1120 results about "Touch Senses" patented technology

The invention discloses a dexterous hand teleoperation method based on vision-touch fusion. The method comprises the following steps: 1) vision detection; the method comprises the following steps of (1) carrying out remote control, (2) carrying out redirection, (3) carrying out tactile grabbing, (4) carrying out vision-tactile interaction, (5) carrying out a communication process and (6) carrying out dexterous hand.The method can stably map human hand actions under the complex vision condition, safe and reliable grabbing control is achieved through tactile feedback, meanwhile, multiple dexterous hand configurations and cross-platform deployment are supported, and the precision, robustness and practicability of teleoperation can be improved.

A smart busy board is provided utilizing a technology driven timer which can be set to predetermined time intervals for each of a plurality of interactive components disposed on the smart busy board. The timer mechanism and some of the interactive components are connected to electrical elements hidden within the interior housing of the smart busy board. Each of the interactive components engage the infant or toddler with some type of sensory output, such as movement, sound, light, and touch for a predetermined time interval. The busy board is designed to stimulate frontal lobe and cognitive development and improve motor skills.

Disclosed is a robotic system and method designed for the verification and validation of smart connected Human-Machine Interface (HMI) devices. The robotic system integrates a multi-finger modular robotic module, a haptic module, a finger actuator, vision cameras, vision lights, a finger rotary module, a Cartesian robotic arm, an onboard user interface, and an L-shaped door. The method involves replicating human finger interactions, simulating touch sensations on a device under test (DUT), ensuring continuous and reliable operation, utilizing vision cameras for navigation and verification, optimizing vision with controlled lighting, positioning cameras strategically, executing various tasks with a robotic arm, and facilitating user interaction through an onboard interface.

The invention belongs to the field of intelligent rehabilitation medical instruments, and particularly relates to a brain-computer interface-based multi-modal child sensory integration training device, which comprises a brain-computer interface head ring, an intelligent touch floor and AR interactive glasses, the brain-computer interface head ring is connected with a biological signal acquisition module, the intelligent touch floor is connected with a motion trail analysis unit, the AR interactive glasses are connected with a universe scene engine, and the biological signal acquisition module, the motion trail analysis unit and the universe scene engine are connected with a digital twin generator. The digital twin generator is connected with a dynamic mode switching decision tree, and the dynamic mode switching decision tree is connected with a multi-mode feedback actuator; the brain-computer interface head ring is located on the head of the child and collects electroencephalogram, myoelectricity and electrocardiosignals through a biological signal collection module; and the biological signal acquisition module sends a signal to the digital twin generator through wireless transmission. According to the invention, the training efficiency can be improved, the evaluation dimension can be expanded, potential safety hazard early warning can be realized, and the compliance can be enhanced.

An electronic device displays a palette user interface in response to receiving one or more inputs from an electronic stylus that is communicatively coupled to an electronic device. In some embodiments, the electronic device displays the palette user interface at a spatial arrangement that is based on a pose of the stylus at the time that the input to initiate display of the palette user interface is received. In some embodiments, the electronic device generates at the electronic stylus a tactile output having one or more tactile output characteristics based on characteristics of the one or more inputs from the electronic stylus. In some embodiments, the palette user interface includes one or more selectable options that when selected, initiate a process to display one or more additional user interfaces for configuring the output that is generated by the device in response to stylus inputs.

The invention discloses a multi-task dexterous hand operation method based on self-adaptive two-way distillation, which comprises the following steps of: constructing a plurality of single-task expert strategies based on vision-touch pre-training, and collecting state-action tracks of a high-degree-of-freedom dexterous manipulator on various operation tasks; on-line distillation is utilized to distill multi-task expert data into a unified diffusion strategy sharing perception characterization and task coding, and modeling action multi-modal distribution is generated through diffusion type actions; a self-adaptive routing network is introduced, supervision weights of all experts are dynamically distributed according to the current observation state, and weighted distillation of the mixed experts is achieved; and after the performance of the unified strategy is superior to that of experts, performing reverse distillation on the unified diffusion strategy into expert strategies of all tasks by adopting action-reward combined constraint, and performing two-way iterative distillation circulation. Through forward and reverse knowledge migration between a unified strategy and a task expert, the problems of observation distribution offset and task imbalance in multi-task dexterous operation can be effectively relieved.

