Year-end Sale % OFF 
Abstract
The global navigation satellite system (GNSS) constitutes an effective and affordable solution to the outdoor positioning problem. When combined with precise positioning techniques, such as the real time kinematic (RTK), centimeter-level positioning accuracy becomes a reality. Such performance is suitable for a whole new range of demanding applications, including high-accuracy field robotics operations. The RTKRCV, part of the RTKLIB package, is one of the most popular open-source solutions for real-time GNSS precise positioning. Yet the lack of integration with the robot operating system (ROS), constitutes a limitation on its adoption by the robotics community. This article addresses this limitation, reporting a new implementation which brings the RTKRCV capabilities into ROS. New features, including ROS publishing and control over a ROS service, were introduced seamlessly, to ensure full compatibility with all original options. Additionally, a new observation synchronization scheme improves solution consistency, particularly relevant for the moving-baseline positioning mode. Real application examples are presented to demonstrate the advantages of our rtkrcv_ros package. For community benefit, the software was released as an open-source package.
Highlights
For a mobile robot to be effective, accurate knowledge about its localization is mandatory
Outdoor solutions benefit from an important resource, denied to indoor applications, which is the global navigation satellite system (GNSS)
The original RTKRCV compensates for the base station delay, computing a correction to the base station position, by integrating the measured base velocity over the delay interval. This operation does not guarantee a consistent solution, especially for long observation delays and platforms subjected to fast varying dynamics. We address this issue by implementing two routines, associated with previously existing options in the configuration file, namely the pos2-maxage and pos2-syncsol options
Summary
For a mobile robot to be effective, accurate knowledge about its localization is mandatory. Autonomous localization is a perception-driven process, usually addressed through probabilistic data fusion techniques, which combine information from several sensors, to derive an updated estimate of the robot’s position and orientation. In this context, outdoor solutions benefit from an important resource, denied to indoor applications, which is the global navigation satellite system (GNSS). GNSS is a ubiquitous resource, enabling any platform, equipped with a receiver, and under clear sky view, to access periodic global position references This information is crucial to the localization process, as global updates are essential to bound estimation errors associated with dead reckoning strategies.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
