Micro-robot adaptive obstacle avoidance system and method

Abstract

This invention discloses an adaptive obstacle avoidance system and method for microrobots. An image acquisition module is positioned above the microfluidic device to acquire first image information reflecting the microrobot's activity in a target liquid environment. A wavelength calculation module determines the background sound field wavelength based on characteristic dimensions. A surface acoustic wave (SAW) transducer excites a background sound field with the background sound field wavelength in the target liquid environment. The background sound field, after being modulated by the target obstacle, forms a sound pressure obstacle avoidance channel that bypasses the obstacle. The sound pressure within the sound pressure obstacle avoidance channel is periodically distributed to form an obstacle avoidance potential well array. A driving device moves the SAW transducer, causing the modulated sound pressure obstacle avoidance channel in the target liquid environment to perform controlled movement, thereby driving the microrobot to perform obstacle avoidance actions through the obstacle avoidance potential well array. This invention enables adaptive obstacle avoidance for microrobots and can also drive microrobots to complete long-stroke continuous movements.

Description

Technical Field

[0001] This invention relates to the field of acoustic flow control technology, and more particularly to an adaptive obstacle avoidance system and method for microrobots. Background Technology

[0002] In related technologies, acoustic manipulation systems for microrobots struggle to achieve long-distance, high-precision automatic obstacle avoidance in complex microfluidic environments with obstacles. On one hand, traditional sound field translation methods cause the microrobot to directly collide with obstacles, resulting in transport failure. On the other hand, path reconstruction methods based on signal modulation are limited by the acoustic aperture size and cannot achieve real-time obstacle avoidance during long-stroke continuous motion, thus leaving room for improvement. Summary of the Invention

[0003] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes an adaptive obstacle avoidance system for microrobots, which can realize adaptive obstacle avoidance of microrobots and can also drive microrobots to complete long-stroke continuous motion.

[0004] This invention proposes an adaptive obstacle avoidance system for microrobots.

[0005] This invention also proposes an adaptive obstacle avoidance method for microrobots.

[0006] A first aspect of this invention provides a microrobot adaptive obstacle avoidance system, comprising a microfluidic device, an image acquisition module, a wavelength calculation module, a surface acoustic wave transducer, and a driving device. The microfluidic device provides a target liquid environment; the image acquisition module is positioned above the microfluidic device; wherein the image acquisition module is configured to acquire first image information reflecting the microrobot's activity in the target liquid environment, the first image information including the feature dimensions of target obstacles in the target liquid environment; the wavelength calculation module is communicatively connected to the image acquisition module and configured to determine the background sound field wavelength based on the feature dimensions; the surface acoustic wave transducer is communicatively connected to the wavelength calculation module, positioned below the microfluidic device, and at a predetermined vertical distance from the microfluidic device, and configured to excite in the target liquid environment... A background sound field with a background sound field wavelength; wherein the preset distance is configured such that the microfluidic device is located in the near-field region of the background sound field excited by the surface acoustic wave transducer, the background sound field is modulated by the target obstacle to form a sound pressure obstacle avoidance channel that bypasses the target obstacle, and the sound pressure in the sound pressure obstacle avoidance channel is periodically distributed to form an obstacle avoidance potential well array; a driving device is connected to the surface acoustic wave transducer; wherein the driving device drives the horizontal movement of the surface acoustic wave transducer to cause the sound pressure obstacle avoidance channel formed after modulation in the target liquid environment to perform controlled movement, and then drives the microrobot to perform obstacle avoidance actions through the obstacle avoidance potential well array.

[0007] Furthermore, the image acquisition module is configured to continuously acquire multiple first actual position information of the microrobot in the target liquid environment at a first preset frame rate; the microrobot adaptive obstacle avoidance system also includes a position compensation control module, which is communicatively connected to the image acquisition module and the driving device, and is configured to: compare the first actual position information with the expected position information corresponding to the preset motion trajectory of the microrobot, and calculate the position deviation of the microrobot; based on the position deviation, control the driving device to drive the surface acoustic wave transducer to move in the direction and / or move at a speed to adjust the moving direction and / or move at a speed of the sound pressure obstacle avoidance channel.

[0008] Furthermore, the image acquisition module is configured to continuously acquire multiple second actual position information of the microrobot in the target liquid environment at a second preset frame rate; the microrobot adaptive obstacle avoidance system also includes a stability determination module, which is communicatively connected to the image acquisition module and the driving device, and is configured to: calculate the displacement between any two adjacent second actual position information; when the displacement is continuously lower than a preset stability threshold for a preset stability time, determine that the microrobot has reached a stable dwell state, and trigger the driving device to drive the surface acoustic wave transducer to move.

[0009] Furthermore, the wavelength calculation module is specifically configured to: determine the wavelength of the background sound field, such that the ratio of the feature size of the target obstacle to the wavelength of the background sound field in the target liquid environment is between 1 / 4 and 1 / 2.

[0010] Furthermore, the microrobot adaptive obstacle avoidance system also includes a fluid membrane disposed between the microfluidic device and the surface acoustic wave transducer.

[0011] Further, the driving device includes a fixed base, a first movable base, a locking mechanism, a second movable base, and a moving platform. The fixed base is provided with a first guide rail inclined relative to a first direction and a vertical direction; the first movable base is slidably mounted on the first guide rail; the locking mechanism includes a locking pin, a first locking hole on the first guide rail, and a second locking hole on the first movable base, the locking pin passing through both the first and second locking holes to lock the relative positions of the fixed base and the first movable base; the second movable base is movably mounted on the first movable base along a second direction; the moving platform is fixedly mounted on the second movable base and has a mounting surface extending horizontally, the mounting surface being fixedly connected to the surface acoustic wave transducer; wherein the first direction and the second direction are perpendicular, and both the first direction and the second direction are parallel to the horizontal direction.

[0012] A second aspect of the present invention provides a microrobot adaptive obstacle avoidance method, further applied to the microrobot adaptive obstacle avoidance system described in the first aspect of the invention, comprising: The first image information of the target liquid environment where the microrobot is located is acquired by the image acquisition module. The first image information includes the feature size of the target obstacle. The background sound field wavelength is determined by the wavelength calculation module based on the characteristic dimensions. A background sound field with the wavelength of the background sound field is excited in the target liquid environment by a surface acoustic wave transducer. The background sound field is modulated by the target obstacle to form a sound pressure obstacle avoidance channel that bypasses the target obstacle. The sound pressure in the sound pressure obstacle avoidance channel is periodically distributed to form an obstacle avoidance potential well array. The horizontal movement of the surface acoustic wave transducer is driven by a driving device, so that the acoustic pressure obstacle avoidance channel formed after modulation in the target liquid environment performs controlled movement, and then the microrobot is driven to perform obstacle avoidance actions through the obstacle avoidance potential well array.

[0013] Furthermore, the movement of the surface acoustic wave transducer driven by the driving device includes: The image acquisition module acquires multiple first actual position information of the microrobot in the target liquid environment at a first preset frame rate. The position compensation control module compares the first actual position information with the expected position information corresponding to the preset motion trajectory of the microrobot, and calculates the position deviation of the microrobot. Based on the positional deviation, the driving device is controlled by the compensation control module to drive the surface acoustic wave transducer to move in the direction and / or speed, so as to adjust the moving direction and / or speed of the sound pressure obstacle avoidance channel.

[0014] Furthermore, before driving the movement of the surface acoustic wave transducer via the driving device, the method further includes: Multiple second actual position information of the microrobot in the target liquid environment are continuously acquired by the image acquisition module at a second preset frame rate; The stability determination module calculates the displacement between any two adjacent second actual position information. When the displacement is continuously lower than the preset stability threshold for a preset stability time, it is determined that the microrobot has reached a stable dwell state, and the driving device is triggered by the stability determination module to drive the surface acoustic wave transducer to move.

[0015] Furthermore, the background sound field wavelength is determined based on the characteristic dimensions using a wavelength calculation module; This includes determining the wavelength of the background sound field such that the ratio of the characteristic size of the obstacle to the wavelength of the background sound field in the target liquid environment is between 1 / 4 and 1 / 2.

