Co-Aligned Rotating LiDAR-Imager Synchronization for 3D Mapping
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Solution Overview
Problem
Combining LIDAR and image sensor data to generate a 3D representation of an environment is challenging due to synchronization issues with photon collection timing, fields-of-view, and exposure time requirements, leading to image artifacts like smearing when the sensors rotate.
Innovation Solution
A device with a LIDAR sensor and an image sensor mounted on a rotating platform, where the image sensor captures pixels synchronously with LIDAR light pulse emission and detection times, and data is mapped to corresponding points in a point cloud, using a controller to align fields-of-view and adjust exposure times to reduce smearing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the LIDAR sensor and image sensor rotate together to scan the environment, then the 3D mapping coverage is improved, but image smearing artifacts occur due to rotation during exposure
Solution Approach 1:
The image sensor exposure is synchronized with the LIDAR rotation period. The image sensor captures images at specific angular positions during the rotation, creating periodic sampling that matches the rotational motion. This timing synchronization ensures that images are captured at consistent phases of the rotation cycle, reducing smearing artifacts while maintaining comprehensive scan coverage.
Solution Approach 2:
The exposure time of the image sensor is adjusted based on the rotation speed and angular position. By dynamically changing the exposure duration parameter, the system optimizes the balance between capturing sufficient light for image quality and minimizing the time the sensor is exposed to moving scenes that would cause smearing. The exposure time is set to be proportional to the angular displacement during the capture period.
2Illumination intensity
If the image sensor exposure time is increased to capture sufficient light, then image brightness is improved, but temporal synchronization with LIDAR pulses becomes difficult
Solution Approach 1:
The system pre-calculates the optimal exposure timing based on the known rotation speed and LIDAR pulse sequence. Before each image capture, the controller determines the precise angular position and synchronizes the exposure start time accordingly. This preliminary timing arrangement ensures that the image sensor begins exposure at the correct moment in the rotation cycle, maintaining synchronization with LIDAR pulses even with longer exposure durations.
Solution Approach 2:
The image sensor maintains continuous operation during rotation, with exposure timed to coincide with appropriate angular positions. Rather than interrupting the sensing process, the system continuously captures images at optimized moments throughout the rotation cycle. This continuous operation allows for longer cumulative exposure while maintaining temporal correspondence with LIDAR data collection.
3Measurement precision
If the LIDAR and image sensor are mounted separately to maintain alignment, then field-of-view matching is improved, but device complexity increases
Solution Approach 1:
The LIDAR sensor and image sensor are integrated into a single unified sensor assembly that rotates together as one unit. This merging of previously separate components eliminates alignment drift between sensors and simplifies the mechanical structure. The integrated design ensures that both sensors share the same rotational axis and maintain fixed relative positions, achieving field-of-view matching through physical integration rather than separate mounting adjustments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves sensor data quality by synchronizing data collection in both the time and space domains, reducing image artifacts and enhancing the accuracy of 3D mapping with synchronized LIDAR and image data.
Implementation Method 1
A LIDAR sensor can determine distances to environmental features while scanning through a scene to assemble a 'point cloud' indicative of reflective surfaces. Individual points in the point cloud can be determined, for example, by transmitting a laser pulse and detecting a returning pulse, if any, reflected from an object in the environment
Implementation Method 2
determining a distance to the object according to a time delay between the transmission of the pulse and the reception of its reflection
Implementation Method 3
An example image sensor can capture an image of a scene viewable to the image sensor. Each CCD may receive a portion of light from the scene incident on the array. Each CCD may then output a measure of the amount of light incident on the CCD during an exposure time
Data Source
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AI summary
Example implementations are provided for an arrangement of co-aligned rotating sensors. One example device includes a light detection and ranging (LIDAR) transmitter that emits light pulses toward a scene according to a pointing direction of the device. The device also includes a LIDAR receiver that detects reflections of the emitted light pulses reflecting from the scene. The device also includes an image sensor that captures an image of the scene based on at least external light originating from one or more external light sources. The device also includes a platform that supports the LIDAR transmitter, the LIDAR receiver, and the image sensor in a particular relative arrangement. The device also includes an actuator that rotates the platform about an axis to adjust the pointing direction of the device.