Magnetic Field Robot Localization With Self-Calibrating Sensor Coils
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Solution Overview
Problem
Existing localization techniques for mobile robots, such as SLAM, face challenges in accurately determining pose without previous data and are prone to errors that accumulate over time, especially in environments with distortions like metallic structures.
Innovation Solution
A mobile robot uses sensor coils to detect magnetic fields, with a calibration coil generating a calibration magnetic field to normalize detection signals, allowing the controller to estimate pose relative to a transmitter magnetic field, even in distorted environments, by dynamically adjusting the calibration magnetic field to maintain signal amplitudes within a predetermined range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SLAM techniques are used for localization, then the robot can build a map and localize itself, but errors accumulate over time and accuracy deteriorates
Solution Approach 1:
The patent introduces magnetic field transmitters as intermediary reference points distributed in the environment. These transmitters create detectable magnetic field signatures that serve as mediators between the robot and the environment, enabling direct pose estimation without relying on accumulated odometry data. The robot's sensor coils detect these magnetic fields to determine position and orientation relative to the transmitters.
Solution Approach 2:
The patent replaces mechanical localization methods (odometry, wheel encoders, inertial sensors) with magnetic field-based detection. Instead of relying on mechanical motion tracking that accumulates errors, the system uses electromagnetic field detection to directly measure pose, substituting the mechanical measurement chain with an electromagnetic sensing approach that resets error accumulation.
2Adaptability or versatility
If magnetic field detection is used for pose estimation, then localization without previous data is enabled, but signal amplitude degrades at farther locations
Solution Approach 1:
The patent implements dynamic gain adjustment in the sensor circuit, where the amplification factor is automatically modified based on the detected signal strength. When the robot moves farther from transmitters and signal amplitude decreases, the gain increases to maintain signal quality. This dynamic adaptation allows the system to operate effectively across varying distances without sacrificing measurement precision.
Solution Approach 2:
The system changes the electrical parameters (gain, amplification factor) of the sensor circuit based on operating conditions. By monitoring signal amplitude and adjusting the amplification parameter dynamically, the system compensates for distance-related signal degradation and maintains consistent measurement quality across the operational range.
3Measurement precision
If sensor coils are used to detect magnetic fields, then pose determination is enabled, but signal amplitudes vary requiring complex normalization
Solution Approach 1:
The patent implements self-calibration where the robot periodically generates its own calibration magnetic field using an onboard coil and uses this to normalize the sensor coil responses. This self-service approach eliminates the need for external calibration equipment or complex pre-calibration procedures. The system uses its own resources to automatically adjust for sensor variations, simplifying the overall calibration process while maintaining measurement precision.
Solution Approach 2:
The system incorporates feedback loops where the detected magnetic field signals are continuously compared against expected patterns, and the sensor gains are adjusted based on the difference. This feedback mechanism automatically compensates for signal amplitude variations and sensor inconsistencies, reducing the need for complex offline calibration procedures and enabling real-time normalization.
4Productivity
If dynamic calibration is performed to maintain signal amplitudes in predetermined range, then computational efficiency is improved, but additional control mechanisms are required
Solution Approach 1:
The patent merges the calibration coil function with the sensor coil array, using the same physical platform for both generating calibration fields and detecting operational fields. This integration reduces the number of separate control mechanisms needed compared to having dedicated calibration equipment. The controller that manages sensor readings also manages calibration, consolidating control functions and reducing overall system complexity while maintaining computational efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method improves accuracy, precision, and computational efficiency of pose estimation, reducing the need for expensive signal processing components and enabling the robot to localize without previous data, even in environments with distortions.
Implementation Method 1
A mobile robot includes a calibration coil configured to generate a calibration magnetic field
Implementation Method 2
sensor coils that generate electrical signals in response to the magnetic fields
Data Source
Figure 1A~1B
Figure 2
Figure 3
AI summary
A mobile robot includes a body movable over a surface within an environment, a calibration coil carried on the body and configured to produce a calibration magnetic field, a sensor circuit carried on the body and responsive to the calibration magnetic field, and a controller carried on the body and in communication with the sensor circuit. The sensor circuit is configured to generate calibration signals based on the calibration magnetic field. The controller is configured to calibrate the sensor circuit as a function of the calibration signals, thereby resulting in a calibrated sensor circuit configured to detect a transmitter magnetic field within the environment and to generate detection signals based on the transmitter magnetic field. The controller is configured to estimate a pose of the mobile robot as a function of the detection signals.