The invention provides an interactive interface design parameterization method guided by tactile feedback. The method comprises the following steps: acquiring physiological features, use habits and use scene information of a user, and presetting basic tactile feedback parameters according to a scene-parameter mapping rule; during interaction, touch parameters such as vibration frequency and amplitude are dynamically adjusted based on user operation behaviors, physiological reactions and scenes by using a deep learning model; and meanwhile, a multi-modal parameter fusion model is established, so that tactile, visual and auditory parameters have a synergistic effect, for example, when a button is clicked, the three parameters are mutually associated to enhance a feedback effect. After the operation is completed, the feedback effect is evaluated through objective indexes such as the subjective score of the user and the operation accuracy, and the user personalized model and the parameter adjustment model are optimized. According to the method, the problems that traditional parameters are fixed, and multi-modal fusion is insufficient are solved, accurate and personalized man-machine interaction is achieved, and the user experience is improved.

Examples of the disclosure include at least one non-transitory computer-readable medium storing instructions for operating a system including a furniture apparatus and stimulation devices, the instructions configured to instruct at least one processor to receive a user selection of one of a plurality of stimulation routines; determine, based on the selection, first stimulation parameters for a first stimulation device of a first type including one of haptic, sound, visible-light, and electromagnetic-radiation stimulation; determine, based on the selection, second stimulation parameters for a second stimulation device of a second type different than the first and including one of haptic, sound, visible-light, and electromagnetic-radiation, the second set being synchronized to a target synchronization frequency; and provide first and second control signals to the first and second stimulation device, respectively, the first signals including the first stimulation parameters and the second signals including the second stimulation parameters.

The embodiment of the invention discloses a pressure touchpad and a pressure sensing detection method thereof, and relates to the technical field of touchpads, the pressure touchpad comprises a substrate layer, an FPC, a touch layer, a touch sensing layer and a piezoelectric layer; the touch layer is arranged above the touch control sensing layer; the touch sensing layer is arranged above the substrate layer; the piezoelectric layer is arranged below the substrate layer; the FPC is arranged on one side of the substrate layer, and the FPC is electrically connected with the touch net and the piezoelectric layer; wherein the piezoelectric layer vibrates under the excitation of an electric signal of the FPC; the piezoelectric layer receives external force above the piezoelectric layer to deform and generate an electric signal; and the touch sensing layer is used for sensing capacitance change to generate an electric signal. The pressure touch panel is simple in structure, the thickness is greatly reduced, and the cost is also reduced.

The invention provides a touch feedback control method and device for a rotary knob, electronic equipment and a medium, and belongs to the technical field of switch control. The method comprises the following steps: converting a current Ia, a current Ib and a current Ic in a three-phase static coordinate system into a current Ialpha and a current Ibeta of a two-phase static coordinate system; the current I alpha and the current I beta of the two-phase static coordinate system are converted into current Id and current Iq under a two-phase rotating coordinate system with rotor flux linkage as orientation; the convergence speed of the driving motor in the dynamic response process is controlled and optimized by adopting a sliding mode variable structure; performing real-time setting through a zebra optimization algorithm to minimize overshoot and optimize convergence time; and the magnitude of the rotation feedback damping force is controlled by adjusting the current Iq. In this way, active rotating tactile feedback and pressing tactile feedback can be provided, and the intelligent interaction degree is improved.

The invention discloses a dexterous hand general grabbing method and device based on single-visual-angle vision and demonstration optimization, and relates to the field of dexterous hand grabbing and artificial intelligence. The method comprises the following steps: firstly, building a real field scene and teleoperation equipment, and collecting expert data of objects with multiple sizes and shapes; and in combination with the collected expert data, on the basis of an algorithm obtained by improving a DAPG algorithm, a general grabbing strategy of cross-object shape primitives is learned in combination with domain randomization operation in a simulation environment. Geometric features of an unknown object are analyzed in real time through the first visual angle visual information, an initial grabbing track is generated, the grabbing force and posture are adjusted by fusing dynamic feedback of a force touch sensor, and high-generalization and high-reliability grabbing is carried out. The problems that a traditional method depends on a large amount of real expert data, a large amount of object model training is needed, strategy generalization is poor, and simulation migration stability is insufficient are solved.

