An Overview of LiDAR Requirements and Techniques for Autonomous Driving

Bastos, Daniel Deggau; Monteiro, Paulo P.; Oliveira, Arnaldo S. R.; Drummond, Miguel V.

doi:10.1109/conftele50222.2021.9435580

Cited by 27 publications

(6 citation statements)

References 43 publications

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“…The difference between the two training objectives will cause that the target before and after can not achieve the best match, and the detection accuracy can not be greatly improved. For example, the loss function in the depth estimation algorithm is to solve the difference between all pixels with truth values and their predicted depth values [7]. The loss in this part is the error of solving all pixels with truth values without difference, rather than focusing on the target.…”

Section: Spatial Attentionmentioning

confidence: 99%

P‐2.22: Research on 3D Target Detection Algorithm in Automatic Driving Scenario

2023

Symp Digest of Tech Papers

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As a research hotspot in computer vision, 3D object detection has wide application prospects. In the field of autonomous driving, the perception system with three-dimensional object detection function enables the vehicle to perceive the surrounding environment, make the vehicle more intelligent, and play a role in assisting driving. Aiming at two commonly used sensors: monocular camera and lidar, combined with deep learning, this paper separately studies the 3D target detection algorithm of PointPillars based on attention mechanism and the 3D target detection method based on monocular vision. The results show that the detection performance based on monocular vision still has advantages and can be used as an effective supplement to Lidar based three-dimensional target detection, improving the robustness of the sensing system.

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Section: Spatial Attentionmentioning

confidence: 99%

P‐2.22: Research on 3D Target Detection Algorithm in Automatic Driving Scenario

2023

Symp Digest of Tech Papers

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“…Lasers generating nanosecond optical pulses with high pulse powers are key components in time-of-flight (ToF) LIDAR systems that provide fast and reliable 3D-maps of the environment to be used for, e.g., autonomous movement of vehicles or robots, or industrial sensing [1][2][3]. The requirements, the system must fulfill for deployment, range from, for example, narrow-band emission in an atmospheric transparency window (e.g.…”

Section: Introductionmentioning

confidence: 99%

High brightness nanosecond-pulse operation of 905 nm distributed Bragg reflector tapered-ridge-waveguide lasers with multiple active regions

Christopher,

Beier,

Koester

et al. 2024

High-Power Diode Laser Technology XXII

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We present weakly tapered ridge waveguide distributed Bragg reflector lasers with three active regions epitaxially stacked in a common waveguide emitting nanosecond pulses around 905 nm for LIDAR. The vertical structure is optimized for pulsed operation and implementation of a surface Bragg grating for emission in the 2nd order vertical mode. 6 mm long diode lasers with a 25 µm output aperture, integrated into an inhouse high pulse current electronic driver, provide a pulse power > 20 W, a beam propagation ratio of M² ~ 4.5, and a lateral brightness of approx. 16 W/(mmmrad). The emission spectrum features a spectral width of < 0.3 nm and a temperature-related shift of < 70 pm/K.

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“…TOF-based sensors utilize the time and phase differences between emission and reflected light to estimate the distance between the object and the sensor. They are more suitable candidates for large FOVs and depth ranges, which is why LiDARs, one type of TOF-based depth imaging modality, predominate the autonomous driving field [ 8 ]. However, TOF sensors, such as Intel Real Sense L515, have low depth reconstruction accuracy, as shown in Figure 1 , making them unsuitable for industrial lines where products are small and require feature recognition in millimeter resolutions.…”

Section: Introductionmentioning

confidence: 99%

Active Dual Line-Laser Scanning for Depth Imaging of Piled Agricultural Commodities for Itemized Processing Lines

Ali,

Wang,

Tao

2024

Sensors

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The accurate depth imaging of piled products provides essential perception for the automated selection of individual objects that require itemized food processing, such as fish, crabs, or fruit. Traditional depth imaging techniques, such as Time-of-Flight and stereoscopy, lack the necessary depth resolution for imaging small items, such as food commodities. Although structured light methods such as laser triangulation have high depth resolution, they depend on conveyor motion for depth scanning. This manuscript introduces an active dual line-laser scanning system for depth imaging static piled items, such as a pile of crabs on a table, eliminating the need for conveyor motion to generate high-resolution 3D images. This advancement benefits robotic perception for loading individual items from a pile for itemized food processing. Leveraging a unique geometrical configuration and laser redundancy, the dual-laser strategy overcomes occlusions while reconstructing a large field of view (FOV) from a long working distance. We achieved a depth reconstruction MSE of 0.3 mm and an STD of 0.5 mm on a symmetrical pyramid stage. The proposed system demonstrates that laser scanners can produce depth maps of complex items, such as piled Chesapeake Blue Crab and White Button mushrooms. This technology enables 3D perception for automated processing lines and offers broad applicability for quality inspection, sorting, and handling of piled products.

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An Overview of LiDAR Requirements and Techniques for Autonomous Driving

Cited by 27 publications

References 43 publications

P‐2.22: Research on 3D Target Detection Algorithm in Automatic Driving Scenario

P‐2.22: Research on 3D Target Detection Algorithm in Automatic Driving Scenario

High brightness nanosecond-pulse operation of 905 nm distributed Bragg reflector tapered-ridge-waveguide lasers with multiple active regions

Active Dual Line-Laser Scanning for Depth Imaging of Piled Agricultural Commodities for Itemized Processing Lines

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