15 results about "PHYSICAL FORCES" patented technology

Embodiments of the invention provide an active pen-stylus that emulates a paper feeling for users of the active pen-stylus. The active pen-stylus comprises a writing shaft that receives physical forces arising from use of the pen-stylus by a user. The active pen-stylus also includes a force sensor that receives forces from the writing shaft, the force sensor configured to convert received forces into an electronic signal. A writing spring receives forces from the force sensor and reflects back to the user a reactionary force that emulates a paper feeling. The writing spring compresses and undergoes geometric deflection in creating the reactionary force that emulates the paper feeling. The geometric deflection produced by the writing spring arises from deformation of the writing spring by the received forces.

An omnidirectional mechanical drive unit in a robot may be controlled by a processor. An input message characterizing a physical force exerted on a force sensor in a first direction may be received. A physical force input vector quantifying the physical force in two or more dimensions may be determined based on the input message. Upon determining that a triggering condition for navigational feedback is satisfied, a haptic force input vector for provide haptic navigational feedback via the omnidirectional mechanical drive unit may be determined. A force output vector aggregating the physical force input vector and the haptic force input vector may be determined. The force output vector may quantify a force to apply to move the robot in a second direction. An indication of the force output vector may be transmitted to the omnidirectional mechanical drive unit. The robot may be moved based on the force output vector.

This invention provides a method for online force assessment of characters in a virtual reality environment, aiming to achieve real-time quantitative assessment, physical accuracy, and high robustness of force on humanoid character movements in virtual reality environments. This method combines a motion generation model and a physics optimizer, using an end-to-end integrated approach to dynamically estimate key mechanical parameters such as joint torque and ground reaction force. Specific steps include: acquiring user motion trajectory data from sparse sensors (such as VR headsets and controllers); generating preliminary full-body motion postures using a motion generation model based on discrete latent space learning; performing physical correction and force estimation on the motion using a physics optimization module (employing a dual proportional-differential controller and a motion tracking optimizer); integrating motion data and force parameters; and outputting character animation and force visualization results in real time through a rendering engine. Through the collaborative design of motion generation and physical force assessment, this invention significantly improves the realism, real-time performance, and adaptability of virtual character movements, making it suitable for VR applications such as security monitoring, medical training, and sports simulation, enhancing immersion and interaction efficiency.

A sound conversion method in virtual reality implemented by a sound conversion system in the virtual reality according to an embodiment of the present invention includes forming a virtual atmosphere in the virtual reality, generating a physical force in the virtual reality, and generating virtual data on the virtual atmosphere on the basis of the physical force, wherein the virtual data is data on a state of the virtual atmosphere changed by the physical force.

The present invention relates to fully autonomous self-navigational medical devices which can be transported within a host subject without existing physical constraints, including those of current physical force limitations, and which are free to undergo a variety of structural and functional adaptations including the ability to perform real-time dynamic adjustment and adaptability to ever changing physiologic, anatomic, and pathologic conditions within the host subject.

A method for analyzing change in a mode of a unidirectional composite material includes applying a physical force of a predetermined pattern onto a unidirectional composite material specimen; sensing a vibration signal generated by the physical force at at least one sensed position thereof; performing modal analysis of a frequency response at a corresponding measurement location, based on the physical force applied to the specimen and the vibration signal measured at the sensed position of the specimen, and calculating at least one mode shape vector of the specimen based on the modal analysis result; compensating the calculated mode shape vector based on a distance between a normal line passing through a center of the specimen and the sensed position, thereby calculating a modified mode shape vector; and calculating a first modal assurance criterion (MAC) of the specimen based on the modified mode shape vector.

The application relates to a pedestrian motion trajectory evolution method and system based on a social force model, and the method comprises the following steps: setting a simulation environment, obtaining the initial position of pedestrians from a video; obtaining the actual force of the pedestrians at the collision moment and the non-collision moment according to a pedestrian dynamics model, updating the speed of the pedestrians according to the speed change of the pedestrians with time, and then updating the position of the pedestrians; obtaining the pedestrian motion trajectory according to the position of the pedestrians at each moment; wherein the construction process of the pedestrian dynamics model is as follows: obtaining the interaction force between the pedestrians and other individuals and the interaction force between the pedestrians and walls based on the social force model; constructing the social force, constructing the physical force according to the contact or collision action between the pedestrians and other individuals, and constructing the speed change of the pedestrians with time; and constructing the pedestrian dynamics model. Compared with the prior art, the application can more accurately reflect the actual force condition between the pedestrians under different situations, and the dynamics analysis is more in line with the actual situation.

To provide a cleaning method capable of improving cleaning effect by easily and reliably applying physical force using water and oil without using a large amount of cleaning solvent, even when cleaning an object to be cleaned requires cleaning with particularly strong physical force. [Solution] The object to be cleaned 7, which has been heated to 100°C or higher, is immersed in heated water 4 mixed with abrasives 6. When the object to be cleaned 7 comes into contact with the heated water 4, the pressure of the steam generated and the abrasives 6 come into contact with the object to be cleaned physically remove dirt adhering to the object to be cleaned 7.

