X Ru, N Gu, H Shang, H Zhang - Micromachines, 2022 - mdpi.com
A review of various calibration techniques of MEMS inertial sensors is presented in this paper. MEMS inertial sensors are subject to various sources of error, so it is essential to …
Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving …
Event-based cameras are a new passive sensing modality with a number of benefits over traditional cameras, including extremely low latency, asynchronous data acquisition, high …
Here we propose a real-time method for low-drift odometry and mapping using range measurements from a 3D laser scanner moving in 6-DOF. The problem is hard because the …
Place recognition in 3D data is a challenging task that has been commonly approached by adapting image-based solutions. Methods based on local features suffer from ambiguity and …
In order to increase accuracy and robustness in state estimation for robotics, a growing number of applications rely on data from multiple complementary sensors. For the best …
J Rehder, J Nikolic, T Schneider… - … on Robotics and …, 2016 - ieeexplore.ieee.org
An increasing number of robotic systems feature multiple inertial measurement units (IMUs). Due to competing objectives-either desired vicinity to the center of gravity when used in …
J Zhang, S Singh - Journal of field robotics, 2018 - Wiley Online Library
We present a data processing pipeline to online estimate ego‐motion and build a map of the traversed environment, leveraging data from a 3D laser scanner, a camera, and an inertial …
D Droeschel, S Behnke - 2018 IEEE International Conference …, 2018 - ieeexplore.ieee.org
Modern 3D laser-range scanners have a high data rate, making online simultaneous localization and mapping (SLAM) computationally challenging. Recursive state estimation …