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Environmental perception: an application of multi-sensor data fusion to autonomous off-road navigation

机译:环境感知:多传感器数据融合在自主越野导航中的应用

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Environmental perception is one of the most difficult problems for off-road autonomous vehicles. Due to the variety and complexity of off-road environments, the information from any single sensor is not enough for safe and efficient vehicle navigation. Employing more sensors can greatly improve the vehicle's perceptive capability. This paper describes a multi-sensor data fusion system for off-road autonomous vehicles. The system acquires data from one camera, four laser range finders, one radar, and several ultrasonic sensors. A hierarchical structure is used to organize the sensors from feature level to high fusion level. Dempster-Shafer evidence theory is adopted to decide the classification of each grid in the fusion map. A weighted evidence combination rule is proposed and implemented to improve the decision results under high conflicting circumstance. The experimental results showed the validity of our method.
机译:环境感知是越野自动驾驶汽车最困难的问题之一。由于越野环境的多样性和复杂性,来自任何单个传感器的信息不足以实现安全,高效的车辆导航。使用更多的传感器可以大大提高车辆的感知能力。本文介绍了一种用于越野自动驾驶汽车的多传感器数据融合系统。该系统从一台摄像机,四个激光测距仪,一个雷达和几个超声传感器获取数据。分层结构用于组织从特征级别到高融合级别的传感器。采用Dempster-Shafer证据理论确定融合图中每个网格的分类。提出并实施了加权证据组合规则,以提高在高度冲突情况下的决策结果。实验结果证明了该方法的有效性。

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