CN117484474B - Soft robot shape reconstruction and control system based on optical fiber sensing - Google Patents
Soft robot shape reconstruction and control system based on optical fiber sensing Download PDFInfo
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- 229910001172 neodymium magnet Inorganic materials 0.000 claims description 4
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/0009—Constructional details, e.g. manipulator supports, bases
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1635—Programme controls characterised by the control loop flexible-arm control
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- Engineering & Computer Science (AREA)
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- Mechanical Engineering (AREA)
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Abstract
The invention discloses a soft robot shape reconstruction and control system based on optical fiber sensing, which comprises a magnetic soft robot strain acquisition and shape visualization real-time reconstruction module, a closed-loop control module and an image display and data storage. The operation principle of the system is that optical fiber sensing is arranged in a magnetically sensitive soft robot, optical fiber signals in the magnetically sensitive soft robot are collected at a high speed through an optical fiber demodulator and converted into strain signals to be transmitted to a reconstruction module of the system for shape reconstruction, meanwhile, analog signals output by a control instrument are collected by utilizing high-speed synchronous collection hardware equipment, high-speed processing is carried out by combining a comparator and a closed-loop control module, and output current of a control signal control power supply is generated so as to regulate and control a magnetic field generated by an electromagnet (an actuator) in real time, so that closed-loop control of the magnetically sensitive soft robot is realized. The system has high shape reconstruction efficiency, high control precision and strong synchronism; the software and hardware collocation flexibility is strong, and the expandability is strong, thereby facilitating the system upgrade.
Description
Technical Field
The invention relates to the technical field of intelligent soft robots, in particular to a soft robot shape reconstruction and control system based on optical fiber sensing.
Background
The magnetically sensitive soft material has the characteristics of long-distance controllability, rapidness, reversibility and large deformation under the drive of a magnetic field, and has great application potential in the emerging fields of biomedical treatment, bionic soft robots, flexible electrons and the like. With the rapid development of advanced manufacturing technology, the magnetic-sensitive intelligent soft structure with multi-mode complex deformation characteristics and multiple functions can be prepared by combining 3D printing technology and micro-and macro-structural design.
The inspiration of the soft robot is derived from natural living things, besides the excellent functions, the sensing is very important to the soft robot, so that the soft robot has the sensing and response functions to the environment and the state of the soft robot, but the current research on the sensing function of the magnetically sensitive soft robot is less, and the simple deformation state of the soft robot is monitored and identified by an electric signal, but the specific magnetically driven deformation shape cannot be identified. The shape recognition capability is extremely important to the driving control of the magnetically sensitive soft material in special complex environments such as closed, non-transparent and the like, for example, the magnetically sensitive soft robot is applied to the fields of interventional minimally invasive treatment, drug transportation, biopsy and the like in biomimetic science and biomedical. In addition, the sensor elements based on the electrical signals are disadvantageous for magnetically driven soft robots, since the electrical signals are subject to electromagnetic interference. The optical fiber sensor has the characteristics of small volume, light weight and strong electromagnetic interference resistance. When an optical signal passes through the optical fiber, the change of temperature and strain can cause the change of parameters such as optical wavelength or frequency, so that the strain or temperature detection of the structure can be realized.
How to apply the optical fiber sensing to the soft robot based on the characteristics of the optical fiber sensing to enrich the sensing function of the magnetically sensitive soft robot and improve the magnetic driving control efficiency is a technical problem to be solved.
