Object Recognition Delay Compensation for Accurate Sensor Association
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Solution Overview
Problem
Existing object recognition devices face precision deterioration due to errors in associating prediction values with detection values, particularly in systems using multiple sensors like cameras, which can lead to incorrect object recognition.
Innovation Solution
An object recognition device that includes sensors to detect objects, a data reception unit to receive object data, and a setting unit to generate prediction data using a motion model and physical-quantity delay times, allowing for the correction of association regions to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If smoothing processing is applied to detection values from sensors, then measurement noise is reduced, but errors occur between prediction values and detection values due to different smoothing processing applied to different physical quantities
Solution Approach 1:
The patent changes the parameter of delay time from a single uniform value to multiple different values corresponding to different physical quantities. By setting different delay times for position and speed based on their respective smoothing processing characteristics, the system compensates for the timing differences introduced by differential smoothing, thereby maintaining accurate association determination while preserving measurement precision.
2Device complexity
If a single delay time is used for all physical quantities, then processing is simplified, but association errors occur when different smoothing processing is applied to different physical quantities
Solution Approach 1:
The patent applies local quality by assigning different delay time characteristics to different physical quantities based on their specific smoothing processing requirements. Instead of using a uniform delay time globally, the system tailors the delay time parameter locally to each physical quantity (position, speed, etc.), ensuring optimal association determination for each while maintaining overall system manageability.
3Productivity
If prediction data is generated using motion models, then current object data can be predicted, but errors occur between prediction values and detection values due to timing mismatches
Solution Approach 1:
The patent applies preliminary action by pre-calculating and setting appropriate delay times for each physical quantity before association determination is performed. This allows the system to compensate for timing differences between prediction and detection in advance, ensuring that when association determination occurs, the values being compared are temporally aligned, thereby maintaining both recognition speed and prediction accuracy.
Data Source
AI summary
The object recognition device includes at least one sensor, a data reception unit, and a setting unit. The sensor detects an object present in a detectable range and transmits object data including a plurality of physical quantities indicating a state of the object. The data reception unit receives the object data from the sensor. The setting unit generates prediction data which predicts current object data based on at least a part of past object data received by the data reception unit and a motion model in the object, and sets a association possible region for determining a association between the prediction data and the current object data based on a plurality of physical-quantity delay times each corresponding to each of the plurality of physical quantities included in the prediction data.