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Hardware-triggered Time Synchronization of Roadside Multi-lidar, Multi-camera Measurement System for Accurate Data Alignment

arXiv 2607.15889 ↗First posted 17 Jul 2026cs.CVcited by 0

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Abstract (arXiv)

Accurate temporal alignment of heterogeneous sensors is necessary for reliable environment perception in roadside multi-lidar, multi-camera systems, particularly in dense urban traffic. For this purpose, an open-source, simple, modular, and configurable hardware-triggered time-synchronization circuit is presented in this work to perform temporal alignment or accurate time synchronization between a lidar and multiple cameras. In the designed circuit, a lidar synchronization pulse is used as a reference input, and independently programmable, time-delayed trigger pulses are generated for each camera, allowing flexible adaptation to varying sensor setups and mounting geometries. A series of experiments is conducted on a roadside-mounted perception system comprised of lidar and three cameras, in which the trigger delay is systematically varied, and its impact on spatial-temporal alignment is evaluated. For different classes of road users, the overlap between lidar point cloud measurements and camera measurements is quantified to identify delay configurations that maximize cross-sensor consistency. The proposed circuit is shown to achieve robust and repeatable synchronization while remaining straightforward to deploy, reconfigure, and extend due to its simple and open-source design. Following validation on a three-camera roadside system, the circuit is extended to a vehicle platform with seven cameras and a lidar, providing a low-cost, extensible solution for multi-sensor synchronization across infrastructure and vehicle setups. All hardware circuit design files and source codes are available at https://github.com/shiva-THI/hardware-trigger-time-sync-lidar-cameras.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 2 of its 35 references that are in the map. First posted on arXiv 17 Jul 2026.

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References · 2

  1. 2017Mask R-CNNcited by 7,266
  2. 2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 191

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