747 results about "Collision detection" patented technology

The invention relates to the field of mobile robot motion planning, and discloses a quadruped robot motion planning method and system based on height self-adaption. The method comprises the following steps: constructing 3D and 2D local obstacle maps according to coordinate transformation, and calculating a grid vertical distance through ray casting to generate a 2.5 D local obstacle map; determining an initial control sampling space by combining speed, acceleration and height constraints; discretizing a sampling space and simulation time, deducing a control value sequence and recursively calculating a local trajectory; then calculating a shaft alignment bounding box in a directed bounding box of the robot, screening grid units in the shaft alignment bounding box, comparing the height of a machine body with the allowable height of grids, and rejecting collision trajectories to obtain a feasible trajectory set; and finally selecting an optimal track by the evaluation function, extracting a control value and sending the control value to hardware for execution. According to the method, the 2.5 D local obstacle map containing height information is constructed, the four-dimensional control sampling space is designed, and the robot height self-adaptive adjustment is realized in combination with the collision detection and evaluation function.

The invention relates to the technical field of building steel structure construction, and provides a closed-loop control method for segmented construction of a special-shaped curtain wall steel structure, and the method comprises the steps: S101, carrying out the three-dimensional scanning of a to-be-installed component and a supporting jig frame, building a coordinate system through a positioning target, and obtaining point cloud data; step S102, extracting component splicing key points, matching point cloud with a design model, performing collision detection and generating pre-splicing positioning data; s103, converting the positioning data into a visual instruction, and guiding the component to be accurately in place in combination with the real-time hoisting data; s104, after installation, a seam area is scanned, and a new entering component is reinspected; s105, the step S102 to the step S104 are repeated until all the components are installed; and S106, integrally scanning to generate a completion model, comparing the completion model with the design model, and outputting a construction quality acceptance report. According to the technical scheme, the construction precision, efficiency and construction quality of the special-shaped curtain wall steel structure are collaboratively optimized by constructing a closed-loop control process.

The present invention relates to the technical field of path planning, and provides a deep reinforcement learning-based path exploration parameter optimization system. The system comprises: a variable parameter path planning module, configured to perform node exploration based on a deep reinforcement learning network, conduct collision detection on child nodes in a child node set, calculate cost values for all child nodes, and finally generate a loading and parking path using a Reeds-Shepp curve; an environmental state space modeling module, configured to perform regional division of obstacles around a current node and conduct environmental state space modeling; and a deep learning parameter optimization module, configured to construct a deep learning network to compute an optimal step size and an optimal steering angle, build a reward function to optimize the deep learning network, and simultaneously execute a training process of the deep learning network.

The invention discloses an obstacle avoidance motion planning method and system for redundant drive of an intelligent process of a welding robot and computer equipment. According to the method, firstly, a motion path of a robot is planned based on welding process redundancy, then a sampling strategy that the position and posture of a welding gun are separated is adopted, then the sampled posture is mapped to a planar two-dimensional space, and the relevance between an obstacle collision boundary and the obstacle avoidance posture of the welding gun is constructed; an incremental extreme gradient lifting model is adopted to carry out probability modeling on the collision boundary and obstacle avoidance attitude relevance, nearest neighbor search and new planning node expansion are carried out based on target cost to obtain new planning nodes, collision detection is carried out on the new planning nodes, and the new planning nodes passing the collision detection are used for incremental learning of an obstacle avoidance model; and finally, an optimization strategy of spherical linear interpolation and cosine slow motion time mapping is adopted to ensure continuity and smoothness of a motion planning path trace. The problem that in the prior art, it is difficult to quickly calculate and generate a collision-free welding track is solved.

The invention discloses a vehicle collision detection, description and early warning system and method based on a driving video, and belongs to the technical field of artificial intelligence and intelligent traffic safety. According to the system, on the basis of a vision-language model, vehicle-mounted videos such as an automobile data recorder are automatically analyzed, and detection, severity grading, natural language description generation and real-time early warning of vehicle collision events are achieved. The system extracts high-dimensional semantic features of video frames through a CLIP model, focuses key information through an attention weighting network, inputs the key information into a deep classification network composed of a plurality of full connection layers, a batch normalization layer and an activation function, and outputs a multi-level accident severity classification result. Integrating target detection and environment information, and generating a structured accident description text by using a fine tuning BART model; a sliding window and time sequence modeling mechanism is adopted, and recognition and early warning of the pre-collision state are achieved. The method effectively solves the technical problems of lack of semantic understanding, inaccurate severity judgment, incapability of early warning and the like of a traditional method, has high accuracy, high interpretability and real-time response capability, and is suitable for intelligent driving assistance and traffic safety monitoring scenes.

