ROS (Robot Operating System) packages have become increasingly popular as a type of software artifact that can be effectively reused in robotic software development. Indeed, finding suitable ROS packages that closely match the software's functional requirements from the vast number of available packages is a nontrivial task using current search methods. The traditional search methods for ROS packages often involve inputting keywords related to robotic tasks into general-purpose search engines or code hosting platforms to obtain approximate results of all potentially suitable ROS packages. However, the accuracy of these search methods remains relatively low because the task-related keywords may not precisely match the functionalities offered by the ROS packages. To improve the search accuracy of ROS packages, this paper presents a novel semantic-based search approach that relies on the semantic-level ROS Package Knowledge Graph (RPKG) to automatically retrieve the most suitable ROS packages. Firstly, to construct the RPKG, we employ multi-dimensional feature extraction techniques to extract semantic concepts from the dataset of ROS package text descriptions. The semantic features extracted from this process result in a substantial number of entities and relationships. Subsequently, we create a robot domain-specific small corpus and further fine-tune a pre-trained language model, BERT-ROS, to generate embeddings that effectively represent the semantics of the extracted features. These embeddings play a crucial role in facilitating semantic-level understanding and comparisons during the ROS package search process within the RPKG. Secondly, we introduce a novel semantic matching-based search algorithm that incorporates the weighted similarities of multiple features from user search queries, which searches out more accurate ROS packages than the traditional keyword search method.

In nuclear isotope and chemistry laboratories, hot cells and gloveboxes provide scientists with a controlled and safe environment to perform experiments. Working on experiments in these isolated containment cells requires scientists to be physically present. For hot cell work today, scientists manipulate equipment and radioactive material inside through a bilateral mechanical control mechanism. Motions produced outside the cell with the master control levers are mechanically transferred to the internal grippers inside the shielded containment cell. There is a growing need to have the capability to conduct experiments within these cells remotely. A simple method to enable remote manipulations within hot cell and glovebox cells is to mount two robotic arms inside a box to mimic the motions of human hands. An AR application was built in this work to allow a user wearing a Microsoft HoloLens 2 headset to teleoperate dual arm manipulators by grasping robotic end-effector digital replicas in AR from a remote location. In addition to the real-time replica of the physical robotic arms in AR, the application enables users to view a live video stream attached to the robotic arms and parse a 3D point cloud of 3D objects in their remote AR environment for better situational awareness. This work also provides users with virtual fixture to assist in manipulation and other teleoperation tasks.

With the increasing complexity of robot systems, it is necessary to simulate them before deployment. To do this, a model of the robot's kinematics or dynamics is required. One of the most commonly used formats for modeling robots is the Unified Robot Description Format (URDF). The goal of this article is to understand how URDF is currently used, what challenges people face when working with it, and how the community sees the future of URDF. The outcome can potentially be used to guide future research. This article presents the results from a survey based on 510 anonymous responses from robotic developers of different backgrounds and levels of experience. We find that 96.8% of the participants have simulated robots before, and of them 95.5% had used URDF. We identify a number of challenges and limitations that complicate the use of URDF, such as the inability to model parallel linkages and closed-chain systems, no real standard, lack of documentation, and a limited number of dynamic parameters to model the robot. Future perspectives for URDF are also determined, where 53.5% believe URDF will be more commonly used in the future, 12.2% believe other standards or tools will make URDF obsolete, and 34.4% are not sure what the future of URDF will be. Most participants agree that there is a need for better tooling to ensure URDF's future use.

The off-the-shelf drones are simple to operate and easy to maintain aerial systems. However, due to proprietary flight software, these drones usually do not provide any open-source interface which can enable them for autonomous flight in research or teaching. This work introduces a package for ROS1 and ROS2 for straightforward interfacing with off-the-shelf drones from the Parrot ANAFI family. The developed ROS package is hardware agnostic, allowing connecting seamlessly to all four supported drone models. This framework can connect with the same ease to a single drone or a team of drones from the same ground station. The developed package was intensively tested at the limits of the drones' capabilities and thoughtfully documented to facilitate its use by other research groups worldwide.

