The ever increasing need for precise location estimation in robotics is challenging a significant amount of research. Hence, new applications such as wireless localization based aerial robot control or high precision personal safety tracking are developed. However, most of the current developments and research solely focus on the accuracy of the required localization systems. Multi-user scalability, energy efficiency and real-time capabilities are often neglected. This work aims to overcome the technology barrier by providing scalable, high accuracy, real-time localization through energy-efficient, scheduled time-difference of arrival channel access. We could show that simultaneous processing and provisioning of more than a thousand localization results per second with high reliability is possible using the proposed approach. To enable wide-spread adoption, we provide an open source implementation of our system for the robot operating system (ROS). Furthermore, we provide open source access to the raw data created during our evaluation.
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ATLAS FaST: Fast and Simple Scheduled TDOA for Reliable Ultra-Wideband Localization
Semantic Scholar · Engineering · 2019
Abstract
The ever increasing need for precise location estimation in robotics is challenging a significant amount of research. Hence, new applications such as wireless localization based aerial robot control or high precision personal safety tracking are developed. However, most of the current developments and research solely focus on the accuracy of the required localization systems. Multi-user scalability, energy efficiency and real-time capabilities are often neglected. This work aims to overcome the technology barrier by providing scalable, high accuracy, real-time localization through energy-efficient, scheduled time-difference of arrival channel access. We could show that simultaneous processing and provisioning of more than a thousand localization results per second with high reliability is possible using the proposed approach. To enable wide-spread adoption, we provide an open source implementation of our system for the robot operating system (ROS). Furthermore, we provide open source access to the raw data created during our evaluation.