Variable-Width Sensor Scanning for Occupancy Grid Mapping
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Solution Overview
Problem
Existing probabilistic occupancy grid methods for environmental perception require significant computational resources and are not optimally efficient in terms of spatio-temporal resolution, especially when using sensors with wide detection regions.
Innovation Solution
Adapt the detection region width of an orientable sensor dynamically, using a narrow region for fine sampling in areas of interest and a wider region for coarser sampling, with orientation adjustments based on the occupancy grid and optionally movement grids, employing integer computations for Bayesian fusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a uniform scanning approach is used with wide detection region, then the coverage area is improved, but the measurement precision deteriorates
Solution Approach 1:
The patent applies local quality by making the detection region width variable rather than uniform. The sensor dynamically adjusts its detection region width based on the occupancy grid, using narrow regions for fine sampling in areas of interest and wider regions for coarser sampling in less critical areas. This resolves the contradiction by providing high measurement precision where needed while maintaining broad coverage where acceptable.
2Measurement precision
If narrow detection region is used for fine sampling, then the measurement precision is improved, but the productivity deteriorates
Solution Approach 1:
The patent implements dynamics by making the detection region width adjustable and adaptive rather than fixed. The system dynamically changes the detection region width based on real-time occupancy grid information, narrowing it for detailed sampling of interesting areas and widening it for faster scanning of other areas. This resolves the contradiction by optimizing the balance between precision and scanning speed according to actual environmental needs.
3Reliability
If probabilistic occupancy grid method is applied, then the reliability is improved, but the device complexity worsens
Solution Approach 1:
The patent applies parameter changes by modifying the detection region width parameter dynamically based on occupancy grid analysis. Instead of using fixed parameters, the system adjusts the detection region width according to the identified regions of interest, thereby reducing unnecessary computations in low-interest areas while maintaining accurate perception where needed. This resolves the contradiction by optimizing computational resource usage while preserving perception reliability.
Data Source
AI summary
A method for perceiving physical bodies in an environment, including the following steps: a) controlling a sensor in an acquisition sequence, with the sensor having a detection region that can be oriented in order to acquire a plurality of distance measurements of the physical bodies; b) determining, based on each of the distance measurements, a probability of occupancy of a set of cells of an occupancy grid by a physical body; and c) constructing a consolidated occupancy grid by Bayesian fusion of the probabilities of occupancy estimated during step b); wherein the detection region of the sensor has a variable angular width and in that the method also comprises the following steps: d) identifying, based on the occupancy grid, at least one region of interest of the environment; and e) determining, based on the one or more regions of interest identified during step d), one of the acquisition sequences defining, for each distance measurement, at least the orientation and the angular width of the detection region of the sensor. A system for implementing such a method is also provided.