Disclosure of Invention
The invention aims to provide a soft robot shape reconstruction and control system based on optical fiber sensing, which enriches the sensing function of a magnetically sensitive soft robot and improves the magnetic driving control efficiency of the magnetically sensitive soft robot. And constructing a system comprising a magnetic soft robot strain acquisition and shape visualization real-time reconstruction module, a closed-loop control module, an image display and data storage. The optical fiber sensor is arranged in the magneto-sensitive soft robot, optical fiber signals are collected at high speed through the optical fiber demodulator and converted into strain signals, and the strain signals are transmitted to a reconstruction module of the system for shape reconstruction. Meanwhile, the closed-loop control module utilizes the high-speed synchronous acquisition hardware equipment to acquire an analog signal output by a control instrument, combines the comparator and the closed-loop control module to perform high-speed processing, and generates a control signal to control the output current of a power supply so as to regulate and control the driving magnetic field generated by the electromagnet in real time, thereby realizing the closed-loop control of the magnetically sensitive soft robot.
Therefore, the invention provides a soft robot shape reconstruction and control system based on optical fiber sensing, which adopts the following technical scheme:
the shape reconstruction and control system of the soft robot based on optical fiber sensing is characterized in that an optical fiber sensor is arranged in the soft robot and is connected with an optical fiber demodulator, and the optical fiber demodulator is used for converting optical fiber signals acquired by the optical fiber sensor into strain signals; the system comprises:
The shape reconstruction module is connected with the optical fiber demodulator and is used for receiving the strain signal and performing shape reconstruction according to the strain signal;
The closed-loop control module is used for acquiring analog signals output by the control instrument by utilizing high-speed synchronous acquisition hardware equipment, carrying out high-speed processing by combining with the comparator, and generating control signals to control the output current of the power supply so as to realize closed-loop control of the magnetically sensitive soft robot.
Further, the optical fiber sensor includes one of a continuous distributed OFDR optical fiber sensor and a quasi-distributed FBG optical fiber sensor, and a combination thereof.
Further, the soft robot has a granular phase and a matrix phase.
Further, the particle phase comprises a hard magnetic magnetically sensitive soft material or a soft magnetic magnetically sensitive soft material, the soft magnetic magnetically sensitive soft material comprising one of ferrite, samarium cobalt and neodymium iron boron particles.
Further, the matrix phase comprises silicone gel, polydimethylsiloxane, dakaning 1700, silicone gel, or flexible photo-curable epoxy.
Further, the preparation method for arranging the optical fiber sensor in the soft robot comprises 3D printing integrated embedding, injection molding embedding or surface pasting.
Further, the shape reconstruction module performs shape reconstruction using an Euler-Bernoulli rod theory, a Rayleigh-Ritz method, or a spatially differentiated geometry.
Further, the Euler-Bernoulli rod theory and Rayleigh-Ritz method specifically include:
The method comprises the steps of converting wavelength or frequency signals of an optical fiber into strain signals, converting the strain signals into curvature and corner cutting signals which are distributed continuously and equidistantly along the length of a structure based on a spatial resolution and numerical interpolation method, and calculating the spatial coordinates of each point through translational rotation transformation of coordinates to reconstruct a deformed shape.
Further, the spatial differential geometry specifically includes:
Converting the spatially distributed strain into characteristic parameter curvature and deflection rate of the curve, calculating the strain value of each position in the optical fiber by using a flener formula among tangential direction, normal direction and auxiliary normal direction of the curve in the three-dimensional space in a distributed sensing mode, and solving a differential equation by using a numerical method to obtain the position of the multi-core optical fiber in the three-dimensional space.
Further, the closed-loop control module controls the direction of the magnetic field of the electromagnet by controlling the direction of the output current in the power supply, so as to finally achieve the purpose of controlling the soft robot, the shape reconstruction module, the closed-loop control module and the image display and data storage module form an integrated system to be connected, the collected optical fiber sensing strain signals are utilized to reconstruct the real-time deformation shape, the magnetic driving closed-loop control of the soft robot can be realized based on the collected control current and voltage signals of the electromagnet, and all results are displayed and stored in the image display and data storage module.
