1074 results about "Tactile sensor" patented technology

The invention discloses a manipulator grabbing planning system and method based on visual identification, and relates to the technical field of robots, the manipulator grabbing planning system comprises a visual perception module, a coordinate conversion module, a motion planning module, a control execution module, a tail end perception module and a system integration and communication module; the visual perception module realizes multi-view target detection, semantic segmentation and three-dimensional pose estimation through a binocular depth camera; the coordinate conversion module is used for converting a target pose under a camera coordinate system into a world coordinate under a mechanical arm base coordinate system; the motion planning module is responsible for generating a mechanical arm grabbing path, optimizing a strategy and supporting generalization migration of a multi-form mechanical arm; the control execution module drives the six-axis cooperative mechanical arm to complete the grabbing action, and vision-force mixed feedback closed-loop control is achieved. The tail end sensing module monitors the grabbing state in real time through a touch sensor and dynamically adjusts a grabbing strategy; and the system integration and communication module is used for realizing real-time data interaction and cooperative work among the modules of the system.

The invention discloses a multi-modal collaborative decision-making method and device for a humanoid robot in an industrial scene, and relates to the technical field of robot control, and the method comprises the steps: obtaining a multi-frame monitoring image, force touch sensor data and equipment operation sensor data of a visual camera of the humanoid robot in the industrial scene; extracting feature vectors of the multi-frame monitoring image, the force touch sensor data and the equipment operation sensor data as multi-modal feature vectors; taking the multi-modal feature vector as a training sample to train a cross-modal model, so that the cross-modal model learns an association relationship among vision, haptic and equipment data; obtaining dynamic industrial scene data, extracting feature vectors, and inputting the feature vectors into the trained cross-modal model to generate scene description information; and outputting an operation decision instruction according to the scene description information so as to control the humanoid robot. Through cross-modal feature fusion and dynamic knowledge reasoning, the task execution precision and environmental adaptability of the humanoid robot in a complex industrial environment can be improved.

The invention relates to the technical field of robot decision making, and provides a robot multi-modal fusion autonomous decision making method and system based on a large language model.The method comprises the steps that a robot obtains multi-modal environment information through a visual sensor, a touch sensor, an auditory sensor and a laser radar which are carried by the robot; performing preliminary filtering and noise reduction processing on the original sensor data, and synchronously recording all the sensor data by timestamps; performing space-time semantic alignment on the preprocessed multi-modal data, mapping pixel coordinates of a target in a visual target coordinate quantization original image to a robot coordinate system, performing uncertainty evaluation on a multi-modal signal through a dynamic Bayesian network, and taking entropy or variance as an uncertainty quantitative evaluation index. According to the method, the information quality is improved from a data fusion source, accurate and reliable basic support is provided for subsequent decision making, and decision making errors caused by data deviation are greatly reduced.

A control method for a support robot, the method comprising: in response to recognizing that a target object has an intent to require support, controlling a support robot to move toward the target object, and when the support robot moves to a target movement position, controlling a robot arm to move to a target joint position, wherein the target movement position and the target joint position are both determined on the basis of the relative position between the target object and a target sensor; and in the process of the robot arm moving to the target joint position or after the robot arm moves to the target joint position, when it is detected by means of a tactile sensor that an external force is applied to the robot arm, performing compliance control on the support robot. Further provided are a support robot, an electronic device, a computer storage medium, and a computer program.

An optical tactile sensing method is provided distinguishing having an optical tactile sensor and performing shape reconstruction and force measurement. The optical tactile sensor has an elastomeric hemisphere. A single camera captures the illumination of the entire reflective inner surface of the elastomeric hemisphere in a single input image. Shape reconstruction for a novel shape is performed while in contact with the hemisphere. Image pixels of a single sensor input image are inputted to a trained neural network, which outputs shape characteristics of the contact of the novel shape. With a continuous pattern on the elastomeric hemisphere, the optical tactile sensing method further distinguishes performing force reconstruction / estimation. Force reconstruction / estimation is performed through tracking deformation of the continuous pattern of the elastomeric hemisphere. Multiple sensor input images collected during the deformation are inputted to a trained neural network, which outputs force vector information of the contact of the novel shape.