[0016] The microrobot adaptive obstacle avoidance system according to embodiments of the present invention has at least the following beneficial effects: by matching the characteristic size between the background sound field wavelength and the target obstacle, the background sound field can form a sound pressure obstacle avoidance channel that bypasses the target obstacle under the modulation of the target obstacle, so that the microrobot is located in the obstacle avoidance potential well array of the sound pressure obstacle avoidance channel under the action of potential energy; by moving the surface acoustic wave transducer, the sound pressure obstacle avoidance channel formed after modulation by the target obstacle in the target liquid environment is made to perform controlled movement, and then the obstacle avoidance potential well array drives the microrobot to perform obstacle avoidance action, thereby realizing the microrobot adaptively bypassing the target obstacle in the target liquid environment and improving the reliability of operation in complex environments.

[0017] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments, wherein: Figure 1 This is a schematic diagram of the overall structure of the microrobot adaptive obstacle avoidance system according to an embodiment of the present invention; Figure 2 This is a cross-sectional schematic diagram of the microrobot adaptive obstacle avoidance system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the adaptive obstacle avoidance function of the microrobot according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a microrobot remaining in an obstacle avoidance potential energy trap according to an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the formation of a sound pressure avoidance channel by the background sound field coupling and scattering field in an embodiment of the present invention. Figure 6 This is a schematic diagram of the sound pressure avoidance channel according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the microrobot adaptive obstacle avoidance function experiment according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the surface acoustic wave transducer structure according to an embodiment of the present invention; Figure 9 This is an assembly diagram of the surface acoustic wave transducer, fluid membrane, and microfluidic device body according to an embodiment of the present invention; Figure 10 This is a diagram showing the distribution of target obstacles within a microfluidic device. Figure 11 This is a flowchart of the microrobot adaptive obstacle avoidance method according to an embodiment of the present invention; Figure 12 This is another flowchart of the microrobot adaptive obstacle avoidance method according to an embodiment of the present invention; Figure 13 This is another flowchart of the microrobot adaptive obstacle avoidance method according to an embodiment of the present invention.

[0019] Figure label: Microrobot adaptive obstacle avoidance system 100, microrobot 200, microrobot cluster 210, target obstacle 300, liquid environment 400; Microfluidic device 1, fixture 11, microfluidic device body 12, channel top 121, substrate 122; Image acquisition module 2, industrial camera 21, optical tube 22; Surface acoustic wave transducer 3, piezoelectric material 31, drain wire 32, electrode 33, standing wave transducer 34; Drive device 4, fixed base 40, first guide rail 401, first movable base 41, second movable base 42, moving platform 43, mounting surface 431, locking mechanism 44, first lock hole 441, second lock hole 442; Fluid membrane 5; Background sound field 61, scattering field 62, sound pressure obstacle avoidance channel 63, obstacle avoidance potential energy trap 64. Detailed Implementation

[0020] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0021] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., are based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0022] In the description of this invention, "several" means one or more, "multiple" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0023] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0024] In the description of this invention, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0025] Microrobot technology is a cutting-edge interdisciplinary field integrating micro- and nanoscience with robotics, aiming to develop novel functional devices with feature sizes ranging from micrometers to nanometers that can perform specific tasks. With breakthroughs in microelectromechanical systems (MEMS) fabrication processes, microrobots have shown broad application prospects in precision medicine, environmental monitoring, and advanced manufacturing. Their core lies in achieving precise manipulation and intelligent control of targets at the micrometer to nanometer scale through the coordinated actuation of multiple physical fields (such as magnetism, light, sound, electricity, and chemical energy). Among these, acoustic field actuation has become an important technological approach for microrobot manipulation due to its advantages of being non-contact, label-free, and biocompatible.

[0026] In the field of acoustic manipulation theory, Gor'kov's theory establishes the relationship between acoustic radiation force and acoustic pressure gradient, indicating that particles in a standing wave field will be driven to the point of minimum potential energy. Based on this, researchers have developed various acoustic field manipulation methods, including potential well reconstruction through phase modulation and changing the acoustic field distribution through frequency tuning. However, traditional acoustic field manipulation methods face a common problem: when there are obstacles (such as columnar structures, bubbles, or impurities) in the particle's path, the overall translation of the acoustic field will cause the particle to directly collide with the obstacle, leading to transport failure; while path reconstruction methods based on signal modulation are limited by the size of the acoustic aperture, making it difficult to achieve real-time obstacle avoidance in long-distance continuous motion.

[0027] Acoustic fluid manipulation, a cutting-edge interdisciplinary field in micro-nano manipulation, achieves non-contact, high-precision manipulation of microscopic targets through the synergistic effect of sound waves and microfluidics. Its core component, acoustic tweezers, is gradually revolutionizing research paradigms in fields such as biomedicine, materials science, and environmental monitoring. Acoustic tweezers utilize the principle of acoustic radiation force, adjusting the frequency, phase, and amplitude of sound waves to create a controllable sound pressure field in the fluid, applying directional force to particles to achieve functions such as capture, movement, rotation, and sorting. Among the many types of acoustic tweezers technology, micromanipulation systems based on surface acoustic waves have become a research hotspot due to their high-frequency operating characteristics, low power consumption, and good compatibility with planar microfabrication processes. This system uses patterned interdigital transducers on a piezoelectric substrate to excite high-frequency sound waves. When the sound waves propagate to the solid-liquid interface, energy leakage occurs, forming a sound field in the fluid and generating acoustic radiation force or acoustic drag force on microscale targets, achieving functions such as capture, transport, and patterned arrangement. A movable surface acoustic wave (SAW) system based on a four-port delay line structure achieves independent control of the sound field position by separating the transducer from the microfluidic device and introducing a coupling layer to conduct acoustic energy. This breaks through the limitations of traditional acoustic aperture on the manipulation range, enabling the driving of particles to achieve continuous movement with micron-level precision within millimeter- or even centimeter-level travel distances, providing an important platform for the automated control of microrobots. As acoustic fluid control technology expands into complex application scenarios, maintaining the stability and reliability of particle transport in non-ideal environments with obstacles has become a key challenge in current research, giving rise to a new direction of cross-integration between topological acoustics and acoustic fluid control.

[0028] In recent years, research in topological acoustics has provided new insights into overcoming this limitation. By introducing specific periodic modulations into the structure, topological acoustic materials can form edge or interface states with anti-backscattering properties, enabling sound waves to propagate without loss around defects. Researchers have observed the phenomenon of topological interface states guiding particles around corners and cavities in bulk acoustic systems, demonstrating the improvement in robustness of mass transport through topological protection. Furthermore, acoustic fluid control chips based on valley Hall topological insulators have enabled the visualization of chiral vortices and valley vortices, and topological pressure traps have been used to manipulate nanoscale targets such as DNA. However, current topological acoustics work mainly focuses on observing passive transport phenomena in fixed sound fields and has not yet been integrated with mobile sound field systems, failing to achieve active, long-range, and high-precision automatic obstacle avoidance manipulation.

[0029] Furthermore, the "conformal acoustic field" design concept provides a new dimension for improving the acoustic manipulation performance of microrobots. By making the geometry of the microrobot conform to the distribution of acoustic field nodes and antinodes, its acoustic energy capture efficiency and motion stability can be optimized. However, existing conformal designs are mainly designed for ideal acoustic field environments and do not consider the dynamic adaptation problem when obstacles are present in complex environments.

[0030] In summary, existing surface acoustic wave (SAW) micromanipulation systems have significant shortcomings in obstacle avoidance capabilities in complex environments: on the one hand, traditional sound field translation methods cannot automatically avoid obstacles; on the other hand, topological acoustics research has not yet been integrated with mobile sound field systems, and active control methods are lacking. Therefore, how to combine the robust transport characteristics of topological acoustics with the long-stroke advantages of mobile SAW systems to achieve automatic obstacle avoidance manipulation of microrobots in complex microchannels has become a pressing technical problem to be solved in this field.

[0031] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0032] The following is combined Figures 1-13 The present invention describes a microrobot adaptive obstacle avoidance system 100 and a microrobot 200 adaptive obstacle avoidance method according to embodiments of the present invention.