The beneficial effects of the invention are as follows:
The invention provides a software robot shape reconstruction and control system based on distributed optical fibers, which provides effective multi-signal multi-channel high-speed synchronous acquisition and transmission, ensures that a plurality of experimental instruments are effectively monitored and controlled in the experimental process, and further realizes real-time reconstruction and closed-loop control of the magnetically-driven deformed shape of a magnetically-sensitive software robot and synchronous display and storage of various signal data. The system has high shape reconstruction efficiency and control precision and strong synchronism for the soft robot; the software and hardware collocation flexibility is strong, and the expandability is convenient for upgrading. The method is characterized in that a high-efficiency shape reconstruction algorithm and high-speed synchronous acquisition hardware equipment are utilized to acquire and process signal data between an instrument and a computer at a high speed, so that visual real-time reconstruction and magnetic drive closed-loop control of a deformed shape are realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale.
FIG. 1 shows a block diagram of a soft robot shape reconstruction and control system based on fiber optic sensing in accordance with an embodiment of the present invention;
Fig. 2 shows a schematic logic structure of a soft robot shape reconstruction and control system based on optical fiber sensing according to an embodiment of the present invention.
Fig. 3 shows a schematic diagram of a platform built based on a soft robot shape reconstruction and control system according to an embodiment of the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples.
The embodiment of the invention provides a soft robot shape reconstruction and control system based on optical fiber sensing, as shown in fig. 1, the system comprises a shape reconstruction module 101, a closed loop control module 102 and an image display and data storage module 103, the optical fiber sensing is arranged in a magnetically sensitive soft robot, an optical fiber demodulator is used for collecting optical fiber signals at a high speed and converting the optical fiber signals into strain signals, and the strain signals are transmitted to a reconstruction module of the system for shape reconstruction. Meanwhile, the closed-loop control module utilizes the high-speed synchronous acquisition hardware equipment to acquire an analog signal output by the control instrument, combines the comparator and the closed-loop control module to perform high-speed processing, and generates a control signal to control the output current of the power supply so as to realize closed-loop control of the magnetically sensitive soft robot.
In some embodiments, the software robot shape reconstruction and control system based on fiber optic sensing is built based on, but not limited to, one or more software co-developments in Labview, MATLAB, python, C ++.
In some embodiments, the optical fiber sensing includes, but is not limited to, continuous distributed OFDR optical fiber sensing or quasi-distributed FBG optical fiber sensing.
In some embodiments, the magnetically sensitive soft robot has a particle phase including but not limited to hard magnetically sensitive soft material or soft magnetically sensitive soft material (ferrite, samarium cobalt or neodymium iron boron particles) and a matrix phase including but not limited to silicone gel, polydimethylsiloxane, dacorning 1700, silica gel or flexible photo-cured epoxy.
In some embodiments, the optical fiber sensor is disposed in a magnetically sensitive soft robot, prepared by a method including, but not limited to, 3D printing integrated embedding (fused deposition, direct write photo-curing), injection molding embedding, or surface pasting.
In some embodiments, the above-mentioned signal and data transmission, such as the data transmission between the shape reconstruction module 101, the closed loop control module 102, and the image display and data storage module 103, and the data transmission between the fiber optic demodulator and each module, include, but are not limited to, wired transmission (USB, serial, ethernet, MBus) or wireless transmission (bluetooth, wiFi).
In some embodiments, the shape reconstruction module implements methods of reconstructing shapes including, but not limited to, euler-Bernoulli rod theory and Rayleigh-Ritz methods or spatially differentiated geometries. The Euler-Bernoulli rod theory and Rayleigh-Ritz method firstly converts the wavelength or frequency signal of an optical fiber into a strain signal, converts the obtained strain signal into curvature and corner cutting signals which are continuously and equidistantly distributed along the length of a structure according to a spatial resolution and numerical interpolation method, and then obtains the spatial coordinates of each point through translational rotation transformation of the coordinates so as to realize reconstruction of a deformed shape. The space differential geometry is to convert the spatially distributed strain into the characteristic parameter curvature and the bending rate of the curve, and utilize the flener formula (Frenet-Serret Formulas) among the tangential direction, the normal direction and the auxiliary normal direction of the curve in the three-dimensional space to calculate the strain value of each position in the optical fiber in a distributed sensing mode, and solve the differential equation in a numerical method, so as to obtain the position of the multi-core optical fiber in the three-dimensional space.
