motion Model

Safe and social navigation is the key to deploying a mobile service robot in a human-centered environment. Widespread acceptability of mobile service robots in daily life is hindered by robot’s inability to navigate in crowded and dynamic human environments in a socially acceptable way that would guarantee human safety and comfort. In this paper, we propose an effective proactive social motion model (PSMM) that enables a mobile service robot to navigate safely and socially in crowded and dynamic environments. The proposed method considers not only human states (position, orientation, motion, field of view, and hand poses) relative to the robot but also social interactive information about human–object and human group interactions. This allows development of the PSMM that consists of elements of an extended social force model and a hybrid reciprocal velocity obstacle technique. The PSMM is then combined with a path planning technique to generate a motion planning system that drives a mobile robot in a socially acceptable manner and produces respectful and polite behaviors akin to human movements. Note to Practitioners —In this paper, we validated the effectiveness and feasibility of the proposed proactive social motion model (PSMM) through both simulation and real-world experiments under the newly proposed human comfortable safety indices. To do that, we first implemented the entire navigation system using the open-source robot operating system. We then installed it in a simulated robot model and conducted experiments in a simulated shopping mall-like environment to verify its effectiveness. We also installed the proposed algorithm on our mobile robot platform and conducted experiments in our office-like laboratory environment. Our results show that the developed socially aware navigation framework allows a mobile robot to navigate safely, socially, and proactively while guaranteeing human safety and comfort in crowded and dynamic environments. In this paper, we examined the proposed PSMM with a set of predefined parameters selected based on our empirical experiences about the robot mechanism and selected social environment. However, in fact a mobile robot might need to adapt to various contextual and cultural situations in different social environments. Thus, it should be equipped with an online adaptive interactive learning mechanism allowing the robot to learn to auto-adjust their parameters according to such embedded environments. Using machine learning techniques, e.g., inverse reinforcement learning [1] to optimize the parameter set for the PSMM could be a promising research direction to improve adaptability of mobile service robots in different social environments. In the future, we will evaluate the proposed framework based on a wider variety of scenarios, particularly those with different social interaction situations and dynamic environments. Furthermore, various kinds of social cues and signals introduced in [2] and [3] will be applied to extend the proposed framework in more complicated social situations and contexts. Last but not least, we will investigate different machine learning techniques and incorporate them in the PSMM in order to allow the robot to automatically adapt to diverse social environments.

ISocioBot: A Multimodal Interactive Social Robot

We present one way of constructing a social robot, such that it is able to interact with humans using multiple modalities. The robotic system is able to direct attention towards the dominant speaker using sound source localization and face detection, it is capable of identifying persons using face recognition and speaker identification and the system is able to communicate and engage in a dialog with humans by using speech recognition, speech synthesis and different facial expressions. The software is built upon the open-source robot operating system framework and our software is made publicly available. Furthermore, the electrical parts (sensors, laptop, base platform, etc.) are standard components, thus allowing for replicating the system. The design of the robot is unique and we justify why this design is suitable for our robot and the intended use. By making software, hardware and design accessible to everyone, we make research in social robotics available to a broader audience. To evaluate the properties and the appearance of the robot we invited users to interact with it in pairs (active interaction partner/observer) and collected their responses via an extended version of the Godspeed Questionnaire. Results suggest an overall positive impression of the robot and interaction experience, as well as significant differences in responses based on type of interaction and gender.

Feasible utilization of the inherent characteristics of holonomic mobile robots

This paper presents a computationally inexpensive generic method to utilize the maximum velocity and acceleration of an omnidirectional mobile robot. The proposed method is based on the inverse kinematic and inverse dynamic models by defining novel velocity and acceleration reserve multipliers respectively. The defined multipliers enable a computationally inexpensive solution and give representative index numbers, showing the amount of utilized resources during online computation. The model was applied to control a kiwi drive mobile robot and validated by experimental measurements. An open-source Robot Operating System (ROS) catkin C++ package was published to enable the feasible implementation of the results.