[0033] Example 1 See Figure 1 and Figure 2 The first aspect of the present invention provides a microrobot adaptive obstacle avoidance system 100, the system including a microfluidic device 1, an image acquisition module 2, a wavelength calculation module, a surface acoustic wave transducer 3, and a driving device 4.

[0034] See Figure 3 The microfluidic device 1 is used to provide a target liquid environment 400. Specifically, the microfluidic device 1 provides a carrying space for the target liquid environment 400. The microfluidic device 1 has a chamber or microchannel for the microrobot 200 to move in, and the target liquid environment 400 contains pre-existing or dynamically existing target obstacles 300.

[0035] See Figure 2 and Figure 11 As shown, the image acquisition module 2 is positioned above the microfluidic device 1. The image acquisition module 2 is configured to acquire first image information reflecting the activity of the microrobot 200 in the target liquid environment 400. This first image information includes the characteristic dimensions of the target obstacle 300 in the target liquid environment 400. The image acquisition module 2 maintains a relatively fixed positional relationship with the microfluidic device 1. The detection optical path of the image acquisition module 2 covers the area within the microfluidic device 1 where the microrobot 200 is active, thereby acquiring the first image information reflecting the activity of the microrobot 200 in the target liquid environment 400. The first image information includes the characteristic dimensions of the target obstacle 300 in the target liquid environment 400. These characteristic dimensions can be parameters that characterize the geometric scale of the target obstacle perpendicular to the direction of background sound field propagation, such as the diameter, equivalent particle size, width, length, or circumcircle diameter of the target obstacle. The first image information contains characteristic dimension data that can be used by subsequent modules. This data can be obtained through image processing or through manual measurement and input; the present invention does not limit this.

[0036] like Figure 11 As shown, the wavelength calculation module is communicatively connected to the image acquisition module 2 and is configured to determine the background sound field wavelength based on the feature size. The feature size of the target obstacle 300 obtained by the image acquisition module 2 is used as an input parameter, and a corresponding background sound field wavelength is output. It should be noted that different feature sizes correspond to different background sound field wavelengths, and this correspondence should ensure that the subsequently formed sound pressure obstacle avoidance channel 63 can effectively bypass the obstacle. By reasonably selecting the wavelength (e.g., making the wavelength and feature size of the same order of magnitude), the background sound field 61 can be scattered and refracted when encountering an obstacle, thereby forming a sound pressure obstacle avoidance channel 63 that bypasses the obstacle. For example, when the obstacle feature size is large, the wavelength increases accordingly; when the size is small, the wavelength decreases accordingly. The specific mapping relationship can be predetermined by system calibration or acoustic simulation, the principle being that the subsequently formed sound pressure obstacle avoidance channel 63 can effectively bypass obstacles of that size.

[0037] See Figure 3 , Figure 4 , Figure 5 and Figure 11 The surface acoustic wave transducer 3 is communicatively connected to the wavelength calculation module and is located below the microfluidic device 1. It is configured to excite a background sound field 61 with a background sound field wavelength in the target liquid environment 400. The background sound field 61 is modulated by the target obstacle 300 to form a sound pressure obstacle avoidance channel 63 that bypasses the target obstacle 300. The sound pressure in the sound pressure obstacle avoidance channel 63 is periodically distributed to form an obstacle avoidance potential well array. When the background sound field 61 propagates, due to the constraints of the boundary conditions (i.e., the difference in acoustic impedance between the target obstacle 300 and the liquid medium), the background sound field 61 is reflected and refracted at the interface of the target obstacle 300, generating a scattered field 62 that diffuses in a direction away from the target obstacle 300. The scattered field 62 and the background sound field 61 are coupled and superimposed to form a local sound field with a spatial modulation structure near the obstacle. The local sound field has the following characteristics: the sound wave energy is localized near a specific path around the obstacle, and the energy in the direction perpendicular to the specific path decays rapidly, thus forming a sound pressure obstacle avoidance channel 63; along the extension direction of the sound pressure obstacle avoidance channel 63, the sound pressure is periodically distributed, forming an obstacle avoidance potential well array with alternating sound pressure nodes and anti-nodes. The radiation potential energy is lowest at the sound pressure nodes, which can stably capture the microrobot 200; when there is an obstacle on the path of the sound pressure obstacle avoidance channel 63, due to the topological protection characteristics of the local sound field, the sound wave energy can naturally bypass the obstacle outline and continue to propagate without the need for pre-planning of the geometric path.

[0038] Please see Figure 4It should be further explained that, in the absence of a target obstacle 300, the background sound field 61 excited by the surface acoustic wave transducer 3 exhibits a regular periodic sound pressure distribution (e.g., a traveling wave or standing wave node array) in the target liquid environment 400, forming a periodic potential well array, but without a sound pressure obstacle avoidance channel 63 to bypass a specific object (target obstacle 300). The microrobot 200 can be captured by any one of the periodic potential energy wells in the periodic potential well array, and by moving the surface acoustic wave transducer 3, the periodic potential well array can be moved, thereby driving the microrobot 200 to move; see [link to relevant documentation]. Figure 5 When the background sound field 61 propagates to the interface of the target obstacle 300, the background sound field 61 is refracted and scattered. Only on the side of the target obstacle 300 away from the sound source (or in a specific area around it), the scattered field 62 couples with the background sound field 61, modulating a local sound pressure obstacle avoidance channel 63 that bypasses the target obstacle 300. The spatial range of the sound pressure obstacle avoidance channel 63 is a distance of several wavelengths extending from the edge of the target obstacle 300 to its rear, rather than filling the entire microfluidic device 1.

[0039] It needs to be further explained that, such as Figure 4 As shown, since the surface acoustic wave transducer 3 is positioned below the microfluidic device 1, the background sound field excited by the surface acoustic wave transducer 3 propagates roughly along the vertical direction into the microfluidic device 1, that is, the propagation direction of the background sound field is perpendicular to the horizontal plane in the vertical direction. Before determining the background sound field excited by the surface acoustic wave transducer 3 based on the target obstacle, it is necessary to pre-adjust the preset distance L between the surface acoustic wave transducer 3 and the microfluidic device 1 in the vertical direction. This preset distance allows the near-field region of the background sound field excited by the surface acoustic wave transducer 3 to cover the target liquid environment in the microfluidic device, thereby ensuring that the background sound field still has a stable phase distribution and sound pressure gradient when it propagates to the target obstacle location. The surface acoustic wave transducer 3 has a defined sound field wavelength excitation range when it is factory-set, and the sound field wavelength excitation range of the surface acoustic wave transducer 3 is...

[0040] The surface acoustic wave transducer 3 is factory-set with a defined sound field wavelength excitation range (or a single operating wavelength can be selected according to the obstacle size) and a fixed effective acoustic aperture A. The distance from the sound source location of the background sound field excited by the surface acoustic wave transducer 3 to the near-field boundary is the Rayleigh distance. In order to ensure that the near-field region of the background sound field excited by the surface acoustic wave transducer 3 covers the target liquid environment in the microfluidic device, the preset distance L between the surface acoustic wave transducer and the microfluidic device 1 must be less than the Rayleigh distance. .

[0041] The surface acoustic wave transducer 3 has a fixed effective acoustic aperture A at the factory setting, which, combined with its pre-configured acoustic field wavelength excitation range, is... The upper limit of the preset distance L can be obtained. Specific methods include simulation analysis, obtaining it from hardware design parameters, and formula derivation. No specific method is specified here; the following explanation focuses on the formula derivation: Let A be the effective acoustic aperture of the surface acoustic wave transducer, and L be the preset distance between the surface acoustic wave transducer and the microfluidic device in the vertical direction. The physical meaning of L is: the distance between the top wall of the cavity that constitutes the target liquid environment in the microfluidic device and the surface acoustic wave transducer.

[0042] To ensure that the target obstacle is located within the effective near-field coupling region of the background sound field, the following conditions must be met: ; According to the Rayleigh distance formula in acoustics, we can obtain: .

[0043] therefore, .