In some embodiments, in the closed-loop control module and the image display and data storage module, the closed-loop control module controls the size direction of the magnetic field of the electromagnet by controlling the size direction of the output current in the power supply, so as to finally achieve the purpose of controlling the deformation mode of the soft robot. The optical fiber sensing strain signals, the current and voltage signals of the electromagnet and the reconstructed real-time deformation shape acquired by the system are all generated and stored in a computer screen.
In this embodiment, as shown in fig. 2, the system has two systems, namely a software system and a hardware system, when being built. As shown in fig. 3, a schematic diagram of a platform constructed based on the system is shown.
In a hardware system, the needed magneto-sensitive soft robot is prepared by direct-writing 3D printing, the material composition of the magneto-sensitive soft robot is a composite material composed of neodymium-iron-boron particles and silicone adhesive, and distributed optical fiber sensing is integrally printed and embedded in the 3D printing process. The distributed optical fiber demodulator can collect optical frequency signals at high speed (120 Hz) and convert the optical frequency signals into optical fiber strain, and the highest spatial resolution can reach 0.65mm. The magnetic driver consists of a power supply, an emergency switch and an electromagnet, wherein the power supply can provide positive and negative 80A direct current, alternating current, sine, pulse, square wave and the like for the electromagnet, and the magnetic driver belongs to a programmable power supply. The electromagnet is a solenoid magnet, which can generate a magnetic field of 0.5T at the highest load current. The experimental device is formed by connecting cables with large current carrying capacity in series. The acquisition card is used for completing the acquisition of power supply voltage and current signals and sending the signals to a computer for processing through a wireless network. The command for controlling the power supply is directly sent to the power supply through the USB interface connected with the computer, and the acquisition signal and the sending control command are mutually independent and processed in parallel so as to achieve the highest acquisition and processing effects.
The software system comprises a shape reconstruction module and a closed-loop control module, and the construction mode of the shape reconstruction module and the closed-loop control module is jointly developed by Labview, MATLAB software.
And the shape reconstruction module transmits the optical fiber signals acquired by the optical fiber demodulator to a reconstruction algorithm by using a high-speed communication mode in the magnetic driving deformation process to perform high-speed operation processing, reconstruct the deformation shape of the magnetically sensitive soft robot in real time, and display and store the deformation shape in real time. The high-speed transmission mode of the data is a wireless network.
The high-speed synchronous multichannel acquisition card with the input and output functions in the closed-loop control module is a core, and can achieve a sampling rate of 100 MS/s. And acquiring an analog signal or a digital signal for controlling the output current or voltage of the magnetic field power supply by using the acquisition card, and transmitting the analog signal or the digital signal to the closed-loop control system. And judging the current state of the structure by combining with the comparator, and processing and storing data at high speed. Meanwhile, a control command of power supply current or voltage is generated and sent to the power supply at a high speed, so that the control of the magnetic field is realized, and finally, the drive control of the magnetically sensitive soft robot is realized.
The above embodiments are only for illustrating the present invention, not for limiting the present invention, and various changes and modifications may be made by one of ordinary skill in the relevant art without departing from the spirit and scope of the present invention, and therefore, all equivalent technical solutions are also within the scope of the present invention, and the scope of the present invention is defined by the claims.
