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• W2899013282 abstract "Vehicle side slip angle is at the basis of many vehicle dynamics control systems. Many methods are available to estimate side-slip angle using on board sensors (usually accelerometers and gyros). The technical advances pertaining autonomous vehicles made an additional kind of sensor available: cameras. This study develops a mixed kinematic vision-based side slip angle estimation. The proposed algorithm merges the information of a commercial grade inertial measurement system, wheel encoders and information from a camera. The camera measurement are integrated in a Kalman filter observer. The paper implements and tests the approach on an instrumented RC scale vehicle, comparing the proposed approach against a kinematic based estimation. Experimental results show a decrease of a factor between 2 and 10 (depending on the type of maneuver) of the estimation mean squared error." @default.
• W2899013282 created "2018-11-09" @default.
• W2899013282 creator A5001651354 @default.
• W2899013282 creator A5042254814 @default.
• W2899013282 date "2018-08-01" @default.
• W2899013282 modified "2023-09-25" @default.
• W2899013282 title "Mixed Kinematics and Camera Based Vehicle Dynamic Sideslip Estimation for an RC Scaled Model" @default.
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• W2899013282 doi "https://doi.org/10.1109/ccta.2018.8511487" @default.
• W2899013282 hasPublicationYear "2018" @default.
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