The invention discloses a robot hierarchical reinforcement learning variable impedance control method based on vision and touch, and belongs to the field of robot control. According to the method, an upper-layer planning system and a lower-layer variable impedance control system are included, the upper-layer planning system fuses information from a visual sensor and a tactile sensor, feature coding is conducted on a visual image through a variational self-coding model, tactile feedback and mechanical arm state information are combined, and an action strategy adapting to the current environment and corresponding impedance parameters are formulated. And the lower-layer variable impedance control system realizes variable impedance control of the robot based on a depth kinematics and dynamics model, and allows the robot to dynamically adjust the motion and contact force according to the sensed information when interacting with the environment, thereby improving the adaptability to the environment change and the task execution efficiency. According to the method, the success rate and execution efficiency of the robot for executing the complex assembly task in the unstructured environment are remarkably improved, and high robustness is shown.

The invention relates to the technical field of manipulator control, in particular to a multi-dimensional force touch sense self-adaptive grabbing dexterous hand control system and a multi-dimensional force touch sense self-adaptive grabbing dexterous hand control method. The control system comprises an upper computer, a dexterous hand master controller module, a finger controller module, a three-dimensional force tactile sensor module and an actuator module, wherein the finger controller module, the three-dimensional force tactile sensor module and the actuator module are independently configured for each finger of the dexterous hand; wherein the dexterous hand master controller receives an instruction of an upper computer and generates a control instruction corresponding to each finger; the three-dimensional force tactile sensor monitors contact data of a finger and an object; the finger controller calculates target positions of the servo motor at different time points based on the control instruction, the contact data and actuator state feedback, and generates a third control instruction; and after receiving the instruction, the actuator module adjusts the position of a servo motor to ensure that the dexterous hand completes self-adaptive grabbing according to a preset track and force. The grabbing force and speed of the dexterous hand can be adjusted in a self-adaptive mode according to different conditions, and the accuracy and stability of the grabbing action are ensured.

The invention relates to a bionic multi-finger underwater manipulator device, a control system, a grabbing strategy and a target identification method.The manipulator is mainly composed of a flange plate and an under-actuated mechanical finger of a seven-connecting-rod mechanism, and the mechanical finger comprises a base, a triangular piece, a fingertip piece and a sliding block; two corners of the triangular piece are connected with the fingertip piece and the sliding block through connecting rod mechanisms respectively, the third corner of the triangular piece is connected with the base through a trapezoidal connecting piece, the sliding block is driven by a threaded linear long-axis motor, a magnetic touch sensor is arranged in a fingertip, and the magnetic touch sensor receives fingertip touch information through a fingertip receptor unit made of a magnetic powder silica gel mixture. The device is controlled by a control system comprising a microprocessor, naturally adapts to objects with different shapes and sizes by formulating corresponding adaptive force grabbing strategies, and classifies and identifies underwater objects through a deep learning algorithm. Compared with the prior art, the method has the advantages of high sensitivity, interference resistance and the like, and has the capabilities of tactile perception recognition and self-adaptive grabbing.

The invention discloses a joint denoising method for robot visual motion prediction, and the method comprises the steps: constructing a unified generative model through fusing an image and a depth map collected by a depth camera, motion data collected by CAN line communication of a Piper mechanical arm, and a tactile image collected by a Gelsight Mini tactile sensor; the method comprises two steps of data acquisition and input coding, and joint denoising and generation: firstly, multi-modal data are coded into low-dimensional potential representation, and then future images, depth maps, tactile data and robot actions are cooperatively predicted through a joint denoising framework based on Transform. A mask self-attention mechanism is innovatively introduced, information interaction between modes is dynamically adjusted, action generation is guided through tactile feedback, and the force control precision is improved. The model adopts a de-noising diffusion probability loss function to jointly optimize multi-modal prediction, so that the output consistency is ensured. According to the method, the robustness and the accuracy of flexible operation of the robot are remarkably improved.

