Abstract: In autonomous robot systems, accurate object recognition and estimation are crucial for ensuring reliable performance, and sensor fusion techniques that combine complementary sensors have ...

ROS 2 (Humble) 向けのセンサフュージョンパッケージです． 1次元の温度センサ融合から始まり，任意次元のシステムや任意のセンサ数に拡張可能な，汎用N次元カルマンフィルタノードを提供します． ...

According to Dave Lee (@heydave7), Rivian's recent Autonomy and AI Day presentation highlighted the company's commitment to integrating both radar and LiDAR sensors for autonomous vehicle development, ...

I live in New Jersey, one of the states that mandates inspection for all vehicles newer than 1995. My daily driver, a Jeep Cherokee, happens to be a 1996 model year with an OBD-II sensor, meaning I ...

End-to-end (E2E) autonomous driving aims to simplify the traditional modular pipeline by directly mapping multi-sensor inputs to driving actions through deep learning, enabling joint optimization and ...

Abstract: In this paper, sensor fusion with feedback is investigated for robust target tracking in unmanned ground vehicles subject to missing measurements. Missing measurements are inevitable in ...

We may receive a commission on purchases made from links. Modern cars are designed to be more efficient and eco-friendly than ever. Automakers build vehicles with a wealth of advanced features to not ...

Sensor fusion is becoming increasingly popular and more complex in automotive designs, integrating multiple types of sensors into a single chip or package and intelligently routing data to wherever it ...

The mathematics that enable sensor fusion include probabilistic modeling and statistical estimation using Bayesian inference and techniques like particle filters, Kalman filters, and α-β-γ filters, ...

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