Scanning Distance Sensor Model Sequential Scanning Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for modeling scanning distance sensors, such as LIDAR, neglect the effect of sequential scanning in dynamic environments, leading to distortions in measured point clouds, which are critical in automotive applications like advanced driver assistance systems.
Innovation Solution
A method that includes modeling the sensor and objects with velocities in three-dimensional space, estimating the effect of sequential scanning, and inversely applying this effect to the detections to correct for simultaneity, thereby aligning the model results with real scanning measurements without significantly increasing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If sequential scanning is neglected in sensor modeling to simplify computation, then computational complexity is reduced, but measurement precision deteriorates due to distortions in point clouds
Solution Approach 1:
The patent applies preliminary action by pre-calculating the sequential scanning effect and its inverse transformation. The method pre-determines the distortion pattern caused by sequential scanning and prepares correction factors that are then applied to the detected point cloud data, enabling efficient post-processing correction without complex real-time simulations
Solution Approach 2:
The patent creates a simplified mathematical model that copies and simulates the sequential scanning effect. Instead of performing complex physical simulations, the invention uses a computational copy of the scanning process that replicates the distortion patterns, which can then be efficiently corrected using the pre-calculated inverse transformation
2Measurement precision
If sequential scanning effect is corrected by full physical simulation, then measurement precision is improved, but computational complexity increases significantly
Solution Approach 1:
The patent applies parameter changes by transforming the complex physical simulation problem into a simplified parameter-based correction model. The method changes the approach from simulating physical scanning processes to adjusting mathematical parameters that represent the scanning effect, enabling efficient computation through parameter transformation rather than full physical simulation
Solution Approach 2:
The patent substitutes the mechanical/physical scanning simulation with a mathematical computation system. Instead of simulating the physical movement and scanning process in detail, the invention replaces it with mathematical transformations and calculations that produce the same corrective effect, significantly reducing computational complexity
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
The method provides more accurate and reliable prototyping results for scanning distance sensors by accounting for the sequential scanning effect, improving the accuracy of point clouds and reducing computational costs.
Implementation Method 1
The light's time of flight, i.e. the time from emitting the light to detecting its reflection, can be used as a measure for the distance between the point where the light was reflected and the sensor
Implementation Method 2
To distinguish the reflections from other light that hits the detector, the emitted light is preferably modulated or pulsed
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
For prototyping parameters of a scanning distance sensor and/or for prototyping software which processes the output of such sensor it is useful to model the sensor. The presented method of modelling a scanning distance sensor comprises that a model of the sensor and of one or more objects in the surroundings of the sensor is defined, the model including, for each of the sensor and the objects, information about its respective location and velocity in three-dimensional space. The method further comprises that, for at least one point in time, a set of detections is determined as if obtained by the sensor when scanning a field of view of the sensor, wherein each of the detections corresponds to a different line of sight originating from the sensor and comprises information about the orientation of the respective line of sight and about the distance of a respective target point from the sensor, the target point being the point in space where the line of sight first crosses any of the objects at the respective point in time. The method in particular comprises that the set of detections is modified by estimating the effect of sequentially scanning the field of view in discrete time steps on the detections and inversely applying the estimated effect to the set of detections.