The design of an intelligent soccer-playing robot

Purpose – The purpose of this paper is to design intelligent robots operating in such dynamic environments like the RoboCup Middle-Size League (MSL). In the RoboCup MSL, two teams of five autonomous robots play on an 18- × 12-m field. Equipped with sensors and on-board computers, each robot should be able to perceive the environment, make decision and control itself to play the soccer game autonomously. Design/methodology/approach – This paper presents the design of our soccer robots, participating in RoboCup MSL. The mechanical platform, electrical architecture and software framework are discussed separately. The mechanical platform is designed modularly, so easy maintainability is achieved; the electronic architecture is built on industrial standards using PC-based control technique, which results in high robustness and reliability during the intensive and fierce MSL games; the software is developed upon the open-source Robot Operating System (ROS); thus, the advantages of ROS such as modularity, portability and expansibility are inherited. Findings – Based on this paper and the open-source hardware and software, the MSL robots can be re-developed easily to participate in the RoboCup MSL. The robots can also be used in other research and education fields, especially for multi-robot systems and distributed artificial intelligence. Furthermore, the main designing ideas proposed in the paper, i.e. using a modular mechanical structure, an industrial electronic system and ROS-based software, provide a common solution for designing general intelligent robots. Originality/value – The methodology of the intelligent robot design for highly competitive and dynamic RoboCup MSL environments is proposed.

Co-Pilot Agent for Vehicle/Driver Cooperative and Autonomous Driving

ETRI's project is aimed at the development of an automated vehicle that cooperates with a driver and interacts with other vehicles on the road while obeying traffic rules without collisions. This paper presents a core block within the system; the block is named Co-Pilot agent and consists of several main modules, such as road map generation, decision-making, and trajectory generation. The road map generation builds road map data to provide enhanced and detailed map data. The decision-making, designed to serve situation assessment and behavior planning, evaluates a collision risk of traffic situations and determines maneuvers to follow a global path as well as to avoid collisions. The trajectory generation generates a trajectory to achieve the given maneuver by the decision-making module. The system is implemented in an open-source robot operating system to provide a reusable, hardware-independent software platform; it is then tested on a closed road with other vehicles in several scenarios similar to real road environments to verify that it works properly for cooperative driving with a driver and automated driving.

RT-ROS: A real-time ROS architecture on multi-core processors

ROS, an open-source robot operating system, is widely used and rapidly developed in the robotics community. However, running on Linux, ROS does not provide real-time guarantees, while real-time tasks are required in many robot applications such as robot motion control. This paper for the first time presents a real-time ROS architecture called RT-RTOS on multi-core processors. RT-ROS provides an integrated real-time/non-real-time task execution environment so real-time and non-real-time ROS nodes can be separately run on a real-time OS and Linux, respectively, with different processor cores. In such a way, real-time tasks can be supported by real-time ROS nodes on a real-time OS, while non-real-time ROS nodes on Linux can provide other functions of ROS. Furthermore, high performance is achieved by executing real-time ROS nodes and non-real-time ROS nodes on different processor cores. We have implemented RT-ROS on a dual-core processor and conducted various experiments with real robot applications. The experimental results show that RT-ROS can effectively provide real-time support for the ROS platform with high performance by exploring the multi-core architecture.

Precisely Groovy [ROS Topics

You should be using the robot operating system (ROS) Groovy on Precise. Groovy Galapagos or "Groovy" for short, is the latest release of the open-source ROS (following the Box Turtle, C Turtle, Diamondback, Electric Emmys, and Fuerte releases) and will be the standard basis for robotic software for the foreseeable future. Precise is the current long-term supported version of Ubuntu Linux, which means that it will be stable and supported for the next couple of years. If you are an ROS user and have not yet made the leap to Groovy, now is a good time. If you are not an ROS user, getting started with ROS is easier than ever with Groovy (Figure 1).

Exponential Growth of ROS [ROS Topics

This paper discusses about open-source robot operating system (ROS). ROS has expanded to include dozens of robots and an exponentially growing amount of code. Robot operating system has served as one of the premier libraries for robotics code in the world. Software shared through ROS is available for anyone to use, edit, and update.