528 research outputs found
Accurate position tracking with a single UWB anchor
Accurate localization and tracking are a fundamental requirement for robotic
applications. Localization systems like GPS, optical tracking, simultaneous
localization and mapping (SLAM) are used for daily life activities, research,
and commercial applications. Ultra-wideband (UWB) technology provides another
venue to accurately locate devices both indoors and outdoors. In this paper, we
study a localization solution with a single UWB anchor, instead of the
traditional multi-anchor setup. Besides the challenge of a single UWB ranging
source, the only other sensor we require is a low-cost 9 DoF inertial
measurement unit (IMU). Under such a configuration, we propose continuous
monitoring of UWB range changes to estimate the robot speed when moving on a
line. Combining speed estimation with orientation estimation from the IMU
sensor, the system becomes temporally observable. We use an Extended Kalman
Filter (EKF) to estimate the pose of a robot. With our solution, we can
effectively correct the accumulated error and maintain accurate tracking of a
moving robot.Comment: Accepted by ICRA202
Cooperative Relative Positioning of Mobile Users by Fusing IMU Inertial and UWB Ranging Information
Relative positioning between multiple mobile users is essential for many
applications, such as search and rescue in disaster areas or human social
interaction. Inertial-measurement unit (IMU) is promising to determine the
change of position over short periods of time, but it is very sensitive to
error accumulation over long term run. By equipping the mobile users with
ranging unit, e.g. ultra-wideband (UWB), it is possible to achieve accurate
relative positioning by trilateration-based approaches. As compared to vision
or laser-based sensors, the UWB does not need to be with in line-of-sight and
provides accurate distance estimation. However, UWB does not provide any
bearing information and the communication range is limited, thus UWB alone
cannot determine the user location without any ambiguity. In this paper, we
propose an approach to combine IMU inertial and UWB ranging measurement for
relative positioning between multiple mobile users without the knowledge of the
infrastructure. We incorporate the UWB and the IMU measurement into a
probabilistic-based framework, which allows to cooperatively position a group
of mobile users and recover from positioning failures. We have conducted
extensive experiments to demonstrate the benefits of incorporating IMU inertial
and UWB ranging measurements.Comment: accepted by ICRA 201
Graph Optimization Approach to Range-based Localization
In this paper, we propose a general graph optimization based framework for
localization, which can accommodate different types of measurements with
varying measurement time intervals. Special emphasis will be on range-based
localization. Range and trajectory smoothness constraints are constructed in a
position graph, then the robot trajectory over a sliding window is estimated by
a graph based optimization algorithm. Moreover, convergence analysis of the
algorithm is provided, and the effects of the number of iterations and window
size in the optimization on the localization accuracy are analyzed. Extensive
experiments on quadcopter under a variety of scenarios verify the effectiveness
of the proposed algorithm and demonstrate a much higher localization accuracy
than the existing range-based localization methods, especially in the altitude
direction
UWB-based system for UAV Localization in GNSS-Denied Environments: Characterization and Dataset
Small unmanned aerial vehicles (UAV) have penetrated multiple domains over
the past years. In GNSS-denied or indoor environments, aerial robots require a
robust and stable localization system, often with external feedback, in order
to fly safely. Motion capture systems are typically utilized indoors when
accurate localization is needed. However, these systems are expensive and most
require a fixed setup. Recently, visual-inertial odometry and similar methods
have advanced to a point where autonomous UAVs can rely on them for
localization. The main limitation in this case comes from the environment, as
well as in long-term autonomy due to accumulating error if loop closure cannot
be performed efficiently. For instance, the impact of low visibility due to
dust or smoke in post-disaster scenarios might render the odometry methods
inapplicable. In this paper, we study and characterize an ultra-wideband (UWB)
system for navigation and localization of aerial robots indoors based on
Decawave's DWM1001 UWB node. The system is portable, inexpensive and can be
battery powered in its totality. We show the viability of this system for
autonomous flight of UAVs, and provide open-source methods and data that enable
its widespread application even with movable anchor systems. We characterize
the accuracy based on the position of the UAV with respect to the anchors, its
altitude and speed, and the distribution of the anchors in space. Finally, we
analyze the accuracy of the self-calibration of the anchors' positions.Comment: Accepted to the 2020 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2020
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