[0044] See Figure 7 and Figure 11 The drive device 4 is connected to the surface acoustic wave transducer 3. The drive device 4 drives the horizontal movement of the surface acoustic wave transducer 3, causing the modulated acoustic pressure obstacle avoidance channel 63 formed in the target liquid environment 400 to perform controlled movement. This, in turn, drives the microrobot 200 to perform obstacle avoidance actions via the obstacle avoidance potential well array. Since the acoustic pressure obstacle avoidance channel 63 originates from the coupling between the background sound field 61 and the obstacle, as the background sound field 61 moves along with the surface acoustic wave transducer 3, the spatial position of the acoustic pressure obstacle avoidance channel 63 also moves synchronously, thereby driving the microrobot 200 to perform obstacle avoidance actions along a path that bypasses the target obstacle 300.

[0045] It should be further explained that when the surface acoustic wave transducer 3 moves as a whole, the relative position of the background sound field 61 and the target obstacle 300 changes, and the sound field will naturally recouple and remodulate, forming a sound pressure obstacle avoidance channel 63 that bypasses the obstacle again under the new relative position. The recoupling and modulation process is an adaptive process.

[0046] The term "driving microrobot 200 to perform obstacle avoidance action" here means that when microrobot 200 is at its original position, it is affected by the sound radiation restoring force due to its deviation from the sound pressure node of the obstacle avoidance potential energy trap array, and is automatically pulled back into the moved obstacle avoidance potential energy trap, thereby following the sound field.

[0047] Understandably, the preset distance between the surface acoustic wave transducer 3 and the microfluidic device 1 determines the range of target obstacles that the microrobot adaptive obstacle avoidance system 100 can avoid from the hardware level, while the wavelength calculation module determines a specific wavelength within the above range from the real-time operation level.

[0048] See Figure 3 In a specific application scenario, the preset motion path of the microrobot 200 is along the positive X-axis direction (e.g., Figure 3 The target obstacle 300 (indicated by the X-axis arrow) is located on the preset motion path of the microrobot 200. The width of the target obstacle 300 in the direction perpendicular to the X-axis (i.e., the Y-axis direction) is W (characteristic dimension). The image acquisition module 2 captures the target obstacle 300 and obtains the first image information. Based on the first image information, the characteristic dimension of the target obstacle 300, i.e., the width W, can be obtained. The wavelength calculation module determines a background sound field wavelength λ based on the characteristic dimension W of the target obstacle 300. The surface acoustic wave transducer 3 excites a background sound field 61 with wavelength λ. When the background sound field 61 encounters an obstacle with a width of W, it diffracts, forming at least two sound pressure obstacle avoidance channels 63 around the target obstacle 300. The at least two sound pressure obstacle avoidance channels 63 bend and converge on both sides of the obstacle, thus avoiding the area occupied by the obstacle. Due to sound wave refraction, a sequence of sound pressure nodes appears within the sound pressure obstacle avoidance channels 63, forming an obstacle avoidance potential well array. The microrobot 200 rests within an obstacle avoidance potential energy well 64 of the obstacle avoidance potential well array. Subsequently, the drive device 4 moves the surface acoustic wave transducer 3 as a whole (e.g., along the positive X-axis), and the sound pressure obstacle avoidance channel 63 and the obstacle avoidance potential well array move synchronously, thus propelling the microrobot 200 to move along the X-axis. Since the sound pressure obstacle avoidance channel 63 is designed to bypass obstacles, the microrobot 200 naturally avoids obstacles during its movement without requiring additional path planning.

[0049] The microrobot adaptive obstacle avoidance system 100 according to an embodiment of the present invention has at least the following beneficial effects: The background sound field wavelength is determined by the characteristic dimensions of the target obstacle 300, so that the background sound field 61 can form a sound pressure obstacle avoidance channel 63 that bypasses the target obstacle 300 under the modulation of the target obstacle 300. Thus, the microrobot 200 is located in the obstacle avoidance potential well array of the sound pressure obstacle avoidance channel 63 under the action of sound pressure potential energy. By moving the surface acoustic wave transducer 3, the sound pressure obstacle avoidance channel 63 formed after modulation by the target obstacle 300 in the target liquid environment 400 is made to perform controlled movement. Then, the obstacle avoidance potential well array drives the microrobot 200 to perform obstacle avoidance action. Thus, the microrobot 200 can adaptively bypass the target obstacle 300 in the target liquid environment 400, improving the reliability of operation in complex environments.

[0050] Example 2 This embodiment is basically the same as Embodiment 1, except that the position deviation of the microrobot 200 during its movement is compensated by the image acquisition module 2 and the position compensation control module.

[0051] like Figure 12As shown, the image acquisition module 2 is further configured to continuously acquire multiple first actual position information of the microrobot 200 in the target liquid environment 400 at a first preset frame rate. The first preset frame rate refers to the image acquisition module 2 continuously capturing images at fixed time intervals (e.g., 0.02 seconds to 0.1 seconds per frame, specifically set according to the movement speed of the microrobot 200 and system response requirements), and extracting the actual coordinate values ​​of the microrobot 200 in the coordinate system of the microfluidic device 1 from each frame image. The multiple first actual position information constitute the actual movement trajectory of the microrobot 200 as time changes.

[0052] The microrobot adaptive obstacle avoidance system 100 also includes a position compensation control module, which is communicatively connected to the image acquisition module 2 and the drive device 4, and is configured to perform the following operations: The first actual position information is compared with the expected position information corresponding to the preset motion trajectory of the microrobot 200, and the position deviation of the microrobot 200 is calculated based on the comparison result.

[0053] The preset motion trajectory can be a pre-planned path, such as moving in a straight line in a certain direction or moving along a specific curve. The expected position information refers to the position coordinates that the microrobot 200 should theoretically reach at the same time point or in the same motion phase. Position deviations include, but are not limited to, forward and backward deviations (i.e., lag or advance) along the direction of motion and lateral deviations perpendicular to the direction of motion.

[0054] Based on the positional deviation, the control drive device 4 drives the surface acoustic wave transducer 3 to move in the direction and / or speed, so as to adjust the moving direction and / or speed of the sound pressure obstacle avoidance channel 63.

[0055] Specifically, when the actual position of the microrobot 200 lags behind the desired position (e.g., the position deviation indicates that the microrobot 200 is lagging behind the preset trajectory by a certain distance), the position compensation control module can control the drive device 4 to appropriately increase the moving speed of the surface acoustic wave transducer 3, so that the sound pressure obstacle avoidance channel 63 moves forward at a faster speed, thereby driving the microrobot 200 to accelerate and catch up with the desired position; conversely, when the microrobot 200 is ahead of the desired position, the moving speed of the surface acoustic wave transducer 3 can be reduced, so that the microrobot 200 decelerates. When a lateral deviation of the microrobot 200 from the preset trajectory is detected (e.g., the actual position is to the left of the desired trajectory), the position compensation control module can control the drive device 4 to adjust the moving direction of the surface acoustic wave transducer 3, so that the sound pressure obstacle avoidance channel 63 generates a corresponding lateral component, guiding the microrobot 200 back to the preset trajectory.

[0056] Through the aforementioned closed-loop position compensation control, while driving the microrobot 200 to perform adaptive obstacle avoidance actions, the position error caused by factors such as sound field disturbance, liquid flow, and irregular reflection of obstacles can be corrected in real time. This enables the microrobot 200 to move more reliably in the liquid environment 400 according to the desired preset motion trajectory, and at the same time, to more reliably bypass the target obstacle 300.

[0057] It should be noted that the first preset frame rate, the calculation method of position deviation (such as proportional control, proportional-integral control, etc.), and the speed / direction adjustment strategy of the drive device 4 can all be preset or adjusted online according to the actual application scenario, and the present invention does not limit them.

