Marker-Based Sensor Plane Orientation for Robot Localization
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Solution Overview
Problem
Robotic devices face challenges in accurately localizing themselves within environments due to sensor plane misalignment with marker planes, leading to less precise position and orientation estimates, especially when the sensor mast deviates from a vertical orientation.
Innovation Solution
A method and system that determine the orientation of a two-dimensional sensor plane relative to a horizontal marker plane by calculating a difference vector between mapped and measured marker positions, allowing for detection of sensor tilt and its cause, such as improper mounting or oscillation, using covariance matrices and eigenvalues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the sensor mast is positioned vertically to simplify mounting, then ease of manufacture is improved, but measurement precision deteriorates when the sensor plane becomes misaligned with the marker plane
Solution Approach 1:
The system dynamically determines the orientation parameters of the sensor plane relative to the marker plane by analyzing marker position data. Instead of relying on fixed physical alignment, the solution changes the parameter representation from physical orientation to computational orientation correction through calculated transformation matrices that compensate for misalignment.
Solution Approach 2:
The patent replaces the mechanical alignment system (physically mounting the sensor mast vertically) with a computational system that calculates and applies orientation corrections. The mechanical requirement for vertical mounting is substituted by mathematical transformation of sensor data to account for actual sensor plane orientation relative to the marker plane.
2Device complexity
If the sensor plane is misaligned with the marker plane, then device complexity is reduced by allowing flexible mounting, but measurement precision deteriorates due to inaccurate position and orientation estimates
Solution Approach 1:
The system uses feedback from observed marker positions to determine the actual orientation of the sensor plane. By continuously analyzing the relationship between expected marker positions (from the map) and measured marker positions (from the sensor), the system calculates correction factors that compensate for misalignment, creating a closed-loop system that maintains accuracy despite flexible mounting.
Solution Approach 2:
The system performs preliminary determination of sensor plane orientation characteristics before using the sensor data for localization. By calculating the orientation parameters and transformation matrices in advance, the system prepares the correction factors needed to maintain measurement precision regardless of the actual physical alignment between sensor and marker planes.
3Measurement precision
If covariance matrices and eigenvalues are used to detect sensor tilt, then measurement precision is improved by identifying misalignment, but device complexity increases due to additional computational requirements
Solution Approach 1:
The system uses the existing sensor data and marker map information to self-determine its own orientation characteristics. Instead of requiring external calibration equipment or additional sensors, the system analyzes the relationship between expected and measured marker positions to automatically calculate its orientation relative to the marker plane, making the complexity serve the function of improved precision.
Data Source
AI summary
Methods and systems for detecting sensor orientation characteristics using marker-based localization are disclosed herein. In one aspect, a robotic device can: receive a map of a horizontal marker plane that includes mapped positions of a first marker and a second marker arranged in the horizontal marker plane; receive, from a sensor configured to scan a two-dimensional sensor plane, sensor data indicative of positions of the first and second markers relative to the sensor; determine measured positions of the first and second markers based on the sensor data and a current position of the sensor; determine a difference vector between a first vector that connects the mapped positions of the first and second markers and a second vector that connects the measured positions of the first and second markers; and determine, based on the difference vector, an orientation of the two-dimensional sensor plane relative to the horizontal marker plane.