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Automotive and robotic applications demand three-dimensional (3D) imaging systems, that are reliable, small and lowcost. A promising technology to satisfy these demands are LiDAR-systems based on the direct time-of-flight principle. To greatly reduce the costs and footprint of current LiDAR-systems new compelling concepts are emerging. These concepts mainly differ in the used illumination techniques of the field-of-view (FOV). Micro-electro-mechanical systems (MEMS)- scanners are replacing the bulkier and more expensive polygon mirrors, which were earlier used to deflect the laser beam and partially illuminate the FOV. In contrast to this approach the full illumination of the FOV with a single widened laser beam is used by the concept known as flash-illumination. The range performance of the direct time-of-flight principle is directly proportional to the emitted laser pulse power and is either limited by detector noise or background radiation. High-power near-infrared laser diodes are announced, which offer higher pulse peak power and shorter laser pulses. The high energy density of these laser sources can, however, be hazardous to the human eye. Therefore, the energy density of the laser pulse must be limited and classified according to the IEC 60825-1:2014. While this is particularly easy for Flash LiDAR-systems, a two-dimensional consideration is necessary to determine the accessible emission limits (AEL) for MEMS-based LiDARsystems, which takes the time dependent scanning-motion of the mirror into account. This work presents a framework to describe and calculate the differences between the calculations of the AEL for Flash- and MEMS-based LiDAR-systems. To achieve this the framework incorporates the calculation of the two-dimensional pulse distribution based on the time dependent behaviour of the MEMS-scanner for the most commonly used one- and two-dimensional scanning-patterns. To further estimate and compare the performance of the LiDAR-systems this work describes an automotive and robotic application use case scenario, which are used to compare the performance for various performance metrices.
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