Claims (5)
1. The shape reconstruction and control system of the soft robot based on the optical fiber sensing is characterized in that the soft robot is internally provided with an optical fiber sensor, the optical fiber sensor is connected with an optical fiber demodulator, and the optical fiber demodulator is used for converting an optical frequency signal acquired by the optical fiber sensor into a strain signal in the driving deformation process of the soft robot; the system comprises:
The shape reconstruction module is connected with the optical fiber demodulator and is used for receiving the strain signal and reconstructing the shape in real time according to the strain signal and a reconstruction algorithm;
The closed-loop control module is used for acquiring a current analog signal output to the actuator by the control instrument by utilizing high-speed synchronous acquisition hardware equipment, carrying out high-speed processing by combining with the comparator, generating a control signal to control the output current of the power supply so as to regulate and control the driving magnetic field generated by the electromagnet in real time, thereby realizing closed-loop control of the soft robot;
the soft robot has a particle phase and a matrix phase, and has multi-mode, rapid and reversible large deformation characteristics and remote driving characteristics under an external magnetic field;
The reconstruction algorithm in the shape reconstruction module adopts an Euler-Bernoulli rod theory and a Rayleigh-Ritz method to reconstruct the shape;
The Euler-Bernoulli rod theory and the Rayleigh-Ritz method specifically comprise the following steps: converting an optical frequency signal acquired by an optical fiber sensor into a strain signal, converting the strain signal into curvature and corner cutting parameters which are continuously and equidistantly distributed along the length of the structure based on a spatial resolution and numerical interpolation method, and calculating the spatial coordinates of each point through translational rotation transformation of the coordinates so as to realize reconstruction of a deformed shape;
The closed-loop control module controls the direction of the output current in the power supply to control the direction of the magnetic field of the electromagnet, the shape reconstruction module, the closed-loop control module, the image display and the data storage module form an integrated system, the collected optical fiber sensing strain signals are utilized to reconstruct the real-time deformation shape, the magnetic driving closed-loop control of the soft robot is realized based on the collected control current and voltage signals of the electromagnet, and all results are displayed and stored in the image display and data storage module.
2. The fiber optic sensing based soft robotic shape reconstruction and control system of claim 1, wherein the fiber optic sensor comprises one or a combination of a continuous distributed OFDR fiber optic sensor and a quasi-distributed FBG fiber optic sensor.
3. The optical fiber sensing based soft robotic shape reconstruction and control system of claim 1, wherein the granular phase comprises a hard magnetic magnetically sensitive soft material or a soft magnetic magnetically sensitive soft material comprising one of ferrite, samarium cobalt, and neodymium iron boron granules.
4. The optical fiber sensing based soft robotic shape reconstruction and control system of claim 1, wherein the matrix phase comprises silicone gel, polydimethylsiloxane, dakaning 1700, silicone gel, or flexible photo-curable epoxy.
5. The optical fiber sensing-based soft robot shape reconstruction and control system according to claim 1, wherein the preparation of the optical fiber sensor arrangement in the soft robot comprises 3D printing integration embedding, injection molding embedding or surface pasting.
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| CN109730776A (en) * | 2018-12-28 | 2019-05-10 | 北京信息科技大学 | The monitoring system of soft robot system |
| CN110216667A (en) * | 2019-06-26 | 2019-09-10 | 华中科技大学 | A kind of controllable magnetization system of magnetic control soft robot |
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| CN109828223A (en) * | 2019-01-30 | 2019-05-31 | 兰州大学 | A kind of Fbg Sensor For Measuring Magnetic Field calibration system and method |
| CN113733545A (en) * | 2021-08-31 | 2021-12-03 | 兰州大学 | Preparation method of magnetic-sensitive intelligent superstructure |
| CN114378805B (en) * | 2022-01-26 | 2023-08-15 | 浙江大学 | Four-foot crawling pneumatic soft robot capable of detecting bending state |
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| CN109730776A (en) * | 2018-12-28 | 2019-05-10 | 北京信息科技大学 | The monitoring system of soft robot system |
| CN110216667A (en) * | 2019-06-26 | 2019-09-10 | 华中科技大学 | A kind of controllable magnetization system of magnetic control soft robot |
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| 光纤形状传感技术综述;赵士元;崔继文;陈勐勐;;光学精密工程;20200115(第01期);第10-29页 * |
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