Systems and methods for detecting an occlusion in an infusion device are disclosed. One method includes generating, during an infusion session at predetermined intervals, a feature vector including an initial measurement of a physical force caused by fluid motion through an infusion device at the start of an infusion session, a current measurement of the physical force, a long term change in the measurement of the physical force, and a short term change in the measurement of the physical force. The feature vector is inputted, during the predetermined intervals, into a support vector machine (“SVM”) to output an indication of a presence or an absence of an occlusion in the infusion device. The SVM may be trained using reference data from reference infusion sessions having known consequences regarding the presence or the absence of an occlusion at various times during the reference infusion sessions.

The invention relates to a computer implemented method for continuous position estimation of a moving body (BDY), comprising: (a) Providing an initial (INT) position (POS) and initial (INT) orientation (ORN) of at least one motion sensor (SNR) attached to said body (BDY); (b) Measuring motion parameters (PRM) comprising at least one acceleration (ACC) in at least one spatial direction (DRT), using said at least one motion sensor (SNR); (c) Providing a motion-model (MMD) for predicting the motion of the body (BDY), wherein the motion-model (MMD) is designed to time-stepwise determine an estimate (EST) of the translation and orientation (ORN) of the body (BDY); (d) Providing a Kalman filter (KMF) comprising a prediction module (PDM) and a correction module (CRM) both working in a repetitive loop, wherein said motion-model (MMD) is used as the prediction module (PDM) for estimating (EST) the motion of the body (BDY). It is proposed, that said model proceeding in the following steps when predicting the motion of the body (BDY): - assuming a center of gravity (COG) of the body (BDY), - estimating (EST) the physical forces (PFC) and torques that are acting on the assumed center of gravity (COG) of the body (BDY) to achieve the measured motions, - determining a prediction of the body (BDY) position from the estimated (EST) physical forces (PFC) and torques.

A mechanical drive unit for a robot may be controlled by receiving from a force sensor an input message characterizing a physical force exerted on the force sensor in a first direction. A physical force input vector may be determined based on the input message and quantifying the physical force in two or more dimensions. A force output vector aggregating the physical force input vector and a second force input vector and quantifying a force to apply to move the robot in a second direction may be determined at least in part by applying a force multiplier multiplying the physical force input vector. An indication of the force output vector may be transmitted to the omnidirectional mechanical drive unit via a communication interface. The robot may be moved via the mechanical drive unit in the second direction based on the force output vector.

This paper considers the Protein Joint Atom Modeling (SPICA) strategy and the corresponding elastic network model of physical interactions, belonging to the field of protein dynamics characterization (computational) technology. First, test sets were constructed, including 135 and 6 protein experimental crystal structures respectively. Then, the following five steps were performed: 1. Construction of the protein joint atom model; 2. Initial parameter setting and force field parameter pairing; 3. Calculation of spring force constants; 4. Construction of the Hessian matrix; 5. Parameter optimization and dynamic analysis. This method is the first to introduce the protein joint atom modeling strategy into the traditional elastic network model computational framework, while integrating the corresponding physical interaction forces, significantly improving computational accuracy while maintaining computational efficiency.

System for the non-invasive, field-based detection of resonance signals between biological units, characterized in that physiological parameters (e.g., electromagnetic, acoustic, or biophotonic signals) are detected and evaluated for patterns of synchronization or coupling, including subtle resonance phenomena that go beyond known physical forces and can be interpreted in the context of a postulated fifth force.

This invention discloses a sensorless foot contact detection method and system for robots based on multimodal fusion, belonging to the field of robot control technology. This invention acquires multi-source sensor data such as robot joint position, velocity, and initial torque; analyzes foot motion state data based on a rigid body dynamics model; and reconstructs foot contact force data through inverse kinematics. Multimodal normalized contact feature values ​​are extracted using corresponding feature mapping functions, and the foot contact state is determined and output after global weighted fusion. This invention eliminates the need for foot physical force sensors, reducing hardware costs and unsprung mass. Multimodal fusion improves the robustness and fault tolerance of contact detection, while a fault-tolerant mechanism enhances the overall operational safety margin.

The application discloses a molecular dynamics trajectory prediction method and system fusing physical force field prior, and relates to the fields of computational chemistry and artificial intelligence. The method acquires initial structure data of a to-be-detected molecular system and physical prior parameters (such as partial charge) between atoms; through a double embedding and residual enhancement mechanism, the physical prior parameters are mapped into high-dimensional features; an improved isometric graph neural network based on physical force field perception is constructed; in the message passing stage, the high-dimensional features are used to construct an electrostatic attention mechanism, to generate electrostatic interaction force features and to be reduced and fused into the updating process of edge features; finally, trajectory prediction is outputted based on the updated edge features through the isometric network. The application implicitly learns potential energy surface features without destroying isometricity, and significantly improves the physical authenticity and long-term stability of the model for molecular dynamics long trajectory prediction.