The invention discloses a five-finger bionic dexterous hand with distributed touch perception and a control method. The five-finger bionic dexterous hand comprises a palm part; fingers of the thumb unit, the index finger unit, the middle finger unit, the ring finger unit and the little finger unit respectively comprise a three-stage series flexion and extension mechanism which is sequentially composed of a third knuckle, a second knuckle and a first knuckle from a metacarpophalangeal joint, and each three-stage series flexion and extension mechanism has three flexion and extension freedom degrees and one deflection freedom degree; the tendon rope driving units are arranged in the palm part; the palm center camera is integrated on the front face of the palm part and used for collecting visual information of an operation area; the 15 air pressure type touch sensor modules are installed on the third knuckles, the second knuckles and the first knuckles of all the finger units in a distributed mode, and each air pressure type touch sensor module is integrated with a pressure and temperature double sensing unit and used for sensing contact pressure and environment temperature; the control module is integrated on the back face of the palm part and is in signal connection with the palm center camera, the air pressure type touch sensor modules and the tendon rope driving unit.

The invention discloses an ultrasonic enhanced tactile sensor system, a sensor and a sensing method. The tactile sensor system comprises a multi-mode sensing unit and a processing unit. The multi-mode sensing unit integrates an ultrasonic module and a visual tactile sensing module, ultrasonic acoustic impedance matching and optical imaging transmission are achieved through an acousto-optic matching structure, and ultrasonic echo signals and tactile deformation images can be synchronously collected. In the processing unit, an event triggering module detects a contact event based on a tactile image and generates a switching signal, and a self-adaptive processing module dynamically controls an ultrasonic mode, distance measurement during non-contact, and switching to object internal imaging or material property identification during contact according to the switching signal. And the three-level fusion processing module outputs a multi-modal sensing result through signal-level synchronous acquisition, feature-level cross-modal fusion and decision-level task switching. According to the system, multi-dimensional perception of proximity sense, surface texture and deep information is realized, and the pre-judgment and accurate operation capability of the robot in a complex scene is improved.

The invention relates to a robot dynamic grabbing control method based on visual sense and tactile sense depth fusion. The method comprises the following steps that firstly, based on visual information, surface geometric features of a target object are extracted, grabbing adaptability scores are calculated, an optimal grabbing point is selected, and a collision-free approaching track is planned; secondly, in a contact establishment stage, detecting a contact event through a touch sensor, fusing vision and touch data to unify a coordinate system, calculating a vision-touch consistency score, and applying an initial grabbing force; and thirdly, in the stable holding stage, slip detection is conducted through wavelet packet energy entropy and pressure gradient, and the grabbing force and impedance parameters are dynamically adjusted in combination with self-adaptive impedance control. According to the method, intelligent control over the whole process from approaching to contact to stable holding is achieved, and the adaptability, stability and safety of robot grabbing in the dynamic environment are improved.

The invention relates to the technical field of pose control, in particular to a robot flexible grabbing method and system based on a touch sensor, and the method comprises the steps: carrying out the image collection of an environment where a to-be-operated object is located based on a camera integrated in a robot, so as to obtain an image of the environment where the to-be-operated object is located; and acquiring a real-time pose of an end effector of the robot based on inertial measurement equipment integrated in the robot, and performing pose estimation on a to-be-operated object in the environment image based on a pre-trained pose estimation model to obtain the pose of the to-be-operated object. By combining the environment image acquired by the camera and the real-time pose information provided by the inertial measurement equipment, the robot can estimate the pose of the object to be operated in real time, and the position and the pose of the object can be accurately speculated by utilizing the pre-trained pose estimation model, so that the accuracy of the operation of the robot is improved. Therefore, the operation of the end effector of the robot can be accurately butted with the object, and errors in the operation process are reduced.

The invention discloses a large-deflection deformation flexible shaft hole assembly method and device based on tactile perception, storage equipment and a program product, and belongs to the technical field of robot assembly. The problem that an existing assembling method does not consider the influence of non-linear large-deflection deformation of the flexible shaft on the assembling precision of the shaft hole is solved. Based on pressure distribution data fed back by the tactile sensor, the deformation condition of the shaft can be estimated and adjusted, the flexible shaft workpiece makes effective contact with the rigid plane where the target hole is located, whether the shaft passes through the hole or not is monitored in real time in the blind hole searching process, and after the hole is searched, the mechanical arm is controlled to automatically align the shaft hole, so that the hole searching efficiency is improved. And the shaft insertion action is completed. The device is mainly used for shaft hole assembly of the large-deflection deformation flexible shaft workpiece.