[0058] Based on this embodiment, a specific implementation of the position compensation control module is further provided. In this example, the image acquisition module 2 continuously acquires images within the liquid environment 400 at a first preset frame rate; the position compensation control module is communicatively connected to the image acquisition module 2 and the driving device 4, and performs closed-loop feedback control. Specifically: Image acquisition module 2 continuously acquires microscopic images at a fixed frame rate (this frame rate is preset according to the expected movement speed of the microrobot 200, ensuring that the movement distance of the microrobot 200 between two adjacent frames does not exceed one potential well spacing). The image processing unit in the position compensation control module performs the following operations sequentially on each frame: contrast enhancement, filtering and denoising, adaptive threshold segmentation, and contour detection. Contours corresponding to the microrobot 200 are selected based on a preset pixel area range, and their centroid coordinates are calculated as the first actual position information of the microrobot 200. If contour detection fails due to image blurring or occlusion, a pre-trained target detection model is invoked for secondary recognition, and the center of the detection box is taken as the current position coordinates. It should be noted that the above specific algorithm is only an example, and this system does not limit the specific implementation of the visual analysis method.

[0059] The position compensation control module internally stores or generates in real time the preset motion trajectory of the microrobot 200. The preset motion trajectory consists of a series of target points arranged in a time sequence. The distance between adjacent target points can be a preset fixed distance or dynamically interpolated based on the desired motion speed. Within each control cycle, the desired position information at the current moment is obtained from the preset motion trajectory through linear interpolation based on the current running time. Subsequently, the position compensation control module calculates the Euclidean distance between the desired position and the first actual position information as the position deviation; simultaneously, it calculates the angle between the direction vector from the desired position to the next target point and the direction vector from the actual position to the actual motion direction as the direction deviation.

[0060] The position compensation control module employs a proportional-integral-derivative (PI-DI) control algorithm. Taking the aforementioned position deviation (and direction deviation) as input, it performs proportional, integral, and derivative operations to generate a compensation speed command. This command is sent to the drive device 4 via a communication interface. Based on the received speed and direction commands, the drive device 4 drives the surface acoustic wave transducer 3 to move at the corresponding speed and direction. As the surface acoustic wave transducer 3 moves, the background sound field 61 in the target liquid environment 400 shifts as a whole, and the sound pressure obstacle avoidance channel 63 modulated by the target obstacle 300 and its associated obstacle avoidance potential well array also synchronously change their spatial position.

[0061] The microrobot 200, having deviated from the sound pressure node of the obstacle avoidance potential well array at its original position, is automatically pulled back into the moved potential well due to the restoring force of sound radiation, thus following the sound field. This process continuously cycles with a fixed control period: the image acquisition module 2 continuously updates the microrobot 200's initial actual position information, the position compensation control module corrects deviations in real time and outputs new compensation commands, and the drive device 4 continuously adjusts the transducer's motion parameters. This forms a closed-loop feedback loop of perception, calculation, and execution until the microrobot 200 completes all predetermined movements according to the preset trajectory and simultaneously performs adaptive obstacle avoidance actions upon encountering the target obstacle 300.

[0062] The proportional-integral-derivative (PID) control algorithm and its parameters (proportional coefficient, integral time, derivative time) used in this example can be pre-tuned or adaptively adjusted online according to the specific application scenario. The high-precision displacement stage can be a piezoelectric ceramic displacement stage, a stepper motor displacement stage, or a voice coil motor displacement stage, as long as it can receive speed / direction commands and drive the surface acoustic wave transducer 3 to move. This invention does not limit the specific control parameters or the type of displacement stage.

[0063] Example 3 This embodiment is basically the same as Embodiment 1, except that the driving device 4 is triggered when the microrobot 200 is stably stationary by the image acquisition module 2 and the stability determination module.

[0064] like Figure 13 As shown, the image acquisition module 2 is further configured to continuously acquire multiple second actual position information of the microrobot 200 in the target liquid environment 400 at a second preset frame rate. It should be noted that the second preset frame rate can be the same as or different from the aforementioned first preset frame rate, and is specifically preset according to the response speed requirements for stability determination; this invention does not impose any limitations on this.

[0065] The microrobot adaptive obstacle avoidance system 100 also includes a stability determination module. The stability determination module is communicatively connected to the image acquisition module 2 and the drive device 4, respectively. The stability determination module is configured to perform the following operations: The image acquisition module 2 continuously acquires multiple second actual position information at a second preset frame rate. For any two adjacent second actual position information, the displacement between them is calculated. This displacement reflects the actual movement distance of the microrobot 200 within that time interval.

[0066] The displacement is compared with a preset stability threshold. The preset stability threshold is a pre-set distance value. When the displacement is less than or equal to this threshold, it is considered that the microrobot 200 has not moved significantly during that time period.

[0067] The stability determination module continuously monitors changes in displacement. When multiple consecutive displacement values ​​(i.e., multiple consecutive adjacent sampling intervals) are all below the preset stability threshold, and this low displacement state lasts for a preset stabilization time, the stability determination module determines that the microrobot 200 has reached a stable dwell state.

[0068] like Figure 4 As shown, the stable dwell state means that the microrobot 200 has been firmly captured at a certain position by the periodic potential energy trap of the periodic potential energy trap array or the obstacle avoidance potential energy trap 64 of the obstacle avoidance potential energy trap array, and no longer undergoes obvious spontaneous displacement.

[0069] After determining that the microrobot 200 has reached a stable stationary state, the stability determination module sends a trigger signal to the drive device 4. In response to this trigger signal, the drive device 4 begins to drive the surface acoustic wave transducer 3 to move. In this way, the transducer's movement is only initiated when the microrobot 200 is in a stable stationary state, thus avoiding detachment or loss of control caused by forcibly dragging the microrobot 200 before it has stabilized.

[0070] It should be noted that the specific values ​​of the second preset frame rate, preset stability threshold, and preset stability time can be pre-calibrated or adjusted online according to the size of the micro-robot 200, the viscosity of the liquid environment 400, the sound field intensity, and the actual application scenario. This invention does not limit these values. Furthermore, the stability determination module can coexist with the aforementioned position compensation control module, with each functioning at different stages or under different conditions: the position compensation control module is used for trajectory tracking correction during motion, while the stability determination module is used for conditional triggering at the start of motion or during motion intervals.

[0071] Example 4 This embodiment is basically the same as Embodiment 1, except that the specific mapping relationship between the wavelength of the background sound field 61 and the characteristic size of the target obstacle 300 is different.

[0072] Furthermore, the wavelength calculation module is specifically configured to determine the wavelength of the background sound field 61, such that the ratio of the feature size of the target obstacle 300 to the wavelength of the background sound field 61 in the target liquid environment 400 is between 1 / 4 and 1 / 2.

[0073] Specifically, let the wavelength of the background sound field be... Let the size of the target obstacle be... ,therefore: ,Right now In other words, the background sound field wavelength is preferably 2 to 4 times the feature size of the target obstacle. When multiple wavelengths are available within the above range, the wavelength calculation module preferably selects: λ=3D, as the nominal wavelength of the background sound field, so that the size matching relationship is located in the middle region of 1 / 4 to 1 / 2, thereby improving the system's tolerance to obstacle size errors, image recognition errors and operating frequency drift.

[0074] In this embodiment of the invention, the formation of the sound pressure obstacle avoidance channel 63 depends on the matching relationship between the characteristic size of the target obstacle 300 and the wavelength of the background sound field. Theoretical analysis and experimental verification show that when the ratio of the characteristic size to the wavelength of the background sound field 61 in the target liquid environment 400 is between 1 / 4 and 1 / 2 (i.e., the wavelength calculation module determines the background sound field wavelength according to the aforementioned preferred range), the scattered field 62 and the background sound field 61 can achieve stable coupling, forming a continuous sound pressure gradient channel around the target obstacle 300. The extension direction of this channel is basically consistent with the propagation direction of the background sound field 61, and the width of the channel is positively correlated with the characteristic size of the target obstacle 300. By adjusting the operating frequency of the surface acoustic wave transducer 3 (thus changing the background sound field wavelength) or according to the actual obstacle's characteristic size, the shape of the sound pressure obstacle avoidance channel 63 can be designed or adaptively formed as needed.

