Spinning Camera Frame-Time Control for Consistent Exposure
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Solution Overview
Problem
Cameras mounted on lidar devices often capture over- or under-exposed images due to varying light conditions, leading to unusable data and affecting lidar readings, particularly when the camera is positioned at different yaw angles and angles of elevation, such as when exiting a tunnel on a sunny day.
Innovation Solution
A camera system is programmed to take images at predetermined yaw angles and angles of elevation by actively adjusting the frame time based on lidar yaw angle and elevation, using a lookup table to determine appropriate exposure times, and adjusting blank lines in the image readout to achieve consistent exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the camera captures images continuously at different yaw angles and angles of elevation, then the coverage of the surrounding environment is improved, but the image exposure becomes inconsistent due to varying light conditions
Solution Approach 1:
The camera system dynamically adjusts the frame time based on the current yaw angle and angle of elevation to compensate for varying light conditions. The frame time is actively modified rather than kept constant, allowing the camera to adapt exposure parameters to the specific angular position and lighting environment, thereby maintaining consistent image exposure across different orientations while preserving comprehensive environmental coverage
Solution Approach 2:
The system changes the temporal parameter (frame time) of the camera based on angular position and lighting conditions. By modifying the frame time parameter dynamically according to the yaw angle, elevation angle, and detected light intensity, the system compensates for exposure variations caused by different viewing angles and lighting environments, achieving consistent image quality across all directions
2Manufacturing precision
If the camera adjusts exposure time for each angle, then the image exposure consistency is improved, but the system complexity increases
Solution Approach 1:
The system employs feedback by detecting the current light intensity at the camera's present angular position and using this information to determine the appropriate frame time. The light detector provides real-time feedback about the lighting conditions, which is then used to adjust the frame time accordingly, creating a closed-loop control system that maintains exposure consistency without requiring complex pre-programming for every possible scenario
Solution Approach 2:
The camera system serves itself by autonomously determining the appropriate frame time based on detected light intensity and current angular position. The system automatically selects frame times from a predetermined set based on the detected conditions, without requiring external intervention or complex manual control, thereby achieving exposure consistency through self-regulation
3Measurement precision
If the camera takes images at all angles, then the detection coverage of lidar window obstructions is improved, but the number of unusable over- or under-exposed images increases
Solution Approach 1:
The system performs preliminary action by establishing a predetermined relationship between angles, light intensity ranges, and appropriate frame times before actual operation. Lookup tables or pre-calibrated data structures store the optimal frame time settings for various angular positions and lighting conditions. This pre-prepared information allows the camera to quickly select appropriate exposure settings without trial and error, ensuring that images captured at all angles are usable for obstruction detection
Solution Approach 2:
The light detector provides real-time feedback about the current lighting conditions at each angular position, enabling the system to select appropriate frame times from predetermined settings. This feedback mechanism ensures that only images with proper exposure are captured and stored, eliminating unusable over- or under-exposed images while maintaining comprehensive angular coverage for reliable obstruction detection
Data Source
AI summary
Example embodiments relate to taking images at certain predetermined angles in order to have consistent exposure throughout the images. An example embodiment includes a method. The method includes determining, using a lidar device, light intensity information of a surrounding environment of the lidar device. The light intensity information includes a plurality of angles within a threshold range of light exposure. The method also includes determining rotation times associated with each of the angles within the threshold range of light exposure. Further, the method includes based on the rotation times associated with each of the angles within the threshold range of light exposure, determining a plurality of target image times. In addition, the method includes capturing, by a camera system, a plurality of images at the plurality of target image times.