The invention relates to a collision prediction method, a collision prediction system and a vehicle, and the method comprises the steps: obtaining a real-time vehicle state of a target vehicle; constructing a collision detection area forwards based on the real-time vehicle state by taking the target vehicle as a reference; the collision detection area is a space area used for predicting the future collision risk of the target vehicle; detecting an obstacle boundary of an obstacle around the target vehicle, generating a travelable space based on the obstacle boundary, and detecting a space boundary of the travelable space; wherein the drivable space is a path space in which the target vehicle can safely drive; and generating a collision prediction result of the target vehicle based on the position relationship between the collision detection area and the space boundary. According to the invention, the problem of low safety of automatic driving of the vehicle is solved.

The invention discloses a collision detection method and a computer readable storage medium. The collision detection method comprises the following steps: determining all static components belonging to a preset static type and all dynamic components belonging to a preset dynamic type in a three-dimensional building model; static SDF data are constructed for all static components in the three-dimensional building model; wherein the static SDF data comprises a plurality of static SDF values, and the static SDF values are SDF values from a space point in the three-dimensional building model to the surface of the nearest static component; constructing dynamic SDF data for all dynamic components in the three-dimensional building model; wherein the dynamic SDF data comprises a plurality of dynamic SDF values, the dynamic SDF values are SDF values from a space point in a dynamic influence area to the surface of a dynamic component used for generating the dynamic influence area, and the dynamic influence area is obtained after the boundary of a minimum three-dimensional bounding box of the dynamic component is expanded outwards by a first preset distance; and detecting whether a collision point exists in the three-dimensional building model based on the static SDF data and the dynamic SDF data.

The invention provides a virtual reality three-dimensional space data correction method, which comprises the following steps of: firstly, acquiring an image, depth and inertia measurement data of a virtual reality terminal, and a pose, a speed and a force feedback signal of an interaction body, and carrying out time sequence alignment under a unified time reference; an interaction event is identified through collision detection, and parameters such as a contact point, a normal direction, a relative speed, a penetration depth and a contact duration are extracted. Then, physical consistency constraints including no penetration, contact stability, friction consistency, momentum conservation and energy non-increase are constructed, and geometric consistency, depth consistency and physical consistency residual functions are established in the local contact area; and solving surface normal, depth, scale, pose, calibration parameters and other corrections through a robust nonlinear optimization method so as to update the point cloud, the grid and the calibration model. According to the method, the consistency and the stability of geometric modeling and physical interaction in the virtual reality scene can be remarkably improved, and the immersion and the interaction precision are improved.

The invention discloses a defect multi-angle detection and fusion method based on a vector graph and affine transformation, and relates to the technical field of image processing, and the method comprises the steps: collecting a plurality of sub-images with overlapping regions at a single angle; constructing a collision map at the angle, wherein the view field of each grid corresponds to a sub-image; extracting defect contours from the sub-images and converting the defect contours into defect vector graphs; according to the defect vector set of all the sub-images at the angle, collision detection and cross-sub-image defect fusion are carried out based on the collision map at the angle, and a defect set at the angle is obtained; one angle is selected as a reference angle, other angles are selected as target angles, a defect set of the target angles is transformed to a reference angle coordinate system based on affine transformation, collision detection and cross-angle fusion are carried out on the transformed defect set and the defect set of the reference angles, and a final optical assembly defect set is obtained. And integrated detection of large-area coverage, high-precision alignment and high-efficiency fusion is realized.

The invention discloses a three-dimensional dynamic safety management and control method and system for power transmission and transformation hoisting operation, and relates to the technical field of construction safety, and the method comprises the steps: obtaining point cloud data of a target operation area through ground three-dimensional laser scanning; according to the point cloud data, a three-dimensional grid model is constructed through an oblique photography technology and a Beidou real-time dynamic carrier phase difference technology, and a semantic electronic fence is generated; according to a pure vision technology, through target detection, three-dimensional reconstruction and time sequence tracking, a hanging object 4D digital branch is constructed, and a hanging object prediction track is obtained; the shortest three-dimensional distance is calculated through an efficient collision detection algorithm according to the hanging object prediction track and the semantic electronic fence, multi-dimensional risk assessment is carried out, and graded early warning signals are generated; and carrying out comprehensive alarm prompting according to the graded early warning signal. According to the invention, a traditional passive protection mode depending on single threshold alarm is changed, and quantitative evaluation and predictive management and control of dynamic risks are realized.