Computing devices and methods for determining a force applied to a user input device are disclosed. In one example, a computing device comprises a user input device comprising a touch surface, a haptic actuator coupled to the touch surface, and an accelerometer coupled to the touch surface. The computing device receives a touch input from the touch surface and drives the haptic actuator with a force detection driving signal to cause an acceleration in the touch surface. The computing device measures the acceleration using a signal from the accelerometer and uses at least the acceleration to determine a force of the touch input on the touch surface.

There is disclosed a modular sensory platform for generating an experience for a guest on the platform located on an event floor of a venue. At least one deck module may each include a frame with a bottom side for mounting to the event floor, a side edge bordering the frame, and a standing surface opposite the bottom for supporting the guest. Lift actuators may be positioned along the side edge or under the deck for changing a distance between the event floor and the standing surface according to a lift signal. One or more sensory stimuli each receivable of a stimulus signal may be mounted to the frame and include at least one of a vibration buzzer, a low-frequency transducer, smoke effects, a heater, a water spritzer, air and scent lines, an air blaster and scent emission, a haptic device, fiber optic lighting, LED lighting, and a fog unit.

The invention discloses a dexterous hand environment article sensing and modeling algorithm based on body sensing. The algorithm comprises the steps that a mechanical arm drives a dexterous hand to approach an object; tactile-spatial data acquisition: a three-axis force sensor is arranged at the tail end of each finger of the dexterous hand, and the system is in contact with an object through multiple fingers of the dexterous hand to acquire multi-dimensional information of the appearance, surface characteristics and local topology of the object; active exploration sampling, multi-finger movement of the mechanical arm and the dexterous hand, and active penetration of unknown object surface and enhanced sampling of local features through the dexterous hand by the system; the method comprises the following steps: modeling an object attribute, analyzing a mechanical response sequence obtained by tactile-spatial data acquisition and active exploration sampling, modeling a target object in three dimensions of elasticity, hardness and local geometric morphology, and realizing accurate identification and modeling of an unknown object appearance form and an object attribute in an environment. The distribution uniformity of the tactile point cloud and the model integrity are improved, the hardware dependency is reduced, and the environmental adaptability is enhanced.

The utility model discloses an electronic device, and the electronic device comprises a control assembly, a touch sensing circuit, and a piezoelectric assembly. The control assembly is connected to the piezoelectric assembly through the touch sensing circuit; the piezoelectric assembly is arranged on a target piece of target equipment, and the piezoelectric assembly is configured to generate a first electric signal in response to a knocking event acting on the target piece; the touch sensing circuit is configured to receive the first electric signal, modulate the first electric signal into a second electric signal and output the second electric signal to the control assembly; the control assembly is configured to generate a corresponding control instruction in response to the second electric signal meeting a control condition.

The invention provides a hand rehabilitation training glove and system based on electromyographic signal guidance and pressure feedback, and the glove comprises a flexible glove main body which is made of an elastic material, is designed to fit the anatomical structure of a human hand, and is used for collecting bioelectrical signals generated by the remaining hand and forearm muscles of a patient when the patient actively intends to generate power; the embedded signal processing module is used for carrying out amplification, filtering, noise reduction and analog-to-digital conversion processing on the collected original electromyographic signals; and the main control unit is used for calculating time domain and frequency domain characteristic values of the electromyographic signals and identifying the motion intention of the patient based on a preset threshold value or an adaptive algorithm. Weak electromyographic signals are collected and processed in a high-precision mode and immediately converted into local touch pressure feedback corresponding to the functions of the weak electromyographic signals, neural pathway connection between the cerebral cortex and target muscles is enhanced, training interestingness and immersion and compliance of a patient are remarkably improved, and the training effect is improved. And key power is provided for continuous long-term rehabilitation training.

The invention discloses an upper limb rehabilitation intelligent self-adaptive system based on multi-modal fusion and MRD-FES cooperation. The system comprises a multi-modal signal acquisition module, a dynamic intention analysis module, a variable damping precise execution module, a neural remodeling strengthening module and a quantitative effect evaluation module. The tDCS-MRD-FES time sequence cooperation protocol is provided, the cortical excitability is improved through tDCS preprocessing, MRD drives training based on intention, FES closed loop strengthens muscle contraction, and vibration tactile feedback is assisted to strengthen sensory movement integration. And the quantitative effect evaluation module further combines a neuroplasticity index and clinical scale digitalization to realize dynamic optimization of training parameters.

