Trajectory Point Weighting for Stable Path-Following Control
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Solution Overview
Problem
Conventional methods for filtering measurement data in path-following control of vehicles do not account for varying fluctuations in point coordinates, leading to instability and jerky movements.
Innovation Solution
A method that acquires measurement data of a trajectory, weights point coordinates with different factors based on their fluctuations, and applies these weights for filtering to stabilize path-following control, particularly by fixing point coordinates near the object with smaller weighting factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all point coordinates are filtered equally without weighting, then the filtering process is simple, but the path-following control becomes unstable and jerky due to varying fluctuations in different point coordinates
Solution Approach 1:
The patent applies different weighting factors to different point coordinates based on their local characteristics. Point coordinates closer to the vehicle are assigned smaller weighting factors (stronger filtering) while those farther away receive larger weighting factors (weaker filtering). This local differentiation resolves the contradiction by adapting the filtering strength to the specific needs of each point coordinate, improving stability without applying uniform complexity across all points.
Solution Approach 2:
The patent changes the parameter of weighting factors dynamically based on the distance of each point coordinate from the vehicle. By adjusting this parameter according to spatial position, the system achieves adaptive filtering that improves path-following stability while maintaining reasonable computational complexity through a systematic parameter assignment strategy.
2Ease of operation
If point coordinates in immediate vicinity of the object are fixed with smaller weighting factors, then the path-following control becomes smoother and more stable, but the flexibility of the control is reduced
Solution Approach 1:
The patent implements a dynamic weighting strategy where the weighting factor is determined by the distance of each point coordinate from the vehicle. This creates a continuous gradient of filtering strength rather than a fixed binary approach. The system dynamically adapts the filtering intensity based on spatial position, achieving smooth control while retaining flexibility through the distance-based parameter variation.
Solution Approach 2:
By applying stronger filtering (smaller weighting factors) only to point coordinates in the immediate vicinity of the vehicle and weaker filtering to distant points, the system achieves local optimization. This resolves the contradiction by making the control smooth where it matters most (near the vehicle) while maintaining flexibility for distant points that require less aggressive filtering.
Data Source
AI summary
A method for filtering measurement data for a path-following control of an object is provided. The method includes: acquiring measurement data of a portion of a trajectory along which the object is to move, the measurement data including a plurality of point coordinates, which are subject to local fluctuations, and thereby form a point cloud; weighting the plurality of point coordinates by assigning them each different weighting factors, the different weighting factors each specifying the possible fluctuations of the individual point coordinates of the point cloud, at least one point coordinate in an immediate vicinity of the object being fixed by assigning a weighting factor of smaller magnitude to the point coordinate than to a point coordinate at a distance from the object; and performing the filtering for all point coordinates of the point cloud based on the different weighting factors for the path-following control of the object.