Radio-to-Pose Information for Gauge-Drift Correction in Cooperative Localization
Radio-to-Pose Information for Gauge-Drift Correction in Cooperative Localization
This research introduces Radio-to-Pose Information (RPI), an interface that converts radio power residuals into Gaussian information matrices to correct gauge drift in cooperative localization.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- Environment
- SimulationOpen source S4
Reported numbers
trajectories
1,000
Trajectory count
View original evidence
oses and minimize uncertainty. We characterize the shared motions detectable from the map and observed links. For an uncertain shared map, RPI keeps correlations across robots and time and reproduces joint Gaussian pose estimates and covariances. Across $1000$ simulated Gaussian trials, RPI matches the results of joint estimation. Across 32 paired trials with a registered map, RPI reduces common-position RMSE from $0
Open source S4robots
32
Reported trials
View original evidence
oses and minimize uncertainty. We characterize the shared motions detectable from the map and observed links. For an uncertain shared map, RPI keeps correlations across robots and time and reproduces joint Gaussian pose estimates and covariances. Across $1000$ simulated Gaussian trials, RPI matches the results of joint estimation. Across 32 paired trials with a registered map, RPI reduces common-position RMSE from $0
Open source S4arena_dimension
50
View original evidence
.542$m to $0.140$m in a $50\times50$m arena compared with a baseline that uses radio only to weight relative measurements.
Open source S5
- paper: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
oses and minimize uncertainty. We characterize the shared motions detectable from the map and observed links. For an uncertain shared map, RPI keeps correlations across robots and time and reproduces joint Gaussian pose estimates and covariances. Across $1000$ simulated Gaussian trials, RPI matches the results of joint estimation. Across 32 paired trials with a registered map, RPI reduces common-position RMSE from $0
Open source S4
.542$m to $0.140$m in a $50\times50$m arena compared with a baseline that uses radio only to weight relative measurements.
Open source S5
Radio-to-Pose Information for Gauge-Drift Correction in Cooperative Localization
Open source S1
arXiv:2611.08361v1 Announce Type: new Abstract: Cooperative localization uses odometry and inter-robot measurements to estimate the motion of a robot team. These measurements describe only relative geometry, but the team's estimated position and orientation can drift together over time, i.e., gauge drift. In this work, we study correction of this gauge drift using a radio attenuation map registered in the same world
Open source S2
Source：arXiv Robotics — research abstracts · arxiv.org