The invention relates to the technical field of component collision detection, in particular to a building component-level collision detection method and system fusing multi-model semantics. The method comprises the steps of obtaining building component model data; component attribute extraction and semantic recognition are carried out according to the obtained building component model data; carrying out space conflict detection on the extracted information based on a bounding box and grid Boolean operation; judging conflict types and levels by utilizing a component attribute semantic library; and outputting a judgment result. By introducing a component attribute semantic database and combining semantic discrimination rules to match conflict types, 'acceptable conflicts' and'substantive conflicts' can be accurately distinguished, non-key conflict information can be automatically filtered, the false alarm rate is greatly reduced, the screening workload of designers is reduced, and collaborative design verification focuses on the core problem affecting construction safety and function implementation.

The invention belongs to the field of software testing and defect detection, focuses on reliability verification of a physical simulation engine, is suitable for scenes depending on physical simulation, such as robot simulation, automatic driving testing, unmanned aerial vehicle control, education and scientific research, and particularly relates to a variation-based physical simulation engine defect detection method. Potential defects of core modules of collision detection, mechanical calculation, dynamics and the like are efficiently found through a variation test method. According to the method, a feature library is constructed through static library API analysis and AST / IR code analysis, test code expansion is performed by utilizing a large model, a test driver adaptive to a specific data type is generated, a physical semantic constraint mutation seed is combined, a test is executed through libFuzzer, defect and coverage rate data are analyzed, a use case selection strategy is optimized, and the test efficiency is improved. Defects of core modules such as collision detection and dynamic solution are efficiently detected, and the test pertinence and efficiency are improved.

The invention discloses a three-dimensional voxel geometry collision detection method based on feature layering and multiple detection strategies, and relates to the technical field of computer graphics and game engines, the method comprises bit compression storage optimization, feature layering extraction and multiple collision detection, through the feature layering and multiple detection strategies, the unnecessary calculation amount is effectively reduced, and the detection efficiency is improved. The overall performance of the algorithm is improved, efficient memory compression is achieved while the detection precision is guaranteed, the requirement for computing resources is reduced, the technology can stably run in the resource-limited environment, unified collision detection processing of various geometries is supported, the universality and flexibility of the system are improved, and the system performance is improved. According to the method, integration and application in different application scenes are facilitated, the real-time rendering capability is optimized, the mobile terminal and the VR equipment are supported to run a complex physical simulation scene at a high frame rate, and the user experience and the interaction effect are improved.

The invention provides a vehicle path planning method and device. The method comprises the following steps: acquiring vehicle parameters, environment sensing data, a path starting point and a path ending point; generating an upper-layer obstacle grid map and a lower-layer obstacle grid map based on the vehicle parameters and the environment perception data; performing collision detection based on the vehicle parameters in the upper-layer obstacle grid map and the lower-layer obstacle grid map to obtain an upper-layer collision detection result and a lower-layer collision detection result; combining the upper-layer collision detection result with the lower-layer collision detection result to generate a planned path from the path starting point to the path ending point; the planned path comprises obstacle-avoiding nodes for bypassing the upper-layer obstacle and obstacle-crossing nodes for crossing the lower-layer obstacle. Therefore, efficient path searching in the multi-obstacle complex scene is realized, and the vehicle has better trafficability in the multi-obstacle complex scene.

The invention discloses a large ship autonomous berthing path planning method, and relates to the technical field of channel control. The method comprises the steps of collecting and processing data, establishing a ship motion model, setting a path planning target, selecting and solving an optimization algorithm, verifying and adjusting a path, obtaining hydro meteorological historical data and real-time sensing data of port wind, wave and flow, ship basic parameters and under-actuated dynamic characteristic data, and preprocessing the data. Obtaining a ship motion model; minimum berthing time, minimum energy consumption and maximum safety are set, and a comprehensive objective function is obtained; defining constraint conditions of kinematics, dynamics, port environment and collision avoidance; solving by using an optimization algorithm, performing dynamics simulation verification and collision detection verification on the planned path, adjusting parameters of the optimization algorithm, and modifying a target function or a constraint condition; according to the method, the optimal berthing path can be planned, the collision risk is effectively avoided, the safety and efficiency of large ship berthing are improved, and the method has universality and flexibility.