The recent adoption of the Robot Operating System (ROS) as a software standard in robotics has contributed to novel solutions for several problems on the area. One such problem is known as Simultaneous Localization and Mapping (SLAM) with autonomous navigation, for which a number of algorithms from different classes are available as ROS packages ready to be used on any compatible robot. Many anticipated applications of autonomous mobile robots require for them to navigate in diverse complex environments without support from exterior infrastructures. To perform this on-board navigation, the robot must make use of the available sensor technologies and fuse the most reliable data respective to the present environment in an adaptive manner and optimize the algorithm parameters prior to the actual implementation to reduce the workaround time. This paper will review recent efforts to develop onboard navigation systems which can seamlessly transition between outdoor and indoor environments and different terrains seamlessly using Gazebo simulator with ROS integration. The methodologies surveyed include SLAM, Odometry and Localisation. An overview of the state-of-the-art is provided with a focus on approaches which are adaptive to dynamic sensor uncertainty, dynamic objects and dynamic scenes. The experiences reported on this work should provide insight for roboticists seeking an Autonomous SLAM solution for indoor applications.

This paper demonstrates the integration model-based design approaches or vehicle control, with validation in a freely available open-source simulator. Continued interest in autonomous vehicles and their deployment is driven by the potential benefits of their use. However, it can be challenging to transition new theoretical approaches into unknown simulation environments. Thus, it is critical for experts from other fields, whose insights may be necessary to continue to advance autonomy, to be able to create control applications with the potential to transition to practice. In this article, we will explain how to use the CAT Vehicle simulator and ROS packages to create and test vehicle controllers. The methodology of developing the control system in this article takes the approach of model-based design using Simulink, and the ROS Toolbox, followed by code generation to create a standalone C++ ROS node. Such ROS nodes can be integrated through roslaunch in the CAT Vehicle ROS package.

March 22nd, 2012 is the day it all began. That's the day we officially incorporated the Open Source Robotics Foundation, the origin of what we now call Open Robotics. The prospect of starting a company is both scary and exciting; but starting an open-source company in a niche as specialized as robotics, now that is terrifying and exhilarating, if not a little unorthodox. All we had was a dream, some open-source code, and some very smart friends, a whole lot of them. We also had the wind at our backs.

Message passing interface: This is the core feature of ROS, and it enables interprocess communication. Using this message-passing capability, the ROS program can communicate with its linked systems and exchange data. We will learn more technical terms concerning the exchange of data between ROS programs/nodes in the coming sections and chapters. Hardware abstraction: ROS has a degree of abstraction that enables developers to create robot-agnostic applications. These kinds of application can be used with any robot; the developers need only worry about the underlying robot hardware.

This is a guest post by Open Source Robotics Foundation CEO Brian Gerkey. AI might be a hot topic but you'll still need to justify those projects. Eight years ago, Morgan Quigley, Eric Berger and Andrew Ng published a paper that was not about ROS. It was about STAIR, the STanford Artificial Intelligence Robot, which used a library called Switchyard to pass messages between software modules to perform complex manipulation tasks like stapler grasping. Switchyard was a purpose-built framework that was designed to be modular and robot-independent, and it was such a good idea that in 2009, "ROS: An Open-Source Robot Operating System" was presented at the IEEE International Conference on Robotics and Automation (ICRA) in Japan.

This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE. Eight years ago, Morgan Quigley, Eric Berger, and Andrew Ng published a paper that was not about ROS. It was about STAIR, the STanford Artificial Intelligence Robot, which used a library called Switchyard to pass messages between software modules to perform complex manipulation tasks like stapler grasping. Switchyard was a purpose-built framework that was designed to be modular and robot-independent, and it was such a good idea that in 2009, "ROS: An Open-Source Robot Operating System" was presented at the IEEE International Conference on Robotics and Automation (ICRA) in Japan.