2006 IEEE Intelligent Vehicles Symposium
DOI: 10.1109/ivs.2006.1689664
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A Multi-Sensor Acquisition Architecture and Real-Time Reference for Sensor and Fusion Methods Benchmarking

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Cited by 14 publications
(9 citation statements)
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“…Timing aspects are crucial in a multiple‐sensor scenario, since each datum needs to be correctly synchronized to the other. Using a software‐based application for time‐stamping external information induces a temporal imprecision, which can be due to the offset of the PC clock with respect to a reference time and to the drift of the internal clock (frequency error) . Spatial consistency is also required when dealing with different sensors information; spatial transformations between reference systems are obtained with calibration procedures .…”
Section: Introductionmentioning
confidence: 99%
“…Timing aspects are crucial in a multiple‐sensor scenario, since each datum needs to be correctly synchronized to the other. Using a software‐based application for time‐stamping external information induces a temporal imprecision, which can be due to the offset of the PC clock with respect to a reference time and to the drift of the internal clock (frequency error) . Spatial consistency is also required when dealing with different sensors information; spatial transformations between reference systems are obtained with calibration procedures .…”
Section: Introductionmentioning
confidence: 99%
“…[1]). In [2] a special parallel hardware device is used to timestamp sensor data with GPS accuracy. But as mentioned earlier, this approach cannot be applied to all sensors.…”
Section: Introductionmentioning
confidence: 99%
“…In [5] a method including UTC timestamps is proposed, but still only the arrival time at an acquisition system is used. In [6] a parallel hardware device is used to timestamp the measurements directly with GPS accuracy, but this method cannot be applied to all sensors. In [7] a method to filter the timestamps and minimize the sensor latencies is proposed.…”
Section: Introductionmentioning
confidence: 99%