Improving poor GPS area localization for intelligent vehicles

Dinh-Van Nguyen, F. Nashashibi, T. Dao, Eric Castelli
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引用次数: 17

Abstract

Precise positioning plays a key role in successful navigation of autonomous vehicles. A fusion architecture of Global Positioning System (GPS) and Laser-SLAM (Simultaneous Localization and Mapping) is widely adopted. While Laser-SLAM is known for its highly accurate localization, GPS is still required to overcome accumulated error and give SLAM a required reference coordinate. However, there are multiple cases where GPS signal quality is too low or not available such as in multi-story parking, tunnel or urban area due to multipath propagation issue etc. This paper proposes an alternative approach for these areas with WiFi Fingerprinting technique to replace GPS. Result obtained from WiFi Fingerprinting will then be fused with Laser-SLAM to maintain the general architecture, allow seamless adaptation of vehicle to the environment.
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改善智能汽车GPS定位能力差的区域
精确定位是自动驾驶汽车成功导航的关键。全球定位系统(GPS)和激光同步定位与制图(Laser-SLAM)的融合体系结构被广泛采用。虽然激光SLAM以其高精度定位而闻名,但GPS仍然需要克服累积误差并为SLAM提供所需的参考坐标。然而,在许多情况下,GPS信号质量过低或不可用,如多层停车场,隧道或城市地区,由于多径传播问题等。本文提出了一种利用WiFi指纹技术替代GPS的替代方法。然后将WiFi指纹识别获得的结果与Laser-SLAM融合,以保持总体架构,使车辆能够无缝适应环境。
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