Surround-View Vehicle Visualization on Uneven Ground Surfaces
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Solution Overview
Problem
Existing vehicle visualization systems struggle to provide a realistic representation of the vehicle on non-planar ground surfaces, limiting the accuracy and effectiveness of the visualization.
Innovation Solution
A method and device that utilize current camera extrinsic parameters and vehicle suspension data to model a vehicle's position and ground surface, allowing for a realistic simulation of the vehicle's vertical motion on non-planar surfaces, using multivariate interpolations and affine transformations to compute the vehicle's three-dimensional posture and ground surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a predefined horizontal planar surface structure is used for ground modeling, then the visualization system is simple to implement, but it cannot reflect the true structure of the ground surface in real-time
Solution Approach 1:
The ground surface model transitions from a static horizontal plane to a dynamic surface that adapts in real-time based on vehicle suspension data and camera extrinsic parameters. The computation unit continuously updates the ground surface representation to reflect actual terrain conditions, making the system adaptive rather than fixed.
Solution Approach 2:
The system changes the parameters used to define the ground surface from fixed horizontal coordinates to dynamic parameters derived from suspension sensor data and camera extrinsic parameters. This allows the ground surface model to adjust its shape and position based on actual vehicle-terrain interaction.
2Measurement precision
If the ground surface is modeled to contact the wheels based on camera extrinsic parameters and suspension data, then the visualization becomes more realistic, but the computational complexity increases
Solution Approach 1:
The system uses data already being collected by the vehicle's existing sensors (cameras and suspension sensors) to automatically determine ground surface characteristics. The computation unit processes this self-generated data to create the adaptive ground model, eliminating the need for separate measurement systems.
Solution Approach 2:
The existing camera and suspension sensor systems serve multiple functions: they provide data for both vehicle control systems and for ground surface modeling. This multi-functional use of existing components reduces overall system complexity while achieving accurate terrain representation.
3Measurement precision
If real-time ground surface reflection is implemented, then the visualization accuracy improves, but the data processing requirements increase
Solution Approach 1:
The system combines ground surface modeling with the existing vehicle visualization function in a single computation unit. Rather than adding a separate ground detection and modeling system, the ground surface adaptation is integrated into the existing surround-view visualization pipeline, consolidating processing tasks.
Data Source
AI summary
The present disclosure provides a method for providing a visualization of a vehicle, the method having the steps: receiving, for each vehicle camera of a plurality of vehicle cameras of the vehicle, current values of camera extrinsic parameters of said vehicle camera; receiving vehicle suspension data relating to a suspension of wheels of the vehicle; and visualizing the vehicle using a predefined model of the vehicle, wherein the vehicle is visualized on a ground surface; wherein the ground surface is modelled to contact the wheels of the vehicle, based on the current values of the camera extrinsic parameters of the vehicle cameras and based on the suspension data.