The invention discloses a navel orange grabbing pose estimation method based on multi-feature segmentation and a visual hedgehog algorithm, and relates to the technical field of computer vision, and the navel orange grabbing pose estimation method comprises the steps: collecting a color image and a depth image of a target navel orange, carrying out the spatial registration, and generating a three-dimensional point cloud; performing sphere fitting on the independent navel orange instance point cloud, outputting sphere center coordinates and radius parameters of each navel orange, and taking the sphere center coordinates and radius parameters of each navel orange as geometric data of the navel oranges; and collision detection and visibility analysis are conducted on the grabbing pose candidate set, collision cost and visibility cost are generated, comprehensive optimization is conducted on the collision cost and the visibility cost through a multi-target optimization function, the optimal grabbing pose is generated, and the mechanical arm is driven to execute grabbing operation based on the optimal grabbing pose. According to the method, the multi-feature segmentation and the visual hedgehog algorithm are combined, so that accurate calculation of the navel orange grabbing pose is realized.

The embodiment of the invention provides a collision detection method and equipment for a humanoid robot. The method comprises the steps that resultant force, collected by a force sensor, of the tail end of the mechanical arm is obtained, derivation is conducted on the resultant force in time, first force change rate data of the resultant force in a time domain are obtained, low-pass filtering is conducted on the first force change rate data based on a preset frequency threshold value, and second force change rate data of the resultant force in the time domain are obtained; the preset frequency threshold value is determined by converting historical force change rate data into data on a frequency domain, the historical force change rate data is obtained by deriving resultant force obtained in the operation process with collision on time, and a collision detection result is determined according to the second force change rate data and the preset threshold value. According to the method provided by the embodiment of the invention, the calculation process is simple and efficient, and the target object screening efficiency and accuracy are improved.

The invention provides a BIM (Building Information Modeling)-based engineering electromechanical installation method. The method comprises the following steps: establishing an engineering electromechanical BIM model; carrying out model collision check and optimization; construction simulation and scheme making are carried out; field installation and implementation; and installation acceptance and model filing. According to the method, the geometric and attribute integrated BIM model is constructed through data collection and digital drawing review, full-dimensional collision detection is carried out, key pipeline specification requirements are preferably guaranteed, model data reliability is guaranteed, construction disjunction caused by drawing errors is avoided, the problem of pipeline collision is solved in advance, and the construction efficiency is improved. Material waste and construction period delay of dismantling and reassembling in the construction stage are reduced, meanwhile, the risk of illegal acceptance of key pipelines is reduced, and the limited space utilization rate is increased.

The invention provides a ship anti-mold-penetrating and collision-preventing method in combination with Beidou and virtual channel constraint in a digital twinborn scene, and the method solves a problem of ship position deviation caused by the installation position difference of a Beidou terminal through Beidou and AIS dual-mode fusion positioning correction. Constructing a refined collision detection adaptation mechanism based on the ship models associated with various goods types, and adapting to size differences of different ship models; and a'positioning-ship model-collision detection 'cooperative link is opened, so that multi-target priority collision avoidance is realized. According to the method, the ship position display precision and the anti-mold-penetrating and anti-collision accuracy in the digital twin scene are effectively improved, and the method is suitable for real-time supervision and simulation in a high-density ship traffic environment.

The invention discloses a BIM-based terminal electromechanical pipeline conflict detection and optimization system, and belongs to the technical field of constructional engineering. The BIM-based terminal electromechanical pipeline conflict detection and optimization system comprises a model integration unit, a conflict detection unit, a pipeline optimization unit, a clear height verification unit, a result output unit and a whole process management unit. The problems that an existing pipeline collision detection technology is insufficient in precision, low in optimization efficiency and difficult to meet the requirements for the special functions and the net height of the terminal are solved, the collision detection unit is provided with a multi-dimensional collision detection mechanism, and the pipeline optimization unit combines the special function requirements and arrangement rules of the terminal to improve the collision detection efficiency of the terminal. A pipeline arrangement scheme with the optimal comprehensive cost is automatically generated and recommended through a genetic algorithm, and meanwhile high-precision and automatic detection and efficient optimization of terminal electromechanical pipeline conflicts are achieved through dynamic net height analysis and closed-loop whole-process management.