[0075] Within a certain fluctuation range of the aforementioned preferred ratio range (1 / 4 to 1 / 2), the sound pressure obstacle avoidance channel 63 still exists. For example, when the characteristic size of the target obstacle 300 changes to a certain extent relative to the nominal value of this ratio range (such as increasing or decreasing by a certain preset percentage), or when the background sound field wavelength changes accordingly due to a slight drift in the system's operating frequency, the sound pressure obstacle avoidance channel 63 will not disappear. Only its width and geometric features such as the radius of curvature for bypassing obstacles will change to a limited extent, but these changes do not affect the basic function of the microrobot 200 in performing obstacle avoidance actions along the channel. In other words, the adaptive obstacle avoidance system has a certain tolerance for the matching accuracy of the ratio of obstacle size to wavelength. This tolerance range can be determined through pre-calibration or acoustic simulation, and the present invention does not specifically limit it.

[0076] It should be noted that in some examples, when the characteristic size of the target obstacle exceeds the operating frequency of the surface acoustic wave transducer 3, that is, when the surface acoustic wave transducer 3 does not have a wavelength that meets the conditions, the problem can be solved by replacing it with a surface acoustic wave transducer with a larger effective acoustic aperture A, or by readjusting the operating frequency of the surface acoustic wave transducer 3.

[0077] Example 5 like Figure 1 , Figure 2 and Figure 9 As shown, the microrobot adaptive obstacle avoidance system 100 further includes a fluid membrane 5 disposed between the microfluidic device 1 and the surface acoustic wave transducer 3. A certain amount of fluid is dripped onto the upper surface of the surface acoustic wave transducer 3; then, the microfluidic device 1 is placed above the surface acoustic wave transducer 3, and the lower surface of the microfluidic device 1 is brought into contact with the dripped fluid; by applying appropriate pressure, the microfluidic device 1 is pressed downward, and the dripped fluid is squeezed and spread between the lower surface of the microfluidic device 1 and the upper surface of the surface acoustic wave transducer 3, forming a continuous and uniformly thick fluid membrane 5. By setting the fluid membrane 5 as an acoustic wave coupling medium, the acoustic waves excited by the surface acoustic wave transducer 3 can be more efficiently transmitted to the liquid environment 400 inside the microfluidic device 1, while reducing the total reflection loss of acoustic waves caused by air gaps.

[0078] Further, the driving device includes a fixed base 40, a first movable base 41, a locking mechanism 44, a second movable base 42, and a moving platform 43. The fixed base 40 is provided with a first guide rail 401 that is inclined relative to the first direction and the vertical direction; the first movable base 41 is slidably mounted on the first guide rail 401; the locking mechanism 44 includes a locking pin (not shown in the figure), a first locking hole 411 provided on the first guide rail 401, and a second locking hole 442 provided on the first movable base 41. The locking pin passes through both the first locking hole 411 and the second locking hole 412 to lock the relative position of the fixed base 40 and the first movable base 41; the second movable base 42 is movably mounted on the first movable base 41 along the second direction; the moving platform 43 is fixedly mounted on the second movable base 42 and has a mounting surface 431 that extends in the horizontal direction. The mounting surface 431 is fixedly connected to the surface acoustic wave transducer; wherein the first direction and the second direction are perpendicular, and both the first direction and the second direction are parallel to the horizontal direction.

[0079] Specifically, the fixed base 40 is provided with a first guide rail that is inclined relative to the first direction and the vertical direction, and the first movable base 41 is disposed on the first guide rail. As can be seen from the above embodiment, the microfluidic device 3 is pressed above the surface acoustic wave transducer 3. When the first movable base 41 is driven to move along the first guide rail, the preset distance between the microfluidic device and the surface acoustic wave transducer 3 can be adjusted so that the microfluidic device is located in the near field region of the background sound field excited by the surface acoustic wave transducer. Then, the locking pin is inserted into the lock hole to lock the relative position between the surface acoustic wave transducer and the first guide rail. Then, the second movable base is driven to move the moving platform horizontally along the second direction, thereby driving the relative position of the surface acoustic wave transducer and the microfluidic device to change in the second direction.

[0080] Example 6 like Figure 11 As shown, a second aspect of the present invention provides an adaptive obstacle avoidance method for a microrobot 200, applied to the microrobot adaptive obstacle avoidance system 100 of the first aspect of the present invention, comprising: S1: The image acquisition module 2 acquires first image information of the target liquid environment 400 where the microrobot 200 is located. The first image information includes the feature dimensions of the target obstacle 300. This step is used to obtain the feature dimensions of the target obstacle 300, providing a basis for subsequent wavelength calculation. S2: The background sound field wavelength is determined based on the characteristic dimensions using the wavelength calculation module; S3: A background sound field 61 with a background sound field wavelength is excited in the target liquid environment 400 by the surface acoustic wave transducer 3. The background sound field 61 is modulated by the target obstacle 300 to form a sound pressure obstacle avoidance channel 63 that bypasses the target obstacle 300. The sound pressure in the sound pressure obstacle avoidance channel 63 is periodically distributed to form an obstacle avoidance potential well array. S4: Drive the horizontal movement of the surface acoustic wave transducer 3 through the drive device 4 so that the sound pressure obstacle avoidance channel 63 formed after modulation in the target liquid environment 400 performs controlled movement, and then drive the micro-robot 200 to perform obstacle avoidance through the obstacle avoidance potential well array.

[0081] The background sound field wavelength is determined by the characteristic dimensions of the target obstacle 300, so that the background sound field 61 can form a sound pressure obstacle avoidance channel 63 that bypasses the target obstacle 300 under the modulation of the target obstacle 300. Thus, the microrobot 200 is located in the obstacle avoidance potential well array of the sound pressure obstacle avoidance channel 63 under the action of sound pressure potential energy. By moving the surface acoustic wave transducer 3, the sound pressure obstacle avoidance channel 63 formed after modulation by the target obstacle 300 in the target liquid environment 400 is made to perform controlled movement. Then, the obstacle avoidance potential well array drives the microrobot 200 to perform obstacle avoidance action. Thus, the microrobot 200 can adaptively bypass the target obstacle 300 in the target liquid environment 400, improving the reliability of operation in complex environments.

[0082] like Figure 12 As shown, S4 further drives the movement of the surface acoustic wave transducer 3 via the driving device 4, and includes the following sub-steps: The image acquisition module 2 acquires multiple first actual position information of the microrobot 200 in the target liquid environment 400, which is continuously acquired at a first preset frame rate. The position compensation control module compares the first actual position information with the expected position information corresponding to the preset motion trajectory of the microrobot 200, and calculates the position deviation of the microrobot 200. Based on the positional deviation, the driving device 4 is controlled by the compensation control module to control the moving direction and / or moving speed of the surface acoustic wave transducer 3, so as to adjust the moving direction and / or moving speed of the sound pressure obstacle avoidance channel 63.

[0083] like Figure 13 As shown, further, between S3 and S4, the following steps are also included: Multiple second actual position information of the microrobot 200 in the target liquid environment 400 are continuously acquired by the image acquisition module 2 at a second preset frame rate; The displacement between any two adjacent second actual position information is calculated by the stability determination module; When the displacement is continuously lower than the preset stability threshold for a preset stability time, it is determined that the microrobot 200 has reached a stable dwell state, and the drive device 4 is triggered by the stability determination module to drive the surface acoustic wave transducer 3 to move.

[0084] Furthermore, the background sound field wavelength is determined based on the feature size using the wavelength calculation module, including: determining the background sound field wavelength such that the ratio of the feature size of the obstacle to the wavelength of the background sound field 61 in the target liquid environment 400 is between 1 / 4 and 1 / 2.

[0085] The following is combined Figures 1-13 Describe a specific example.

[0086] like Figure 1 , Figure 2 and Figure 9 As shown, the microfluidic device 1 includes a microfluidic device body 12 and a clamp 11. The clamp 11 is used to fix the microfluidic device body 12, and the top of the clamp 11 is provided with a clearance structure. On a projection plane perpendicular to the vertical direction, the projection of the clearance structure on the projection plane covers the projection of the microfluidic device body 12 on that projection plane. The microfluidic device body 12 includes, from top to bottom, a channel top 121, a channel base 122, and a channel sidewall. The channel top 121 and the channel base 122 are arranged opposite to each other and spaced apart. The channel sidewall connects the channel top 121 and the channel base 122. The channel sidewall, channel top 121, and channel base 122 enclose a channel, which forms a target liquid environment 400 after being filled with a liquid medium. The channel top 121 is made of borosilicate glass, which forms an acoustic impedance mismatch interface with the microfluidic environment, enhancing sound wave reflection to form a standing wave resonance.

