A system disclosed herein applies a parameterized sensing and localization error model for use by connected devices to improve cooperative sensor fusion by estimating errors using key prediction factors (e.g., distance and velocity) at different tiers. The parameterized sensing and localization error model implements a local sensor fusion process for fusing measurements from sensors of a connected device and a global sensor fusion process for fusing measurements from many connected devices. The local sensor fusion process generates a covariance matrix that incorporates a measured distance and the global sensor fusion process generates a covariance matrix that incorporates a measured velocity combined with the local sensor fusion result. Results show an average improvement of 1.42× in RMSE vs. a typical fixed error model on a 1/10 scale test-bed.
SYSTEMS AND METHODS FOR COOPERATIVE SENSOR FUSION BY PARAMETERIZED COVARIANCE GENERATION IN CONNECTED AUTONOMOUS VEHICLES
2025-01-23
Patent
Electronic Resource
English
Nonlinear Trajectory Generation for Autonomous Vehicles via Parameterized Maneuver Classes
Online Contents | 2006
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