The invention discloses a multi-curvature high-resolution bionic miniature visual tactile sensor for fingertips, which relates to the technical field of sensors and comprises a fingertip structure, a transparent support structure, a flexible silica gel sensing layer and an image acquisition module. A cavity is formed in the fingertip structure; the transparent supporting structure is clamped in the cavity; the flexible silica gel sensing layer is adhered to the transparent supporting structure, and black circular array mark points are attached to the surface of the flexible silica gel sensing layer; the image acquisition module is arranged on the fingertip structure, the acquisition end of the image acquisition module is arranged above the transparent supporting structure, and the view field area of the acquisition end covers the whole flexible silica gel sensing layer area; compared with other fingertip tactile sensors, the visual tactile sensor is a human fingertip simulated visual tactile sensor with the highest spatial resolution, the smallest overall size and the lowest manufacturing cost.

The present invention relates to an advanced augmented reality, AR, apparatus featuring a video see-through AR, VST-AR, device that captures images of a real-world environment and displays augmented versions on a screen. The system includes a corporal entity, such as an empty laboratory vessel, equipped with a unique identification marker. This marker provides real-time spatial data for generating visual augmentations representing virtual matter within the vessel. The apparatus integrates various sensors, including an inertial measurement unit, IMU, capacitive tactile sensors, and a thermal diode, to dynamically adjust visual augmentations based on user interactions. Additional sensory enhancements include an olfactory output fan, an eccentric rotating mass, ERM, motor, and auditory outputs. Wireless connectivity via IEEE 802.11 (Wi-Fi) and IEEE 802.15.1 (Bluetooth) ensures seamless communication between components. This AR system is particularly valuable for educational and laboratory settings, offering realistic, interactive simulations.

A visual tactile sensor, a manipulator and a control method thereof, the visual tactile sensor comprising: a contact layer, at least a portion of which is transparent; when the contact layer is subjected to external force, at least one part of a plurality of markers in the marker array generates displacement and / or deformation; and the image acquisition unit is used for performing image acquisition on the marker array and performing image acquisition on the outside through the transparent part of the contact layer. The visual tactile sensor provided by the invention not only can capture the external visual information before operation to identify the operation object, but also can provide the tactile information in the operation process, so that the perception capability of an operation system is enhanced, and the operation success rate is improved.

The invention discloses an intelligent navigation method and system, and relates to the field of intelligent robot control. The method comprises the following steps: acquiring multi-modal data acquired by a touch sensor, a visual sensor and a force sensor; if the matching degree of the tactile data and the visual data is lower than a preset threshold value, adjusting the tactile data by adopting a weighting coefficient to obtain a fusion feature vector; a three-dimensional point cloud map is generated according to the fusion feature vector, and if it is detected that the dynamic change rate of the point cloud map is higher than a preset threshold value, an incremental updating algorithm is triggered to correct the environment model; extracting a terrain feature set from the environment model, and generating a candidate path set by adopting a reinforcement learning algorithm; and if the passing cost value of the candidate path is lower than a preset threshold value, smoothing the candidate path to obtain an optimized navigation path. According to the invention, accurate navigation and path planning in a complex environment are realized, and the adaptability and robustness of a navigation system are improved.

The invention relates to the technical field of artificial intelligence, and discloses a multi-modal man-machine interaction interface and behavior prediction system, which comprises a multi-modal data acquisition module used for acquiring visual, auditory and tactile data of a user in real time; the data synchronization and preprocessing module is used for carrying out time synchronization on the collected multi-modal data and carrying out denoising and error correction on the data; the data fusion module is used for fusing different modal data and extracting core features of the data; the behavior prediction module is used for performing user behavior prediction based on the fused data; and the system optimization module is used for dynamically adjusting the interaction mode and function of the system based on the behavior prediction result so as to realize personalized user experience. By adopting a multi-modal data fusion technology, data from a visual sensor, an auditory sensor and a tactile sensor are efficiently fused, core features are extracted, and a more accurate user behavior prediction effect is achieved.

