13 patents in this list

Updated: February 06, 2024

Explore patents surrounding the enhancement of LiDAR systems through innovative alignment and calibration methods to improve accuracy and performance in various applications.

1. Sensor Array Calibration Technique for Correcting Misalignments in Vehicle Systems

Lyft, Inc., 2024

(Summary) Calibrating sensors in a vehicle sensor array to account for misalignments and improve accuracy. The calibration technique involves determining the relative orientation of the sensor array to the vehicle and comparing it to the expected orientation. If deviations are found, calibration factors can be calculated to correct sensor measurements. This can be done using techniques like comparing sensor output, using camera markers, or analyzing vehicle motion data.


2. Radiation Calibration Method for Airborne Hyperspectral Imaging LiDAR Systems


(Summary) Radiation calibration method for airborne hyperspectral imaging LiDAR system. The method calibrates the radiation detection of the LiDAR system so that the spectral data captured by the hyperspectral LiDAR can be used accurately for tasks like ground target classification. The calibration involves two steps: spectrum calibration using a monochromator to determine channel wavelengths, and radiation calibration using a rotating white board to determine channel sensitivities.

3. Camera-Assisted LiDAR Transmitter and Receiver Alignment for Enhanced Performance

Waymo LLC, 2023

(Summary) Precise alignment of LIDAR transmitter and receiver blocks to improve LIDAR performance. A camera is used to image the positions of the light sources in the transmitter block and the detectors in the receiver block. Any offsets between the positions are calculated and used to adjust the alignment of the blocks. This ensures the beams from the sources are directed to corresponding detectors, even if they are not initially aligned.

4. Sensor Fusion Method for Enhanced LiDAR-Based Positioning in Autonomous Vehicles


(Summary) Accurate, robust positioning for autonomous vehicles, using data from onboard sensors without relying on external maps. The method integrates inertial measurements with lidar point clouds and local maps to determine a vehicle's position. It compensates vehicle motion using inertial data, matches lidar points to maps, and probabilistically combines the data sources to optimize positioning.

5. Iterative Alignment Optimization of LiDAR and Camera Sensors for Autonomous Driving Systems

Luminar, LLC, 2022

(Summary) Optimizing alignment of lidar and camera sensors to merge data for autonomous driving systems. The method involves iteratively adjusting transformation parameters to align sensor data sets from sensors with overlapping fields of view. The alignment is optimized using a metric of mutual information between the sensor datasets.


6. Optimized LiDAR-Camera Calibration Technique for Autonomous Vehicle Perception

Lyft, Inc., 2021

(Summary) Calibrating LiDAR sensors with cameras in autonomous vehicles to ensure accurate alignment of data for environment perception. The calibration involves using a rotating platform with markers to generate 3D point clouds from the cameras and LiDAR. By optimizing the LiDAR position/rotation to match the cameras, misalignments can be determined and corrected.

7. Optimized Calibration and Alignment Technique for Coherent LiDAR Systems in Vehicles


(Summary) Calibration and alignment of coherent lidar systems for vehicles to maximize performance and range. The lidar system uses FMCW technology with phase modulation. The receive lens is aligned using an added waveguide coupler that allows a second light source to transmit through the lens. Optical phase modulators are calibrated to match the phase of the combined signals from the target and local oscillator. This ensures maximum signal strength when detected by photodetectors.

8. Sensor Calibration for Autonomous Vehicles Using LiDAR and Camera Data Integration


(Summary) Calibration of sensors like lidar and camera on autonomous vehicles. The calibration allows generating and maintaining high definition maps for safe autonomous driving. The system uses captured lidar and camera data to calibrate the sensors. It extracts corners from lidar points to align with camera edges. This provides a transform for mapping between lidar and camera coordinates. The calibrated sensors are then used to generate high precision maps that allow precise autonomous vehicle positioning in lanes for safe driving.


9. Camera-Assisted Method for Aligning LiDAR Optics

Waymo LLC, 2020

(Summary) A method to align LIDAR optics using a camera. The method involves obtaining images with the camera while interposing different apertures between the camera and LIDAR device. By analyzing the images, alignment offsets between the LIDAR transmitter and receiver can be determined.

10. Sensor Fusion Method for Enhancing Autonomous Vehicle Navigation with Camera and LiDAR

Mobileye Vision Technologies Ltd., 2019

(Summary) Using camera and lidar sensors together to enable autonomous navigation. The method involves aligning camera images with lidar reflections to correlate objects identified in both sensor outputs. This allows attributing lidar depth information to camera-detected objects. By combining camera object recognition with lidar distance measurement, it provides more accurate navigation information for autonomous vehicles.

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