Mobile Robot Magnetic 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 position and orientation without relying on previous pose data and are prone to errors due to distortions in magnetic fields caused by conductive objects, which can lead to inaccuracies in navigation and mapping.
Innovation Solution
A mobile robot system that 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 by modulating the calibration magnetic field and adjusting sensor circuit gains to maintain detection signals within a dynamic range, thereby improving accuracy and precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SLAM techniques are used for localization and mapping, then the robot can determine its position and orientation, but the system is prone to errors due to magnetic field distortions from conductive objects
Solution Approach 1:
A calibration coil is introduced as an intermediary component that generates a known calibration magnetic field. This calibration field serves as a reference to distinguish between actual position changes and magnetic field distortions caused by conductive objects. The calibration coil acts as a mediator between the sensor coils and the environment, providing a stable reference that is independent of external magnetic field disturbances.
Solution Approach 2:
The system dynamically adjusts the gain of the sensor circuit based on calibration signals. By changing the amplification parameter of the sensor circuit in response to calibration data, the system compensates for variations in magnetic field strength and maintains measurement accuracy despite changes in robot position or environmental magnetic conditions.
2Measurement precision
If the robot navigates farther from the magnetic field transmitter, then the detection signals decrease in amplitude, but maintaining signal amplitude within dynamic range requires complex gain adjustment
Solution Approach 1:
The system employs feedback control where the controller monitors the amplitude of detection signals and automatically adjusts the sensor circuit gain accordingly. The calibration signals provide a reference level that enables the controller to determine appropriate gain adjustments, creating a closed-loop system that maintains signal amplitudes within the optimal dynamic range without manual intervention.
Solution Approach 2:
The calibration coil and controller work together to enable the system to self-adjust. The calibration coil generates reference signals that automatically trigger gain adjustments in the sensor circuit, allowing the system to maintain optimal performance without external calibration or manual configuration.
3Measurement precision
If calibration coil is added to generate calibration magnetic field, then detection signal normalization is improved, but device complexity increases
Solution Approach 1:
The calibration coil serves multiple functions: it generates calibration magnetic fields for signal normalization, provides reference signals for gain adjustment, and enables error compensation. By making this single component multi-functional, the system achieves improved measurement precision without proportionally increasing overall system complexity.
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
The system enables accurate and efficient estimation of the robot's pose relative to a magnetic field transmitter, reducing errors and the need for previous pose data, and improving computational efficiency by maintaining detection signals within a smaller dynamic range.
Implementation Method 1
sensor coils that generate electrical signals in response to the magnetic fields
Data Source
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.