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Localization and mapping using only a rotating FMCW radar sensor.

Vivet D, Checchin P, Chapuis R - Sensors (Basel) (2013)

Bottom Line: These effects are, in the majority of studies, ignored or considered as noise and then corrected based on proprioceptive sensors or localization systems.Without the use of any proprioceptive sensor, these estimates are then used to build the trajectory of the vehicle and the radar map of outdoor environments.In this paper, radar-only localization and mapping results are presented for a ground vehicle moving at high speed.

View Article: PubMed Central - PubMed

Affiliation: Institut Pascal, Université Blaise Pascal, Clermont Université, Clermont-Ferrand, France. damien.vivet@univ-bpclermont.fr

ABSTRACT
Rotating radar sensors are perception systems rarely used in mobile robotics. This paper is concerned with the use of a mobile ground-based panoramic radar sensor which is able to deliver both distance and velocity of multiple targets in its surrounding. The consequence of using such a sensor in high speed robotics is the appearance of both geometric and Doppler velocity distortions in the collected data. These effects are, in the majority of studies, ignored or considered as noise and then corrected based on proprioceptive sensors or localization systems. Our purpose is to study and use data distortion and Doppler effect as sources of information in order to estimate the vehicle's displacement. The linear and angular velocities of the mobile robot are estimated by analyzing the distortion of the measurements provided by the panoramic Frequency Modulated Continuous Wave (FMCW) radar, called IMPALA. Without the use of any proprioceptive sensor, these estimates are then used to build the trajectory of the vehicle and the radar map of outdoor environments. In this paper, radar-only localization and mapping results are presented for a ground vehicle moving at high speed.

No MeSH data available.


Related in: MedlinePlus

Estimation of velocities. (a) and (b) represent the linear and angular velocity estimates respectively. Ground truth velocity is in red. The estimates given by the method are in blue.
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f18-sensors-13-04527: Estimation of velocities. (a) and (b) represent the linear and angular velocity estimates respectively. Ground truth velocity is in red. The estimates given by the method are in blue.

Mentions: Two other experiments were conducted on Auvergne Zenith car-park. The vehicle was driven over trajectories of 1.4-km and 1.5-km at a mean speed of 5 m/s in a static environment. The linear and angular velocity estimates are presented in Figures 17 and 18 respectively.


Localization and mapping using only a rotating FMCW radar sensor.

Vivet D, Checchin P, Chapuis R - Sensors (Basel) (2013)

Estimation of velocities. (a) and (b) represent the linear and angular velocity estimates respectively. Ground truth velocity is in red. The estimates given by the method are in blue.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3673098&req=5

f18-sensors-13-04527: Estimation of velocities. (a) and (b) represent the linear and angular velocity estimates respectively. Ground truth velocity is in red. The estimates given by the method are in blue.
Mentions: Two other experiments were conducted on Auvergne Zenith car-park. The vehicle was driven over trajectories of 1.4-km and 1.5-km at a mean speed of 5 m/s in a static environment. The linear and angular velocity estimates are presented in Figures 17 and 18 respectively.

Bottom Line: These effects are, in the majority of studies, ignored or considered as noise and then corrected based on proprioceptive sensors or localization systems.Without the use of any proprioceptive sensor, these estimates are then used to build the trajectory of the vehicle and the radar map of outdoor environments.In this paper, radar-only localization and mapping results are presented for a ground vehicle moving at high speed.

View Article: PubMed Central - PubMed

Affiliation: Institut Pascal, Université Blaise Pascal, Clermont Université, Clermont-Ferrand, France. damien.vivet@univ-bpclermont.fr

ABSTRACT
Rotating radar sensors are perception systems rarely used in mobile robotics. This paper is concerned with the use of a mobile ground-based panoramic radar sensor which is able to deliver both distance and velocity of multiple targets in its surrounding. The consequence of using such a sensor in high speed robotics is the appearance of both geometric and Doppler velocity distortions in the collected data. These effects are, in the majority of studies, ignored or considered as noise and then corrected based on proprioceptive sensors or localization systems. Our purpose is to study and use data distortion and Doppler effect as sources of information in order to estimate the vehicle's displacement. The linear and angular velocities of the mobile robot are estimated by analyzing the distortion of the measurements provided by the panoramic Frequency Modulated Continuous Wave (FMCW) radar, called IMPALA. Without the use of any proprioceptive sensor, these estimates are then used to build the trajectory of the vehicle and the radar map of outdoor environments. In this paper, radar-only localization and mapping results are presented for a ground vehicle moving at high speed.

No MeSH data available.


Related in: MedlinePlus