7,952 research outputs found
It's the Human that Matters: Accurate User Orientation Estimation for Mobile Computing Applications
Ubiquity of Internet-connected and sensor-equipped portable devices sparked a
new set of mobile computing applications that leverage the proliferating
sensing capabilities of smart-phones. For many of these applications, accurate
estimation of the user heading, as compared to the phone heading, is of
paramount importance. This is of special importance for many crowd-sensing
applications, where the phone can be carried in arbitrary positions and
orientations relative to the user body. Current state-of-the-art focus mainly
on estimating the phone orientation, require the phone to be placed in a
particular position, require user intervention, and/or do not work accurately
indoors; which limits their ubiquitous usability in different applications. In
this paper we present Humaine, a novel system to reliably and accurately
estimate the user orientation relative to the Earth coordinate system.
Humaine requires no prior-configuration nor user intervention and works
accurately indoors and outdoors for arbitrary cell phone positions and
orientations relative to the user body. The system applies statistical analysis
techniques to the inertial sensors widely available on today's cell phones to
estimate both the phone and user orientation. Implementation of the system on
different Android devices with 170 experiments performed at different indoor
and outdoor testbeds shows that Humaine significantly outperforms the
state-of-the-art in diverse scenarios, achieving a median accuracy of
averaged over a wide variety of phone positions. This is
better than the-state-of-the-art. The accuracy is bounded by the error in the
inertial sensors readings and can be enhanced with more accurate sensors and
sensor fusion.Comment: Accepted for publication in the 11th International Conference on
Mobile and Ubiquitous Systems: Computing, Networking and Services
(Mobiquitous 2014
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
Tightly Coupled 3D Lidar Inertial Odometry and Mapping
Ego-motion estimation is a fundamental requirement for most mobile robotic
applications. By sensor fusion, we can compensate the deficiencies of
stand-alone sensors and provide more reliable estimations. We introduce a
tightly coupled lidar-IMU fusion method in this paper. By jointly minimizing
the cost derived from lidar and IMU measurements, the lidar-IMU odometry (LIO)
can perform well with acceptable drift after long-term experiment, even in
challenging cases where the lidar measurements can be degraded. Besides, to
obtain more reliable estimations of the lidar poses, a rotation-constrained
refinement algorithm (LIO-mapping) is proposed to further align the lidar poses
with the global map. The experiment results demonstrate that the proposed
method can estimate the poses of the sensor pair at the IMU update rate with
high precision, even under fast motion conditions or with insufficient
features.Comment: Accepted by ICRA 201
COMPARISON OF LOW COST PHOTOGRAMMETRIC SURVEY WITH TLS AND LEICA PEGASUS BACKPACK 3D MODELS
This paper considers Leica backpack and photogrammetric surveys of a mediaeval bastion in Padua, Italy. Furhtermore, terrestrial
laser scanning (TLS) survey is considered in order to provide a state of the art reconstruction of the bastion. Despite control points
are typically used to avoid deformations in photogrammetric surveys and ensure correct scaling of the reconstruction, in this paper
a different approach is considered: this work is part of a project aiming at the development of a system exploiting ultra-wide band
(UWB) devices to provide correct scaling of the reconstruction. In particular, low cost Pozyx UWB devices are used to estimate
camera positions during image acquisitions. Then, in order to obtain a metric reconstruction, scale factor in the photogrammetric
survey is estimated by comparing camera positions obtained from UWB measurements with those obtained from photogrammetric
reconstruction. Compared with the TLS survey, the considered photogrammetric model of the bastion results in a RMSE of 21.9cm, average error 13.4cm, and standard deviation 13.5cm. Excluding the final part of the bastion left wing, where the presence of several poles make reconstruction more difficult, (RMSE) fitting error is 17.3cm, average error 11.5cm, and standard deviation 9.5cm. Instead, comparison of Leica backpack and TLS surveys leads to an average error of 4.7cm and standard deviation 0.6cm (4.2 cm and 0.3 cm, respectively, by excluding the final part of the left wing)
- …