Rotating LiDAR-Imager Alignment for Smear-Free 3D Mapping
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Solution Overview
Problem
Combining LIDAR and image sensor data to create a synchronized 3D representation of an environment is challenging due to timing and exposure time differences between the two sensors, leading to issues like image smearing during rotation.
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 synchronized in both the time and space domains to maintain overlapping fields-of-view and reduce exposure times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the image sensor uses a longer exposure time to capture sufficient light, then the image quality improves, but the rotation of the platform causes image smearing and misalignment with LIDAR data
Solution Approach 1:
The system determines the platform rotation amount during the exposure period and uses this information to adjust the imaging region in advance. By predicting the rotation and compensating for it before the exposure completes, the system maintains spatial alignment between LIDAR and image data while allowing longer exposure times for better image quality
Solution Approach 2:
The system dynamically adjusts the imaging region parameters (position and size) based on the detected platform rotation amount. By changing the imaging region parameters in real-time to compensate for rotation, the system maintains alignment precision without requiring short exposure times
2Productivity
If the platform rotates faster to increase scanning coverage, then the productivity improves, but the timing synchronization between LIDAR and image sensor becomes more difficult
Solution Approach 1:
The system detects the actual platform rotation amount during image capture and uses this feedback information to adjust the imaging region and timing parameters. This closed-loop feedback mechanism maintains synchronization precision between LIDAR and image sensor even at higher rotation speeds for increased productivity
Solution Approach 2:
The system dynamically adjusts the imaging region and exposure timing based on the actual platform rotation speed and amount. By making the imaging parameters adaptive to the rotation dynamics, the system maintains synchronization precision across varying rotation speeds
3Manufacturing precision
If the exposure time is reduced to prevent image smearing, then the spatial alignment precision improves, but the image quality deteriorates due to insufficient light capture
Solution Approach 1:
The system determines the platform rotation amount in advance and pre-adjusts the imaging region to account for expected rotation during exposure. This allows the use of longer exposure times without sacrificing spatial alignment precision, as the rotation compensation is already in place
Solution Approach 2:
Instead of solely relying on short exposure times to prevent smearing, the system introduces a temporal dimension by measuring and compensating for rotation amount that occurs during exposure. This transforms the problem from a spatial constraint to a spatiotemporal solution, allowing longer exposures while maintaining alignment
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
This approach improves sensor data quality by reducing image artifacts and enhances the accuracy of sensor fusion, allowing for precise mapping of color and distance information in a 3D representation.
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
the image sensor may include an array of charge-coupled devices (CCDs) or other types of light sensors. 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
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.