The invention relates to the technical field of sensors, and provides a visual tactile sensor and a robotic.The visual tactile sensor comprises a shell, an elastic body, a light-transmitting plate, a camera, a light source and a light uniformizing plate, the camera, the light source and the light uniformizing plate are arranged in the shell, the elastic body is connected to the surface of the front end of the light-transmitting plate, and the light-transmitting plate is embedded in the front end of the shell; the elastic body protrudes out of the front end surface of the shell, the light-transmitting plate is made of light-transmitting materials, one end of the light uniformizing plate corresponds to the light source, the other end of the light uniformizing plate corresponds to the side portion of the light-transmitting plate, and the light-transmitting plate is used for transmitting light from the side portion of the light-transmitting plate to the front end surface of the light-transmitting plate. Therefore, more uniform light can be obtained to irradiate the surface of the elastic body connected to the surface of the front end of the light-transmitting plate, the light supplementing uniformity of the light source in the visual tactile sensor is effectively improved, the imaging quality of the elastic body of the visual tactile sensor is further improved, and meanwhile, the precision and the stability of the visual tactile sensor are improved.

The invention provides a large-area split type flexible magnetic tactile sensor with a sensing function, and the sensor employs a plurality of flexible square magnetic sheets which are magnetized in the thickness direction, and the polarities of the flexible square magnetic sheets are alternately arranged in a checkerboard array mode in which the polarities of the magnetic fields of the adjacent flexible square magnetic sheets are opposite, so as to simulate a flexible magnetic film which is magnetized in a folded manner. The magnetic flux density of a contact force acquisition area is enhanced, a U-net algorithm is adopted to carry out field intensity-force relation fitting on the divided acquisition area, and a contact force cloud picture is generated, so that a Hall sensor and a flexible magnetic film can keep a large distance to carry out split type large-area contact force sensing, and lossless split type installation is realized; and compared with simple magnetic field modes such as unidirectional magnetization, the touch sensor has higher sensitivity. According to the size of a required contact force measuring surface, more flexible magnetic touch sensor arrays are arranged, a contact force cloud picture is drawn together through a plurality of units, and the flexible magnetic touch sensor array has application potential in the fields of bionic robots, flexible electronics, medical treatment and the like.

An optical tactile sensor comprising a contact part having a contact surface that comes into contact with an object, the contact part being deformed in response to a contact state of the object with respect to the contact surface; a marker disposed on the contact part, and configured to be displaced in response to deformation of the contact part; and an imaging unit configured to capture an image of the marker from a side opposite to a side where the object comes into contact, wherein the contact part allows light in a first wavelength range to pass therethrough, and blocks light in a second wavelength range different from the first wavelength range, the marker reflects light that is incident on the marker from the opposite side, and the imaging unit receives the light reflected by the marker and the light in the first wavelength range, and generates an image.

The invention discloses a multi-mode tactile and visual fusion identification method for medicine box braille salient point characters. The method comprises the following steps: acquiring three-dimensional morphology and pressure data of Braille salient points through a tactile sensor, acquiring an image and the like through a visual sensor, and performing preprocessing (improved U-Net segmentation, illumination correction and the like); hardware is utilized to trigger synchronization, an ICP algorithm is improved to complete space-time alignment, and a feature level (attention mechanism) and a decision level (D-S evidence theory) are fused; character semantics are analyzed by means of a multi-mode neural network, and multi-channel feedback is visualized through voice, tactile vibration and AR. A dynamic optimization mechanism is set, and sensor scheduling, incremental learning and safety verification are covered. The system comprises a tactile / visual perception module, a data processing module (FPGA + NPU), a feedback execution module and a communication module. According to the scheme, the problems of low traditional recognition precision and poor environmental adaptability are solved, high-precision medicine box braille recognition is achieved, and a reliable scheme suitable for multiple scenes is provided for safe medicine use of visually impaired people.

The embodiment of the invention discloses a visual tactile sensor, a clamping force control method and device and related equipment, a clamping device is controlled to clamp an object to move, and the visual tactile sensor is arranged on the clamping device; in the process of controlling the clamping device to clamp the object to move, the clamping force of the clamping device is adjusted in response to event information output by an event camera on the visual touch sensor. Therefore, through the visual tactile sensor arranged on the clamping device, in the process of controlling the clamping device to clamp the object to move, the clamping force of the clamping device can be adjusted in time according to the event information output by the event camera on the visual tactile sensor, so that the object is prevented from sliding or even falling off, and the user experience is improved.

The invention provides a finger-shaped visual tactile sensor, a sensing method and a dexterous hand. The finger-shaped visual tactile sensor includes: a transparent elastic body; the transparent supporting body is positioned below the transparent elastic body and is used for supporting the transparent elastic body; the LED lamp group is positioned near the transparent support body; the camera is used for acquiring an image of the transparent elastomer; and the shell is used for mounting the transparent supporting body, the LED lamp group and the camera. The finger-shaped visual tactile sensor can better adapt to a dexterous hand to execute fine operation.

