Flexible Robot Arm Shape Calibration Using Bragg Reflectors
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Solution Overview
Problem
Flexible arm robots, such as continuum arm robots and borescopes, face challenges in accurate positional control due to their flexible nature, making it difficult to determine their shape and length within a workspace, which hinders automated control and precise task execution.
Innovation Solution
Integration of distributed Bragg reflectors into flexible arm robots, combined with machine learning algorithms that utilize sensor data and FBG interrogation results to determine a calibration function for precise positional and shape determination, enabling accurate control of the robot arm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If flexible arm robots are used to access inaccessible spaces, then adaptability and versatility are improved, but measurement precision and positional control accuracy deteriorate
Solution Approach 1:
The flexible arm is segmented into multiple sections with distributed Bragg reflectors at different positions. Each section can be independently monitored by sensors, allowing precise measurement of position and shape throughout the entire arm length, resolving the measurement accuracy issue while maintaining flexibility
Solution Approach 2:
The patent replaces traditional mechanical positioning systems with optical sensing technology. Distributed Bragg reflectors combined with optical sensors provide non-contact, high-precision measurement of the flexible arm's position and shape, eliminating the need for complex mechanical control systems
2Measurement precision
If complex systems are implemented to determine robot position and shape, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The distributed Bragg reflector system serves multiple functions simultaneously: it acts as both a structural component of the flexible arm and a sensing element for position and shape measurement. This multi-functionality reduces the need for separate measurement systems, simplifying the overall device while maintaining high measurement precision
Solution Approach 2:
The flexible arm structure itself provides the sensing capability through integrated Bragg reflectors. The arm's deformation directly modulates the optical properties of the embedded reflectors, allowing the structure to serve its own measurement needs without requiring external complex measurement equipment
3Measurement precision
If distributed Bragg reflectors are integrated into the flexible arm, then measurement precision is improved, but manufacturing complexity increases
Solution Approach 1:
The Bragg reflectors are nested within the flexible arm structure, with optical fibers containing the reflectors embedded inside the arm's segments. This nested configuration allows the sensing elements to be integrated into the existing arm structure during manufacturing, reducing overall complexity compared to adding external sensing systems
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 solution provides accurate determination of the shape and position of flexible arm robots, reducing errors and enabling automated control, which is crucial for precise tasks such as inspection and repair in complex environments.
Implementation Method 1
interrogating the distributed Bragg reflector during these movements; the distributed Bragg reflector being connected to an interrogator measuring the change in Bragg wavelength as the robot bends
Data Source
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AI summary
A method of determining the position and shape of a flexible arm robot having at least one distributed Bragg reflector integrated, the method comprising: moving the flexible arm robot through a series of movements; tracking the movements of the flexible arm robot and recording positional data of at least a section of the flexible arm robot as a ground truth and interrogating the distributed Bragg reflector during these movements; inputting the data from the interrogation of the distributed Bragg reflector and the camera into a machine learning algorithm; using the output of the machine learning algorithm to determine a calibration function for the position of the distributed Bragg reflector within the flexible arm robot; and applying the calibration function to software used to control the movement of the flexible arm robot.