18 results about "A* search algorithm" patented technology

This invention discloses a method, apparatus, medium, and device for parameter optimization of analog circuits, relating to the field of analog circuit technology. The invention automatically identifies current paths through a search algorithm to deeply analyze the circuit topology, determine the symmetry structure in the analog circuit, and constructs symmetry constraints based on the identical optimization parameters of electrical components within the symmetry structure. Simultaneously, it transforms the product of the transistor's gate width and the number of parallel connections into the total width and sets the optimization boundary. This combination reduces the dimensionality of the optimization variables while ensuring that the parameter optimization process conforms to the layout design of the analog circuit. Furthermore, it combines a population mutation algorithm and a non-dominated sorting genetic algorithm with an elitist strategy to perform iterative optimization within the constructed efficient search space, significantly improving the convergence speed of analog circuit parameter optimization, reducing computational costs, and enhancing the practicality of the analog circuit parameter optimization method.

Disclosed are systems and methods for enhancing local node performance in a storage system through offloading cache replacement tasks to remote nodes. A periodic time-series analysis of CPU cycle utilization and network latency is conducted on one or more arrays to identify and / or forecast underutilized nodes in the one or more arrays. A first array detects a shortage of available cache slots in an allocation queue and identifies underutilized remote nodes in either its own array or another array. The array shares the metadata pages with the remote node. A worker thread on the remote node runs a search algorithm on the received meta data pages and creates a list of candidate replacement memory slots.

A mobile vision transformer network for use on mobile devices, such as smart eyewear devices and other augmented reality (AR) and virtual reality (VR) devices. The mobile vision transformer network considers factors including number of parameters, latency, and model performance, as they reflect disk storage, mobile frames per second (FPS), and application quality, respectively. The mobile vision transformer network processes images, e.g., for image classification, segmentation, and detection. The mobile vision transformer network has a fine-grained architecture including a search algorithm performing latency-driven slimming that jointly improves model size and speed.

A vortex electromagnetic wave near field azimuth identification method is provided. Four kinds of vortex electromagnetic waves with different modes are set to detect a target, four groups of echo data are obtained, two-by-two interference processing is performed on the four groups of echo data, the phase generated by the target slant range is eliminated, six groups of echo phases after interference are extracted, six groups of theoretical phases are constructed, and a search algorithm is used to obtain a high-precision target azimuth angle which makes the sum of absolute values of errors between the echo phases after interference and the theoretical phases minimum. The present application can complete azimuth identification only by using four modes under the condition of ensuring measurement accuracy, is more efficient, and is more in line with the demand of rapid direction finding of near field detector.

This invention relates to the field of marine ranching technology, and provides an integrated control method and robot for repairing fishing nets. The method includes: based on an uncertain heatmap, using an adaptive focusing scanning algorithm to guide a 3D lidar to collect point cloud data of a target area, forming a 3D topography of the target area; acquiring the spectral signal of the fishing net in the target area to determine the net material type, optimizing the tactile probe parameters to control the tactile probe's movement, collecting the vibration response signal of the fishing net to obtain a fishing net health index; determining whether to issue a repair command through multi-source fusion decision-making; and upon receiving the repair command, determining the location of the damaged point based on the 3D topography and the geometric contour of the damaged area, obtaining the robot's planned path through an A search algorithm, and precisely moving to the actual working area to perform the repair operation through adaptive PID control.

This invention discloses a mapping optimization method and related apparatus for quantum circuits, belonging to the field of quantum computing technology. The method includes: acquiring multiple quantum circuits containing different numbers of logical bits; calling a search algorithm according to the different number of logical bits contained in each quantum circuit to find the target qubit block that maps the logical bits of the quantum circuit to the physical bits of the quantum processor according to a certain number of hops, and storing the target qubit block in memory; performing the mapping operation from the logical bits of the quantum circuit to the physical bits of the quantum processor based on the target mapping region of the target qubit block of the quantum processor. This application first finds the target qubit block by calling a graph search algorithm, and then performs the mapping operation on the local mapping region of the target qubit block, aiming to improve the mapping efficiency and mapping quality of qubits in quantum circuits, thereby improving the overall computing efficiency of quantum computing.

Systems and processes for aligning weakly-annotated tabular data to recognized characters in a document are provided. Data table annotations are grouped by column and value to produce a plurality of annotation groups. Character recognition tokens are received, and a search algorithm is performed to align the annotation groups to the tokens in a stepwise manner. A base column is designated, after which the search algorithm is performed on the base column annotation groups and the results are used to determine a vertical range of the data table. The search algorithm is then run for the other columns of the data table with the results being limited based on the vertical range. At each step, the annotations in an annotation groups are each aligned to one or more of the tokens. A bounding box is generated for each annotation in the data table and output to a target application.

One embodiment provides a method comprising receiving content for presentation on a display, and obtaining a plurality of image patches from the content. Each image patch is segmented from a bottom and horizontal-center portion of a sub-sampled grayscale image of a frame of the content. The method further comprises applying a searching algorithm to the plurality of image patches to detect a region of interest of moving text in the content. The searching algorithm utilizes a first set of features and a second set of features to detect the region of interest with respect to a vertical axis and a horizontal axis of the display, respectively. The method further comprises correcting one or more visual artifacts in the region of interest, where the one or more visual artifacts include broken text.