[0087] like Figure 10 As shown, the internal height of the flow channel is 400 micrometers, and a target obstacle 300 (such as a cylindrical column with a diameter of approximately 50-80 μm and a height matching the flow channel height) is pre-set to simulate the obstacle environment that may be encountered in actual applications. When the background sound field 61 excited by the surface acoustic wave transducer 36 propagates to the obstacle, reflection and refraction occur, generating a scattered field 62. The scattered field 62 couples with the background sound field 61 to form a local sound field with topological protection characteristics. This local sound field can guide the microrobot 200 to automatically bypass the obstacle, achieving adaptive obstacle avoidance. The micro-obstacle is 3D printed on the spacer layer in the device fixture 11, exhibiting good compatibility with biological samples.

[0088] like Figure 1 and Figure 2 As shown, the image acquisition module 2 includes an industrial camera 21 and an optical tube 22. One end of the optical tube 22 is located above the fixture 11, and the industrial camera 21 is connected to the other end of the optical tube 22. The top of the fixture 11 is provided with a clearance structure, through which the detection optical paths of the industrial camera 21 and the optical tube 22 extend into the target liquid environment 400 inside the microfluidic device body 12.

[0089] like Figure 1 and Figure 2As shown, the driving device includes a fixed base 40, a first movable base 41, a locking mechanism 44, a second movable base 42, and a moving platform 43. The fixed base 40 is provided with a first guide rail 401 inclined relative to a first direction and a vertical direction; the first movable base 41 is slidably mounted on the first guide rail 401; the locking mechanism 44 includes a locking pin (not shown), a first locking hole 411 on the first guide rail 401, and a second locking hole 442 on the first movable base 41. The locking pin passes through both the first locking hole 411 and the second locking hole 412 to lock the relative positions of the fixed base 40 and the first movable base 41; the second movable base 42 is movably mounted on the first movable base 41 along a second direction; the moving platform 43 is fixedly mounted on the second movable base 42 and has a mounting surface 431 extending horizontally, with the mounting surface 431 fixedly connected to a surface acoustic wave transducer; wherein the first direction and the second direction are perpendicular, and both the first direction and the second direction are parallel to the horizontal direction. By moving the surface acoustic wave transducer through the drive device 4, the microrobot 200 can be driven to achieve various motion forms such as translation, rotation, and aggregation.

[0090] For example, when there are multiple microrobots 200 in the target liquid environment 400, at least two microrobots 200 can be located in the same obstacle avoidance potential energy trap 64 of the obstacle avoidance potential energy array or the same periodic potential energy trap in the periodic potential energy trap array under the action of acoustic potential energy to form a microrobot cluster 210.

[0091] The surface acoustic wave transducer 3 includes a piezoelectric material 31, a guide wire 32, electrodes 33, and a standing wave transducer 34. The piezoelectric material 31 is made of a 128° Y-cut lithium niobate wafer, which has the characteristics of high sound velocity and high electromechanical coupling coefficient. A four-port delay line structure standing wave transducer 34 is fabricated on the surface of the piezoelectric material 31 by photolithography and metal deposition processes. The period of its interdigitated electrodes 33 corresponds to the operating frequency of 9MHz, and the finger width and finger spacing are designed according to the sound wave wavelength. The electrodes 33 are connected to an external signal generator through the guide wire 32 for inputting a sinusoidal drive signal. The standing wave transducer 34 is arranged in a bisymmetrical manner on the piezoelectric material 31, which can form a stable standing wave field distribution and generate periodic sound pressure nodes and anti-nodes in the central region.

[0092] A fluid membrane 5 is provided between the microfluidic device 1 and the surface acoustic wave transducer 3.

[0093] In this specific application scenario, the feature size of the target obstacle 300 has been obtained by the image acquisition module 2, and the wavelength of the background sound field 61 has been determined by calculation.

[0094] Furthermore, the signal generator is turned on, outputting a sine wave signal with a frequency of 9MHz and a peak voltage of 3V. After being amplified by the power amplifier, the signal is input to the surface acoustic wave transducer 3. The frequency fine-tuning knob is adjusted to bring the system to the optimal resonance state. At this time, a stable localized sound pressure obstacle avoidance channel 63 is formed in the microfluidic device 1 containing the target obstacle 300. The microrobot 200 suspension is injected into the liquid environment 400. Under the influence of the background sound field 61, the microrobot 200 migrates towards the sound pressure node driven by the sound radiation force, and is eventually captured and locked in the periodic potential energy trap of the periodic potential trap array. Observation through the industrial camera 21 confirms that the microrobot 200 has stably stopped at the predetermined starting position. The entire process takes about 10-30 seconds.

[0095] The surface acoustic wave transducer 3 is controlled by the drive device 4 to move along the positive X-axis at a set speed (100 μm / s in this embodiment). The surface acoustic wave transducer 3 moves synchronously with the drive device 4, and the sound pressure obstacle avoidance channel 63 translates as a whole. The microrobot 200 is subjected to a restoring force due to its deviation from the center of the periodic potential energy trap, and moves along with the periodic potential energy trap array. The position of the microrobot 200 is recorded in real time through image feedback, and the deviation between the actual movement speed and the set speed is calculated.

[0096] When the microrobot 200 moves to approximately 30 μm in front of the target obstacle 300, the sound wave energy automatically bypasses the obstacle 300 due to guidance, forming a sound pressure obstacle avoidance channel 63 around the obstacle 300. Under the influence of sound radiation force, the microrobot 200 follows the sound pressure obstacle avoidance channel 63, bypassing the obstacle 300 before continuing to move forward following the periodic potential well array. No external intervention is required throughout the entire process. The obstacle avoidance process is recorded by an industrial camera 21, measuring the minimum distance between the bypass trajectory and the obstacle. In this embodiment, the minimum distance is measured to be approximately 30 μm.

[0097] Industrial camera 211 continuously acquires position images of microrobot 200 at a rate of 30 frames per second and extracts centroid coordinates. The actual coordinates are compared with a preset trajectory to calculate the position deviation. When the deviation exceeds 10 μm, the movement speed of drive device 4 is automatically adjusted to bring microrobot 200 back to the predetermined trajectory. In this embodiment, within a travel range of 18000 μm, the maximum trajectory deviation is less than 8 μm, and the average deviation is approximately 4 μm.

[0098] The above fully describes the composition of the microrobot adaptive obstacle avoidance system 100 and the adaptive obstacle avoidance method of the microrobot 200 of the present invention. Specifically, it includes the structure and connection relationship of each component of the system, the excitation and control of the surface acoustic wave transducer 3, the spatial scattering coupling effect of micro-obstacles on the sound field, the formation mechanism of the localized sound pressure guiding channel, and the basic operation process of the microrobot 200 adaptive obstacle avoidance and trajectory closed-loop correction based on sound field translation drive. Through the above embodiments, the present invention realizes the basic function of the microrobot 200 automatically avoiding obstacles in complex microfluidic environments without external intervention.

[0099] In summary, this invention utilizes the scattering coupling effect between the background sound field 61 in a movable surface acoustic wave system and microscopic obstacles in the environment to form a localized sound pressure guidance channel, achieving for the first time the adaptive obstacle avoidance function of a microrobot 200 in a complex microfluidic environment. Experimental results show that this invention can drive the microrobot 200 to complete continuous motion along a path containing obstacles, covering a distance of centimeters, with motion errors controlled within 20 micrometers, an obstacle avoidance success rate exceeding 85%, and the ability to selectively capture and tow microscale targets. The system structure of this invention is simple, highly compatible with existing microfluidic processes, and has broad application prospects in cell manipulation, micro / nano assembly, targeted delivery, and environmental sensing.

