10 results about "Spatial system" patented technology

An electronic spatial system is disclosed including an electronic circuit that is sensitive to spatial radiation, including at least one signal input port and / or at least one signal output port; a signal processing unit; an electronic spatial radiation detection unit electrically connected to the signal processing unit; and at least one protective switch electrically connected between the electrical ground of the electronic spatial system and at least one out of the signal input or signal output ports of the sensitive electronic circuit, and controlled by the signal processing unit. The signal processing unit is configured to switch the at least one protective switch to the electrical ground upon detecting an amplitude of a signal that is representative of an amount of spatial radiation greater than a predefined radiation threshold.

The invention discloses a terrestrial-like space system connection efficiency evaluation method and device and a readable storage medium, and relates to the technical field of data processing, and the terrestrial-like space system connection efficiency evaluation method comprises the steps: obtaining terrestrial-like space information of a terrestrial-like space system in a three-dimensional model of a target region; determining an evaluation index value of the connection efficiency of the terrestrial space system according to the terrestrial space information; the evaluation index value comprises a terrestrial area coefficient, a terrestrial floor connectivity rate and a terrestrial connection work efficiency ratio; and comparing the evaluation index value with a preset index threshold value to obtain a comparison result, and taking the comparison result as an evaluation result of the connection efficiency of the terrestrial space system in the three-dimensional model. According to the method, the evaluation efficiency and the evaluation accuracy of the connection efficiency of the terrestrial space system can be improved, and the consistency of evaluation results is ensured.

The application provides an environment adaptive formation control method based on a free parameterization stable network, automatically switches between a compact formation and a standard formation according to real-time distances from a formation geometric center to obstacles, and realizes intelligent reconstruction of a formation shape through a preset distance threshold and a smooth transition mechanism; a free parameterization stable network architecture is used to realize parameterization dynamic operator design of each spatial distributed control unit, distributed information exchange is realized through a sparse interconnection topology isomorphic to a spatial system communication graph; inherent stability properties of the free parameterization stable network structure are used to construct a controller parameter unconstrained scheme suitable for a space environment, so that the stability of a spatial closed loop system can be guaranteed for any parameter value, thereby avoiding feasibility constraints of linear matrix inequalities, and realizing unconstrained gradient learning of a three-dimensional distributed controller.

An augmented reality (AR) headset is disclosed that provides a wearer with spatial, system, and temporal contextual information of a surgical robotic system to guide the wearer in configuring, operating, or troubleshooting the surgical robotic system before, during, or after a surgical procedure. Spatial contextual information can be rendered in a coordinate system of the AR headset to display a spatially fixed 3D generated virtual model of the robotic arms, instruments, table, and other components of the surgical robotic system that matches the actual position or orientation of the surgical robotic system. The AR headset can communicate with the surgical robotic system to receive real-time status information of the components of the surgical robotic system. The AR headset can use the real-time status information to display context-sensitive user interface information, such as reminders, suggestions, visual or audio cues about maneuvering the robotic arms and table to their target positions and orientations or for troubleshooting purposes.

The invention relates to the technical field of road rain and sewage pipe network path planning, in particular to a road rain and sewage pipe network path planning method based on reinforcement learning. The method comprises the following steps: firstly, based on acquired multi-source heterogeneous data, carrying out preprocessing to obtain a unified space system; based on the unified space system, obtaining state attributes in the unified space system; based on attributes of the states, obtaining a state transition legality function, and judging whether the two states are reachable or not; on the reachable basis, calculating a transfer weight based on a state transfer legality function; then, based on the transfer weight, determining a strategy candidate set; constructing an instant reward function based on the strategy candidate set; on the basis of an instant reward function, a state value is obtained through a dynamic self-regularization Bellman updating formula, then a next state is determined, and finally a path sequence is formed. The technical problems that path hopping is severe, a decision cannot be explained, and control over path continuity and environmental adaptability is lacked are solved.

