LIDAR Channel Activation for Multi-Resolution Point Cloud Processing
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Solution Overview
Problem
Current computer-implemented control systems in autonomous vehicles are not equipped to process point clouds generated by LIDAR systems with a large number of channels, leading to latency and the need for permanent deactivation of channels to reduce processing demands, which limits the advantage of increased resolution.
Innovation Solution
A dynamic channel activation and deactivation system in autonomous vehicles that identifies active and inactive channels based on environmental factors and scan data, allowing for varying resolutions in different horizontal bands of the point cloud without requiring system redesign or introducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR systems with a large number of channels are used to generate denser point clouds, then measurement precision is improved, but control system processing capability becomes insufficient leading to latency
Solution Approach 1:
The patent segments the LIDAR system into multiple independent channels that can be selectively activated or deactivated. Each channel corresponds to a specific angular range in elevation, allowing the system to divide the full point cloud into multiple subsets processed separately by the control system, thereby managing processing load while maintaining high resolution where needed.
Solution Approach 2:
The patent implements dynamic channel activation and deactivation based on real-time environmental factors and scan data. The control system dynamically determines which channels to activate for each scan, allowing the point cloud resolution to adapt to current operational needs rather than maintaining a fixed high resolution across all channels continuously.
2Measurement precision
If all channels of the LIDAR system are activated to maximize resolution, then measurement precision is improved, but device complexity increases due to processing demands
Solution Approach 1:
The patent applies local quality by providing high-resolution data only in specific angular ranges where it is most needed. By selectively activating channels corresponding to critical regions (such as areas where pedestrians are likely to be observed), the system achieves high measurement precision locally without requiring all channels to operate at maximum resolution simultaneously.
Solution Approach 2:
The patent implements partial action by activating only the necessary subset of channels required for the current scanning task rather than all channels. The control system determines the minimum set of channels needed based on environmental factors and operational requirements, reducing processing complexity while maintaining sufficient resolution for safe operation.
3Productivity
If channels are permanently deactivated to reduce processing load, then control system processing capability is improved, but measurement precision deteriorates due to reduced channel count
Solution Approach 1:
The patent transforms the static channel configuration into a dynamic one where channels can be activated or deactivated based on real-time conditions. This allows the system to optimize between processing capability and measurement precision for each scan, rather than being constrained by a fixed channel configuration that permanently sacrifices resolution.
Solution Approach 2:
The control system performs preliminary analysis of environmental factors and scan requirements before activating channels. By determining which channels will be needed in advance of each scan based on predicted operational needs, the system prepares the appropriate resolution levels proactively, avoiding both over-processing and under-processing.
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
Enables the autonomous vehicle to utilize the increased resolution of LIDAR systems with more channels while maintaining processing efficiency, focusing higher resolution on critical areas like pedestrian detection and adjusting based on terrain and travel conditions.
Implementation Method 1
Each light emitter/light detector pair is referred to as a 'channel' of the LIDAR systems
Implementation Method 2
LIDAR system that generates a point cloud having multiple resolutions
Data Source
AI summary
An autonomous vehicle having a LIDAR system mounted thereon or incorporated therein is described. The LIDAR system has N channels, with each channel being a light emitter/light detector pair. A computing system identifies M channels that are to be active during a scan of the LIDAR system, wherein M is less than N. The computing system transmits a command signal to the LIDAR system, and the LIDAR system performs a scan with the M channels being active (and N-M channels being inactive). The LIDAR system constructs a point cloud based upon the scan, and the computing system controls the autonomous vehicle based upon the point cloud.