[0100] It should be emphasized that the present invention has the following technical effects: First, this invention achieves adaptive obstacle avoidance for the microrobot 200, overcoming the limitations of traditional methods that rely on built-in microstructures or complex signal modulation. When the background sound field 61 encounters an obstacle, the resulting scattered field 62 couples with the background field to form a local sound field with topological protection characteristics, enabling sound wave energy to automatically bypass the obstacle and propagate along a predetermined path. This endows the microrobot 200 with the ability to autonomously avoid obstacles, significantly improving the reliability of manipulation in complex environments.

[0101] Second, the present invention achieves the driving of the microrobot 200 by overall translation of the sound field, which breaks through the limitation of the traditional sound aperture on the range of motion, while maintaining the micron-level motion accuracy. Experimental results show that the microrobot 200 can complete continuous motion with a millimeter-level stroke on a complex path containing multiple obstacles, and the motion error is controlled within 20 micrometers.

[0102] Third, this invention integrates visual feedback and closed-loop control modules, enabling real-time monitoring and dynamic correction of the movement of the micro-robot 200. It can automatically adjust the movement strategy according to environmental changes, providing a complete technical solution for automated micro-manipulation.

[0103] Fourth, the system structure of this invention is simple, compatible with existing microfluidic chip processing technology, has controllable manufacturing costs, and is easy to achieve mass production and widespread application. It has broad application prospects in cell manipulation, micro-nano assembly, targeted delivery, environmental sensing and other fields.

[0104] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention. Furthermore, the embodiments of the present invention and the features thereof can be combined with each other unless otherwise specified.

Claims

1. A microrobot adaptive obstacle avoidance system, characterized in that, include: A microfluidic device for providing a target liquid environment; An image acquisition module is disposed above the microfluidic device; wherein, the image acquisition module is configured to acquire first image information reflecting the activity of the microrobot in the target liquid environment, the first image information including the feature dimensions of target obstacles in the target liquid environment; A wavelength calculation module, which is communicatively connected to the image acquisition module, is configured to determine the background sound field wavelength based on the feature size. A surface acoustic wave transducer, communicatively connected to the wavelength calculation module, is positioned below the microfluidic device and at a predetermined vertical distance from the microfluidic device. It is configured to excite a background sound field with a background sound field wavelength in a target liquid environment. The predetermined distance is configured such that the microfluidic device is located in the near-field region of the background sound field excited by the surface acoustic wave transducer. The background sound field, after being modulated by a target obstacle, forms a sound pressure obstacle avoidance channel that bypasses the target obstacle. The sound pressure within the sound pressure obstacle avoidance channel is periodically distributed to form an obstacle avoidance potential well array. A driving device is connected to the surface acoustic wave transducer; wherein, the driving device drives the horizontal movement of the surface acoustic wave transducer so that the acoustic pressure obstacle avoidance channel formed after modulation in the target liquid environment performs controlled movement, and then drives the microrobot to perform obstacle avoidance actions through the obstacle avoidance potential well array.

2. The microrobot adaptive obstacle avoidance system according to claim 1, characterized in that, The image acquisition module is also configured to continuously acquire multiple first actual position information of the microrobot in the target liquid environment at a first preset frame rate; The microrobot adaptive obstacle avoidance system also includes a position compensation control module, which is communicatively connected to the image acquisition module and the driving device, and is configured to: compare the first actual position information with the expected position information corresponding to the preset motion trajectory of the microrobot, and calculate the position deviation of the microrobot; Based on the positional deviation, the driving device is controlled to drive the surface acoustic wave transducer to move in the direction and / or speed, so as to adjust the moving direction and / or speed of the sound pressure obstacle avoidance channel.

3. The microrobot adaptive obstacle avoidance system according to claim 1, characterized in that, The image acquisition module is also configured to continuously acquire multiple second actual position information of the microrobot in the target liquid environment at a second preset frame rate; The microrobot adaptive obstacle avoidance system also includes a stability determination module, which is communicatively connected to the image acquisition module and the driving device. The stability determination module is configured to: calculate the displacement between any two adjacent second actual position information; when the displacement is continuously lower than a preset stability threshold for a preset stability time, determine that the microrobot has reached a stable dwell state, and trigger the driving device to drive the surface acoustic wave transducer to move.

4. The microrobot adaptive obstacle avoidance system according to claim 1, characterized in that, The wavelength calculation module is specifically configured as follows: The background sound field wavelength is determined such that the ratio of the characteristic size of the obstacle to the wavelength of the background sound field in the target liquid environment is between 1 / 4 and 1 / 2.

5. The microrobot adaptive obstacle avoidance system according to claim 1, characterized in that, The microrobot adaptive obstacle avoidance system also includes a fluid membrane disposed between the microfluidic device and the surface acoustic wave transducer.

6. The microrobot adaptive obstacle avoidance system according to claim 1, characterized in that, The driving device includes: The fixed base is provided with a first guide rail that is inclined relative to the first direction and the vertical direction; The first movable seat is slidably mounted on the first guide rail; The locking mechanism includes a locking pin, a first locking hole on the first guide rail, and a second locking hole on the first movable seat. The locking pin passes through both the first locking hole and the second locking hole to lock the relative position of the fixed seat and the first movable seat. The second movable seat is movably mounted on the first movable seat along the second direction; A mobile platform is fixedly installed on the second mobile base and has a mounting surface extending in a horizontal direction, wherein the mounting surface is fixedly connected to the surface acoustic wave transducer. Wherein, the first direction and the second direction are perpendicular, and both the first direction and the second direction are parallel to the horizontal direction.

7. A microrobot adaptive obstacle avoidance method, characterized in that, The microrobot adaptive obstacle avoidance system applied to any one of claims 1 to 6 comprises: The first image information of the target liquid environment where the microrobot is located is acquired by the image acquisition module. The first image information includes the feature size of the target obstacle. The background sound field wavelength is determined by the wavelength calculation module based on the characteristic dimensions. A background sound field with the wavelength of the background sound field is excited in the target liquid environment by a surface acoustic wave transducer. The background sound field is modulated by the target obstacle to form a sound pressure obstacle avoidance channel that bypasses the target obstacle. The sound pressure in the sound pressure obstacle avoidance channel is periodically distributed to form an obstacle avoidance potential well array. The horizontal movement of the surface acoustic wave transducer is driven by a driving device, so that the acoustic pressure obstacle avoidance channel formed after modulation in the target liquid environment performs controlled movement, and then the microrobot is driven to perform obstacle avoidance actions through the obstacle avoidance potential well array.

8. The microrobot adaptive obstacle avoidance method according to claim 7, characterized in that, The movement of the surface acoustic wave transducer driven by the driving device includes: The image acquisition module acquires multiple first actual position information of the microrobot in the target liquid environment, which are continuously acquired at a first preset frame rate; The position compensation control module compares the first actual position information with the expected position information corresponding to the preset motion trajectory of the microrobot, and calculates the position deviation of the microrobot. Based on the positional deviation, the driving device is controlled by the compensation control module to drive the surface acoustic wave transducer to move in the direction and / or speed, so as to adjust the moving direction and / or speed of the sound pressure obstacle avoidance channel.

9. The microrobot adaptive obstacle avoidance method according to claim 7, characterized in that, Before driving the movement of the surface acoustic wave transducer via a driving device, the method further includes: Multiple second actual position information of the microrobot in the target liquid environment are continuously acquired by the image acquisition module at a second preset frame rate; The stability determination module calculates the displacement between any two adjacent second actual position information. When the displacement is continuously lower than the preset stability threshold for a preset stability time, it is determined that the microrobot has reached a stable dwell state, and the driving device is triggered by the stability determination module to drive the surface acoustic wave transducer to move.

10. The microrobot adaptive obstacle avoidance method according to claim 7, characterized in that, The background sound field wavelength is determined by the wavelength calculation module based on the characteristic dimensions. This includes determining the wavelength of the background sound field such that the ratio of the characteristic size of the obstacle to the wavelength of the background sound field in the target liquid environment is between 1 / 4 and 1 / 2.

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