This application belongs to the field of robot motion control technology and discloses a robot trajectory tracking method, device, storage medium, and electronic device. First, the robot system is dynamically modeled; the current error state vector is calculated, and the dynamic equation of the error state is constructed; the error state is transformed into a three-dimensional z-space, and the dynamic equation of the error state is constructed in the three-dimensional z-space; a sliding mode surface is constructed in the three-dimensional z-space, and the equivalent phase space constraints corresponding to the sliding mode surface are calculated based on the optimization objective and constraints; a subspace is constructed according to the control strategy, and the subspace where the current state is located is determined through a search algorithm; the relative distances of the current state to all subspaces are calculated, and the optimal sliding mode surface is determined based on the relative distances; the relative relationship between the optimal sliding mode surface and the current error is calculated, and the relative relationship is input into the control law to determine the final control quantity. This method can significantly suppress robot jitter when approaching the equilibrium point, while improving computational efficiency and achieving optimal arrival at the target control point.

This invention discloses a path determination method for an unmanned loader, relating to the field of electronic technology. The method includes: acquiring real-time operational images and real-time point cloud data of the unmanned loader operating in a work scenario; determining the gate status of a hopper in the real-time operational image based on the real-time operational images and real-time point cloud data; identifying hoppers with open gates as temporary passage areas and updating the grid map using these temporary passage areas to obtain a target grid map; acquiring the current position of the unmanned loader and determining the optimal path for the unmanned loader to operate in the work scenario within the target grid map using a search algorithm based on the current position. This technical solution enables the planning of the optimal path based on the open status of the hopper. Compared to related technologies that rely on preset trajectories and purely visual detection, this method improves the flexibility of the optimal path and increases the passage efficiency of the unmanned loader.

This invention relates to a method for unmanned aerial vehicle (UAV) flight path planning, comprising: discretizing the UAV flight area using a three-dimensional mesh to obtain a set of cubes, and obtaining the semantic representation vector of each cube in the set; parsing and decomposing the user's flight path planning task instructions through an intelligent agent to obtain a sequence of semantic subtasks, and obtaining the semantic representation vector of each subtask in the sequence; matching the subtasks with the semantic representation vectors of the cubes to obtain a set of target cubes for each subtask; finally, using a designed semantic A* search algorithm to search for flight paths, generating flight path segments that satisfy each subtask; and assembling the generated flight path segments into a complete three-dimensional flight path according to the order of the subtasks. This method can automatically generate refined flight paths that meet semantic intent and geometric safety requirements, realizing end-to-end intelligent planning from semantic instructions to executable flight paths.

This invention provides a multi-constraint fusion AGV path planning method and related components, including: constructing a topological road network containing production process constraints to obtain a topological road network containing mandatory nodes; performing constraint filtering on the topological road network based on the AGV's physical parameters to obtain a feasible topological road network; using a search algorithm to perform process-oriented global path search in the feasible topological road network to generate an initial globally optimal path; collecting environmental data in real time and performing dynamic obstacle detection based on the environmental data to obtain obstacle information; performing local replanning on the initial globally optimal path based on the obstacle information to generate a final executable path; smoothing the final executable path and converting it into control commands, and driving the AGV to execute through the control commands. Compared with the prior art, this invention improves the executability of path planning.

The present application relates to the technical field of path planning, and particularly relates to a monitoring path planning method and system for a chemical industrial park, which comprises the following steps: obtaining a digital twin map of the chemical industrial park, wherein the digital twin map comprises static information and real-time dynamic data; constructing an equivalent dangerous concentration field based on the digital twin map; planning a monitoring path from a starting point to an ending point based on the equivalent dangerous concentration field and using an A search algorithm, wherein the moving cost of the A search algorithm is positively correlated with the equivalent dangerous concentration field. The present application improves the safety of robots in complex dangerous environments.

The application belongs to the field of mobile robot path planning and tracking control, and specifically relates to a kind of autonomous navigation method for complex dynamic environment-oriented car-like mobile robot. The method comprises the following steps: 1) generating an initial trajectory by A* search algorithm, limiting the trajectory range by using the self-vehicle expansion plane, iteratively optimizing the coordination point and expansion plane, and dynamically adjusting the path to complete path planning; 2) generating a globally smooth path by using virtual chassis and pure pursuit control, iteratively optimizing the path sampling and conflict detection, dynamically adjusting the local path segment, and realizing tracking control. The application optimizes the path planning and tracking control method, improves the adaptability of the robot to complex environment, realizes real-time path adjustment and conflict-free navigation, and ensures that the mobile robot safely and efficiently completes the task.

Techniques are discussed herein for generating trajectories for controlling motion and / or other behaviors of vehicles in complex driving environments. In certain examples, a search algorithm may be used to determine and evaluate a set of possible candidate actions for a vehicle, including candidate actions based on a predetermined exploration policy and additional candidate actions based on machine learned models that output predicted behaviors for the vehicle based on the current driving environment. Costs associated the various candidate actions may be evaluated based on state transition costs and / or future state predictions of the driving environment. Certain examples may include a tree search using a combination of predetermined heuristic candidate actions and adaptive-learning candidate actions at various nodes within a tree structure representing a driving route from a current vehicle state to an intended end state.