The invention provides a touch force feedback simulation method and system based on a pressure deformation signal, and relates to the technical field of touch interaction and tactile feedback, and the method comprises a data collection process: configuring a sensor to collect the physical state of a touch interface, and obtaining an instantaneous pressure and deformation signal; the impedance compensation process comprises the following steps: step 1, acquiring an instantaneous signal; 2, constructing a dynamic hysteresis loop model; step 3, calculating a viscosity energy loss value; 4, generating an energy compensation waveform; 5, an actuator is driven to generate reverse damping vibration; according to the method, the material viscosity loss is quantified through the physical phase space model, reverse energy is accurately injected, and the problems of touch hysteresis and soft collapse caused by viscoelasticity of a touch interface are effectively solved.

The present disclosure relates to a haptic input / output device for recreational vehicles. The disclosed aspects provide dynamic haptic feedback to a vehicle operator depending on a vehicle context and / or the functionality being controlled by the haptic input / output device. In some instances, the haptic input / output device is usable to control a touch-sensitive input device, thereby offering tactile feedback to a vehicle operator when controlling providing input via the touch-sensitive input device accordingly.

A remote haptic signal-based method and system of performing an authentication of video of a person in order to authorize access to a secured resource. The system and method are configured to cause a remote computing device to generate a vibration while collecting sensor data from the same device. The sensor data is evaluated to determine whether the appropriate motion response from the remote computing device is present. If the response is present, the system determines the image is authentic and can verify an identity of the person, and can further be configured to automatically grant the person access to one or more services, features, or information for which he or she is authorized.

Computing devices and methods for determining a force applied to a user input device are disclosed. In one example, a computing device comprises a user input device comprising a touch surface, a haptic actuator coupled to the touch surface, and an accelerometer coupled to the touch surface. The computing device receives a touch input from the touch surface and drives the haptic actuator with a force detection driving signal to cause an acceleration in the touch surface. The computing device measures the acceleration using a signal from the accelerometer and uses at least the acceleration to determine a force of the touch input on the touch surface.

The invention relates to an electromagnetic radiation interference resisting method and device of a touch key and computer equipment. The method comprises the following steps: acquiring touch sensing data input through a plurality of touch keys in a current time period; determining a touch sensing reference value corresponding to each touch key, and obtaining a touch sensing deviation value corresponding to each touch key based on the difference between the touch sensing reference value corresponding to each touch key and the touch sensing data; obtaining an interference intensity statistical result based on the touch sensing deviation value corresponding to each touch key, and if the interference intensity statistical result meets a strong electromagnetic radiation interference judgment condition, indicating that the touch key integrated equipment is in a strong electromagnetic radiation interference environment; and adjusting the key-out threshold value of each touch key in the strong electromagnetic radiation interference environment based on the strict key-out rule to obtain a key-out threshold value adjustment result of each touch key. By adopting the method, the anti-interference stability of the touch key integrated equipment in a complex electromagnetic environment can be improved.

Systems and methods for touch sensing are provided. An input device includes a display and a touch sensor. The touch sensor has a sensing area with a plurality of sensor pixels forming rows and columns. Each sensor pixel includes a first electrode having first capacitive coupling areas and a second electrode having second capacitive coupling areas. The first capacitive coupling areas are configured to capacitively couple with one or more adjacent sensor pixels disposed in a same row and the second capacitive coupling areas are configured to capacitively couple with one or more adjacent sensor pixels in a same column. The first electrode is configured to electrically connect to one or more sensor pixels in the same column and the second electrode is configured to electrically connect to one or more sensor pixels in the same row. The sensor pixels are configured to facilitate parallel touch sensing in multiple orientations.

The invention provides a man-machine emotion interaction assembly, method and device, a robot, a medium and a program product, and relates to the technical field of artificial intelligence. The man-machine emotional interaction assembly comprises a pressure tracking module which is used for capturing a micro gesture contacted by a user and generating a corresponding sensing signal; the sound receiver is used for collecting user voice; the processing module is connected with the pressure tracking module and the sound receiver and comprises an emotion pressure sensing model and a sensing session model, the emotion pressure sensing model is used for performing emotion sensing based on the sensing signal to obtain a sensing result, and the sensing session model is used for performing semantic and emotion analysis on the user voice; generating response information based on the analysis result and the sensing result; and the tactile stimulation module is connected with the processing module, receives the stimulation instruction generated by the processing module, and executes tactile stimulation based on the stimulation instruction. Through the technical scheme disclosed by the invention, the man-machine emotion interaction component effectively relieves the pressure and nervous emotion of the user by reappearing a secure physical prompt.

