{'fraction_non_alphanumeric': 0.024844720496894408, 'fraction_numerical': 0.0038819875776397515, 'mean_word_length': 4.832579185520362, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A low-cost system for high-rate, high-accuracy temporal calibration for LIDARs and cameras

Deployment of camera and laser based motion estimation systems for controlling platforms operating at high speeds, such as cars or trains, is posing increasingly challenging precision requirements on the temporal calibration of these sensors. In this work, we demonstrate a simple, low-cost system for calibrating any combination of cameras and time of flight LIDARs with respect to the CPU clock (and therefore, also to each other). The newly proposed device is based on widely available off-the-shelf components, such as the Raspberry Pi 3, which is synchronized using the Precision Time Protocol (PTP) with respect to the CPU of the sensor carrying system. The obtained accuracy can be shown to be below 0.1 ms per measurement for LIDARs and below minimal exposure time per image for cameras. It outperforms state-of-the-art approaches also not relying on hardware synchronization by more than a factor of 10 in precision. Moreover, the entire process can be carried out at a high rate allowing the study of how offsets evolve over time. In our analysis, we demonstrate how each building block of the system contributes to this accuracy and validate the obtained results using real-world data.