LiDAR Virtual Camera Views for Collision and Vehicle Inspection
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Solution Overview
Problem
Current light ranging systems, such as LiDAR, have limitations in providing comprehensive environmental awareness to drivers, particularly in detecting potential collisions and inspecting vehicle parts, and lack dynamic display capabilities that adapt to changing vehicle poses.
Innovation Solution
A vehicle ranging system that uses one or more light ranging devices to provide three-dimensional image streams, allowing a virtual camera to change poses and offer dynamic displays of the environment, and includes semantic labeling for detecting vehicle parts and proximity breaches, enabling notifications and improved inspection processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed camera is used to capture environmental images, then the system structure is simple, but the system cannot adapt to changing vehicle poses and provide dynamic views
Solution Approach 1:
The patent uses a virtual camera that copies the functionality of a physical camera but exists as software within the 3D environment. This virtual camera can be positioned and oriented anywhere in the 3D space without adding physical complexity to the system, allowing it to adapt to changing vehicle poses while maintaining simple system structure.
Solution Approach 2:
The virtual camera's pose is dynamically adjusted based on vehicle movement and environmental conditions. The system automatically changes the virtual camera's position and orientation to provide optimal views as the vehicle moves, enabling adaptability without requiring physical camera adjustments.
2Adaptability or versatility
If multiple physical cameras are installed to provide multiple views, then dynamic display capabilities improve, but system cost and complexity increase
Solution Approach 1:
The single physical LiDAR system performs multiple functions: it captures 3D environmental data, constructs the 3D representation, and enables the virtual camera to generate multiple views. This multi-functional approach provides dynamic display capabilities without requiring multiple specialized camera devices.
Solution Approach 2:
The patent transitions from 2D camera images to 3D point cloud representation, adding a dimensional aspect that allows a single sensor to provide information equivalent to multiple cameras. The 3D space enables virtual camera positioning from any angle without requiring additional physical sensors.
3Reliability
If traditional collision detection systems are used, then the system is simple, but the ability to detect potential collisions and provide warnings is insufficient
Solution Approach 1:
The system performs preliminary detection by continuously monitoring the 3D environment and identifying potential collision risks before they become immediate threats. The virtual camera and 3D representation allow the system to anticipate potential hazards and provide advance warnings to the driver.
Solution Approach 2:
The system provides continuous feedback to the driver about environmental conditions and potential collision risks. By processing the 3D point cloud data and generating warnings based on detected hazards, the system creates a feedback loop that improves collision detection reliability without requiring complex additional hardware.
4Productivity
If vehicle inspection is performed manually, then the process is simple, but inspection efficiency and thoroughness are limited
Solution Approach 1:
The vehicle inspection system uses the vehicle's own LiDAR sensor to perform self-inspection. The system captures 3D data of the vehicle's exterior, automatically detects damage or anomalies, and generates inspection reports without requiring external inspection equipment or manual processes, thereby improving efficiency while keeping the system simple.
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
Enhances driver awareness with dynamic environmental displays and improves vehicle inspection efficiency by providing real-time notifications and semantic labeling of vehicle parts, reducing the risk of collisions and facilitating thorough inspections.
Implementation Method 1
A LiDAR system measures the distance to an object by irradiating a landscape with pulses from a laser, and then measuring the time for photons to travel to an object and return after reflection, as measured by a receiver of the LiDAR system. A distance to an object can be determined based on time-of-flight from transmission of a pulse to reception of a corresponding reflected pulse.
Data Source
AI summary
Methods are provided for using a light ranging system. A computing system receives, from light ranging devices, ranging data including distance vectors to environmental surfaces. A distance vector can correspond to a pixel of a three-dimensional image stream. The system can identify a pose of a virtual camera relative to the light ranging devices. The light ranging devices are separated from the pose by first vectors that are used to translate some of the distance vectors using the first vectors. The system may determine colors associated with the translated distance vectors and display pixels of the three-dimensional image stream using the colors at pixel positions specified by the translated distance vectors. The system may use one or more models with the ranging data to provide semantic labels that describe a region that has been, or is likely to be, in a collision.