The application discloses a system identification method based on subspace band constraint, and steps are as follows: collecting input and output dynamic data of a system and preprocessing; based on the preprocessed input and output dynamic data, a black box state space model containing the input and output dynamic data is identified through a subspace system identification method, and a state space matrix is obtained, the state space matrix comprises a state matrix, an input matrix and an output matrix; a constraint about the state space matrix is constructed through prior knowledge; the state matrix and the input matrix in the state space matrix are kept unchanged, and the output matrix satisfying the constraint is calculated, or the state matrix and the output matrix are kept unchanged, and the input matrix satisfying the constraint is calculated; a step response model of the system is calculated based on the state space matrix satisfying the constraint; and the step response model is fitted into a low-order transfer function model. Through the constraint using the prior knowledge in the subspace identification method, the identification accuracy is improved.

A smart space system includes: a cabin, including: a bottom surface; and a first screen, located on a side wall of the cabin and connected to the bottom surface; an interactive human-machine interface, including: a display system, having an imaging device, wherein the imaging device is configured to project multiple multimedia images onto the first screen; and a controller, signal-connected to the interactive human-machine interface to issue a control command to the interactive human-machine interface, so that the multimedia images are connected to form a first continuous image, so that images of the first continuous image appear coherent on the first screen.

The present application relates to the technical field of magnetic resonance imaging, and discloses a breast lesion multi-modal magnetic resonance imaging system based on multi-nuclear atom information fusion, which comprises: synchronous acquisition of hydrogen nucleus, sodium nucleus and phosphorus nucleus signals and conversion into a quantitative concentration field, which is mapped to a hydrogen nucleus spatial system after a resolution matching operation; subsequently, a non-lesion reference background is extracted to generate a sodium abnormal distribution field and a phosphorus abnormal distribution field, and an initial lesion profile and its directional extension weight are generated; then, the abnormal layer center positions of the two abnormal distribution fields are calculated along the outer normal to obtain local layer position eccentricity, and the directional extension weight is used for weighted calculation to combine into a boundary correction amount; finally, a target lesion three-dimensional surface is reconstructed based on the boundary correction amount, and a medical image model is output by fusing the local layer position eccentricity on the surface. The present application effectively solves the multi-nuclear metabolic layer position eccentricity problem in the invasion front, and comprehensively improves the precision of lesion three-dimensional profile boundary reconstruction and metabolic distribution calibration.

This application relates to the fields of intelligent building and Internet of Things (IoT) technology, specifically to an intelligent building variable space system and its control method. The intelligent building variable space system includes variable space components, sensor modules, and an IoT platform. The variable space components are used to dynamically adjust the spatial layout and upload their own operational status data in real time; the sensor modules are used to collect and upload spatial environmental data; the IoT platform includes a data processing unit, a linkage control unit, and a function expansion unit. The data processing unit analyzes data and identifies user space usage patterns based on machine learning algorithms, generating and issuing pre-adjustment instructions 5-15 minutes before a preset event occurs; the linkage control unit, according to preset linkage rules, responds to safety events or scene event trigger signals, synchronously controlling the variable space components and other intelligent devices to perform coordinated actions; the function expansion unit expands the system control modes and linkage rules by dynamically loading software function plugins.

Systems, methods, and apparatus are disclosed for omnimodal sensing, data fusion, and autonomous decision-making across physical and digital domains. The disclosed architecture integrates biological-analog modalities including visual, auditory, olfactory, gustatory, and tactile sensors with symbolic or linguistic data sources such as text, structured records, or unstructured digital inputs. A data-fusion engine consolidates these heterogeneous streams into a unified context representation. A machine-learning inference model performs diagnostic, predictive, or safety-related reasoning from this representation. A distributed-ledger framework validates and preserves data provenance, and a resilient communication subsystem ensures command, control, and safety continuity through alternative channels such as cellular text, low-frequency radio, optical, acoustic, or magnetoelectric field-based transmission. This framework enables autonomous and semi-autonomous platforms including vehicles, humanoids, industrial robots, drones, and space systems to perceive, decide, and act with human-level contextual understanding even under degraded network conditions.