The application discloses a motion control method of a mobile robot and the mobile robot, and relates to the field of robots. The mobile robot comprises a wheel part and a base part connected with the wheel part, and a somatosensory sensing device is arranged on the base part. The method comprises the following steps: receiving a tactile pressing operation on the somatosensory sensing device; and in response to the tactile pressing operation, controlling the mobile robot to perform interactive motion; wherein the interactive motion is motion corresponding to the tactile pressing operation, and at least one of the wheel part and the base part moves in the process of the interactive motion.

Systems and methods are provided for guiding movement of a tool. The system includes a tool and a manipulator. A guide handler obtains a target state for the tool and generates virtual constraints based on the target state and a current state of the tool. A constraint solver calculates a constraint force adapted to attract the tool toward the target state or repel the tool away from the target state based on the virtual constraints. A virtual simulator simulates dynamics of the tool in a virtual simulation based on the constraint force and input from one or more sensors, to output a commanded pose. The control system commands the manipulator to move the tool based on the commanded pose to thereby provide haptic feedback to the user that guides the user toward placing the tool at the target state or away from the target state.

In some embodiments, a computer mouse comprises a housing, a depressible keyplate disposed within the housing, a carrier platform including a top side and disposed within the housing, a haptic element coupled to a top side of the carrier platform, a biasing system configured to couple the carrier platform to the housing and provide a pre-loading force that pushes the haptic element coupled to the carrier platform against a bottom surface of the depressible keyplate, and a limiter element operable to physically limit a movable range of the keyplate in one direction that prevents a top surface of the keyplate to deflect past an adjacent top surface of the housing due to the pre-loading force, the top surface of the keyplate and the adjacent top surface of the housing forming a continuous contour when the depressible keyplate is in a non-depressed, neutral position.

A hand gesture tracking device, method, and non-transitory computer readable storage medium thereof are provided. The device performs hand gesture tracking corresponding to a user based on multiple real-time images and an inertial sensing data. The device determines whether a virtual object associated with a haptic feedback interaction is contacted based on the hand gesture tracking. In response to determining that the virtual object associated with the haptic feedback interaction is contacted, the device triggers a haptic feedback device of a wearable device to perform the haptic feedback interaction corresponding to a time interval. The device inactivates the inertial sensing data corresponding to the wearable device to perform the hand gesture tracking corresponding to the time interval.

The invention discloses a dexterous hand grabbing stability control system and method based on force control compliant interaction.The system comprises a dexterous hand, a mechanical arm, a force sensing module, a touch sensor, an actuator and an upper computer actuator, the dexterous hand is installed at the tail end of the mechanical arm through a mechanical interface, and the dexterous hand and the mechanical arm form a cooperative control closed loop through real-time communication; according to the control mode of the dexterous hand grabbing stability control system, the upper layer completes object positioning and global motion planning through a mechanical arm, the lower layer completes a layered collaborative architecture of contact perception, compliant control and task action execution through a dexterous hand, and compliant grabbing and stable control over objects are achieved. The mechanical characteristics in the grabbing process can be adjusted in a self-adaptive mode, it is ensured that objects with different hardness are stably and smoothly grabbed, and the problem that the objects slide or are damaged is effectively solved.

The invention discloses an intelligent interaction robot control system which comprises a sensing input module, a core processing module, an output execution module and a system management and maintenance module. The perception input module collects multi-modal data through a visual, auditory, environment and touch unit; the core processing module carries out fusion analysis on the data and generates a decision instruction through a multi-modal information fusion unit, a situation cognition and decision unit, an emotion calculation unit and a motion planning unit; the output execution module executes an interaction task through a voice unit, an expression action unit and a motion unit; and the system management and maintenance module provides knowledge base, cloud collaboration and energy monitoring support. Through multi-modal information deep fusion and situational cognition, accurate understanding of user intentions and environments is realized, emotional interaction and personalized service capabilities are provided, the problems that an existing system is single in interaction mode and lacks context understanding are solved, and the intelligent level and user experience of the robot are remarkably improved.