The invention provides a tactile sensor and a device with the tactile sensor, the tactile sensor comprises a shell, a shooting assembly, a touch layer and a reflecting piece, a transparent part is arranged on the shell, and the touch layer is connected with one end, far away from the shell, of the transparent part; the touch layer comprises one or more specific patterns, the reflecting part is arranged in the shell and faces the touch layer, an inclination angle is formed between the plane where the reflecting part is located and the plane where the touch layer is located, and the inclination angle ranges from 15 degrees to 65 degrees; the shooting assembly is arranged in the shell, and the shooting end of the shooting assembly faces the reflecting part. According to the touch screen, the deformation of the specific pattern on the touch layer when the touch layer is in contact with the object is reflected to the shooting assembly through the reflecting piece, so that the shooting assembly analyzes the changed pattern through an advanced image processing algorithm to generate detailed touch information; and by adjusting the relative angle among the reflecting piece, the touch layer and the shooting assembly, the overall thickness of the touch sensor is effectively reduced, the overall size is reduced, and the application range is wider.

The invention discloses a physics-based visual tactile sensor multi-mode contact simulation system and method, and the system comprises an elastic body contact simulation unit which is used for carrying out the particle processing of an elastic body of a visual tactile sensor, and obtaining the three-dimensional coordinates of particles on the surface of an object through the contact simulation of the elastic body; the coordinate system conversion unit is used for calculating the coordinates of the mark points on the pixel coordinate system through the coordinate system conversion relation to obtain a mark point simulation image; the tactile image simulation unit is used for processing the three-dimensional coordinates of the particles to generate a tactile simulation image; and the tactile mark point joint simulation unit is used for combining the mark point simulation image and the tactile simulation image to obtain a tactile mark point joint simulation image. According to the method, simulation of the visual tactile sensor tactile image, the mark point image and the tactile mark point combined image in the motion states of pressing, sliding, rotating and the like can be efficiently completed.

The invention relates to the technical field of robots. According to the touch sensing fingertip device, protection of a touch sensor in fine operation of a mechanical arm is achieved, and objects of sheet structures can be grabbed more accurately. Specifically, through the bionic fingernail part installed on the back side of the fingertip body, the protection part of the bionic fingernail part extends forwards and exceeds the highest point of the touch sensor, and a cantilever protection structure similar to a human fingernail is formed; the protection parts form a physical barrier (for example, the protection parts are preferentially contacted during grabbing) in a non-contact state by utilizing a reasonable coverage range of the bionic nail part, and meanwhile, when the protection parts are matched with fingers on the opposite side, the two corresponding protection parts can be matched to grab an object of a sheet-shaped structure; according to the design, the durability of the sensor in a complex environment is improved, and the accuracy of grabbing the sheet-shaped objects is improved.

The invention discloses a shoe tree grabbing robot track planning system and method based on multi-modal sensing. The system comprises a shoe tree storage area, a mechanical arm grabbing assembly, a multi-modal sensing device, a posture recognition module, an interference sensing module, a grabbing point optimization module, a stable window generation module, a path planning module, a fine adjustment control module and a self-learning module. The system extracts the posture of the shoe tree by fusing visual images, structural sound waves and infrared contour information, then utilizes interference fringes to analyze and judge the material and friction characteristics, combines stability to judge and screen a grabbable target, and executes posture fine adjustment and fitting at the tail end of a clamping jaw through a touch sensing film. And the grabbing failure information is used for updating the strategy database to realize self-adaptive optimization of the grabbing strategy. The method is suitable for grabbing special-shaped objects and is high in robustness and success rate.

A tactile sensor, consisting of a flexible main body with embedded magnets, soft magnetized cilia on the main body, and magnetic sensing elements embedded on the substrate layer. The magnetic sensing elements produce signals in response to the changes in the magnetic field. Tactile interaction with the main body and cilia displaces the magnetic material and changes the magnetic field. Cilia are sensitive to sub-mN force magnitudes, the main body is sensitive to larger range of force magnitudes. Multiple sensing elements, magnets and cilia may be distributed over large and curved surfaces. Three-axial forces can be measured using the sensor.