Title
A Bio-Inspired Multi-Sensor System for Robust Orientation and Position Estimation
Abstract
The nature animals have evolved highly efficient and robust organs that support their complex daily navigation tasks. To mimic animal's navigation capability, we present a novel bio-inspired navigation system that draws inspirations from nature animals in this paper. The system consists of a three-axis magnetometer, a monocular camera, a micro inertial measurement unit (MIMU) and a polarization camera. While dead reckoning, orientation, and landmark recognition are considered as three most important capability for various species, we also designed corresponding algorithms based on the bio-inspired sensing system to perform autonomous navigation. In detail, the dead reckoning component is accomplished by integrating the monocular camera and the MIMU into a visual inertial odometry (VIO) and the orientation capability is achieved by combining the absolute orientation from the magnetometer with the relative orientation from the VIO. A loop closure detection is then used as the landmark recognition component to reduce the navigation drifts. All the three components are fused with a graph optimization method to generate the robust navigation result. To valid the proposed navigation sensing system and the algorithms, we have conducted series of experiments on ground and aerial unmanned vehicles, and have added orientation noise to testify the accuracy and robustness of the system.
Year
DOI
Venue
2021
10.1109/IROS51168.2021.9635932
2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
DocType
ISSN
Citations 
Conference
2153-0858
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Jia Xie100.34
Xiaofeng He2266.87
Jun Mao3112.56
Lilian Zhang4164.20
Guoliang Han501.69
Wenzhou Zhou600.34
Xiaoping Hu740859.63