Environment perception is an important capability for fully autonomous operation of agricultural machinery. High-precision work requires perception systems that are able to locate objects with high and specified accuracy. In this paper, we present an object detection and tracking system in a global coordinate frame based on 2D LiDAR data and RTK-GNSS positioning. The LiDARs and the RTK-GNSS device are installed on a tractor that is moving while the data is recorded. The final mapping result is compared to an RTK-GNSS based ground truth measurement of the object positions. For a test setup with four objects on a clover field, the average object positioning accuracy of the LiDAR system was determined to be 0.135 m (CEP50) and the worst case accuracy was 0.178m (CEP50). The preliminary results from this study can be used as a basis for determining requirements for safety margins when using this system for autonomous driving.
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Environment perception is an important capability for fully autonomous operation of agricultural machinery. High-precision work requires perception systems that are able to locate objects with high and specified accuracy. In this paper, we present an object detection and tracking system in a global coordinate frame based on 2D LiDAR data and RTK-GNSS positioning. The LiDARs and the RTK-GNSS device are installed on a tractor that is moving while the data is recorded. The final mapping result is c...
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