LiDAR technology plays a vital role in various applications, including autonomous driving, environmental monitoring, and robotics. Accurate target detection is a crucial task in LiDAR systems to ensure the precise identification of objects and obstacles. However, the absence of clear standards for LiDAR system design parameters poses challenges in determining the optical system configurations. This paper focuses on a procedure that determines the necessary resolutions in LiDAR systems, with a specific emphasis on target detection algorithms. The investigation methodology encompassed the steps involved in scenario generation, capturing LiDAR point cloud data, and evaluating the obtained LiDAR data. Multiple widely-used algorithms are selected to represent diverse approaches to object detection. The paper concludes by summarizing the derived angular resolution requirements for each algorithm. By incorporating these findings, developers can optimize LiDAR system configurations to meet the specific demands of their application domains, ultimately enhancing the performance and reliability of LiDAR applications.
While most of the efforts in the development of vehicle headlamps are focused on the design of high-resolution visible beam distributions, recent research shows the possibilities of using a near-infrared auxiliary headlamp for machine vision. Contrary to previous non-imaging approaches not designed to attenuate parts of the beam, this feature can supplement missing light during low-beam driving. This paper aims to evaluate various emitters and optical concepts for an auxiliary near-infrared headlamp, with particular emphasis on etendue and power density. Firstly, the system requirements for an automotive headlamp consisting of a visible and near-infrared source are discussed. Secondly, we evaluate differnent design approaches to the optical system with focus on the near-infrared subsystem. Consequently, the optomechatronical system is discussed, looking at optics, electronics and mechanics seperately.
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