Robot Posture Detection via Sensor Fusion and Gravity Correction
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Solution Overview
Problem
Current robot posture detection technologies based on single sensor data are inaccurate due to sensor abnormalities and high error rates, which hinder precise robot posture assessment.
Innovation Solution
A computer-implemented method that uses a combination of position sensors and gyroscopes to obtain and process position parameters of robot nodes, applying weighted values and discrete processing to calculate body gravity center offset values, thereby correcting the robot's center of gravity parameters for accurate posture detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single sensor detection data is used for robot posture detection, then the device complexity is reduced, but the measurement precision deteriorates due to sensor abnormality and high error rates
Solution Approach 1:
The patent combines multiple sensors (accelerometers, gyroscopes, and other detection sensors) into an integrated detection system. The controller receives and processes data from all these sensors simultaneously, merging their outputs to determine robot posture. This combination allows the system to compensate for individual sensor errors and abnormalities, significantly improving measurement precision while maintaining manageable device complexity through unified data processing.
2Measurement precision
If multiple sensors are combined for robot posture detection, then the measurement precision is improved, but the device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The controller serves multiple functions: it receives data from various sensors, processes the data, corrects errors, and determines robot posture. By making the controller a multi-functional component that handles all detection and processing tasks, the patent avoids the need for separate dedicated processing units for each sensor, thereby improving measurement precision while minimizing the increase in device complexity.
3Measurement precision
If sensor data is processed with weighted values and discrete processing, then the measurement precision is improved, but the computational complexity increases
Solution Approach 1:
The patent applies preliminary processing steps to sensor data before final posture calculation. Weighted values are assigned to different sensor data based on their reliability and characteristics, and discrete processing is performed to simplify the data. These preliminary actions prepare the data in advance, making the final center of gravity calculation more accurate while keeping the overall processing complexity manageable through structured, pre-planned data preparation steps.
Data Source
AI summary
The present disclosure is applicable to robot technology. A method for robot posture detection and a robot are provided. The method includes: obtaining a position parameter of each of nodes of a robot; obtaining a first weighted value of each of the nodes corresponding to the position parameter of the corresponding node; calculating a weighted value of each of body parts of the robot based on the first weighted value of the node of the corresponding body part; and correcting an original parameter of a center of gravity of the robot according to a body gravity center influence factor of each of the body parts, and the weighted value of each of the body parts.