The invention discloses a robot grabbing pose generation method and device, and the method comprises the steps: obtaining a natural language grabbing task instruction, and carrying out the analysis based on a large language model, and generating a structured task parameter containing target object identification information and grabbing constraint information; performing open vocabulary target detection on the image based on the identification information, and obtaining a target area mask in combination with pixel-level segmentation; generating a target point cloud based on the mask, the depth map and the camera internal reference, carrying out depth completion or denoising, outlier elimination and threshold confirmation filtering, inputting the processed target point cloud into a grabbing pose prediction network, outputting a plurality of candidate six-degree-of-freedom grabbing poses, carrying out constraint screening according to grabbing constraints, and carrying out collision detection; and selecting the candidate with the optimal confidence coefficient from the collision-free candidates as the optimal grabbing pose to be output. Task constraints penetrate through a target extraction process, a point cloud construction process and a pose screening process, and point cloud processing and collision verification are combined, so that an executable six-degree-of-freedom grabbing pose which meets the constraints is output.

The invention discloses a real-time software deformation interaction method based on a physical engine in an environment. The real-time software deformation interaction method comprises the following steps: S1, establishing a virtual environment and a software model; s2, constructing an interactive perception and collision detection network; s3, receiving and analyzing a multi-modal interaction instruction; s4, real-time deformation calculation based on a physical engine; s5, performing multi-user collaborative state synchronization and rendering feedback; and S6, carrying out fault state simulation on the software object. According to the method, real-time and high-precision simulation of software deformation is realized through deep fusion of software dynamics calculation of a physical engine and an interaction instruction stream, and through hierarchical physical attribute binding and client prediction, the network synchronization data volume is greatly reduced while the millimeter-level deformation precision is ensured, so that the network synchronization efficiency is improved. And low-delay and high-consistency experience under multi-person cooperative operation is ensured.

The invention relates to the technical field of mobile robot autonomous navigation path planning, and discloses a complex orchard scene-oriented hybrid sampling global path planning method, which comprises the steps of adopting a Gaussian hybrid sampling strategy, switching between global uniform sampling and Gaussian offset sampling through a probability threshold, and considering global exploration and key area guidance; a dynamic node expansion strategy is adopted, the expansion step length is adaptively adjusted according to the distance between the expansion step length and a target point, and the expansion direction is optimized by fusing vectors facing a sampling point and the target point and introducing an obstacle influence factor; a layered collision detection strategy is adopted, and step-by-step filtering is carried out through rough detection based on a quadtree, secondary screening based on an axis alignment bounding box and accurate geometric judgment in sequence so as to improve the efficiency; and a dynamic iteration termination mechanism is adopted, and the minimum number of iterations and the path quality convergence state are combined as composite termination conditions. The method can quickly generate a smooth and safe path, and is especially suitable for structured scenes such as orchards.

The invention discloses a grabbing and placing task-oriented robot trajectory planning method and device, and the method comprises the steps: obtaining a natural language task instruction, carrying out the path decomposition based on a large language model, and generating a stage sequence containing pre-grabbing, grabbing, lifting, pre-placing, placing and withdrawing, and each stage target and / or constraint; receiving the optimal grabbing pose and / or placing pose provided by the upstream module, and replacing or correcting stage targets related to grabbing and / or placing; generating a trajectory segment according to the corrected stage target and constraint, and carrying out smoothing processing to obtain a trajectory sequence; performing collision detection on the track sequence, and if collision occurs, outputting collision information and executing local repair or replanning until the collision detection is passed or a preset replanning condition is met; and outputting the executable track sequence of the robot controller. According to the scheme, stage decomposition and key pose landing are achieved, and a collision feedback closed loop is formed to obtain an executable track.

The invention relates to the technical field of vehicle intelligent driving and active safety control, and discloses an active obstacle avoidance method and system considering multi-source uncertainty and fault positioning, and the method comprises the following steps: S1, predicting the tracks of a normal vehicle and a sideslip vehicle, and obtaining the predicted position and covariance of the normal vehicle and the sideslip vehicle; s2, constructing an extended state equation containing a positioning fault, and estimating and compensating a positioning deviation; s3, establishing a linear error tracking model, unifying various uncertainties into equivalent disturbance, and solving a disturbance invariant set; s4, generating a candidate obstacle avoidance track based on the compensated state; s5, track comfort is evaluated, hard constraints are checked, and infeasible tracks are removed; s6, transversely expanding the contour of the vehicle by using a disturbance invariant set, and carrying out longitudinal and transverse separation expansion on the contour of the target vehicle based on the predicted covariance; s7, performing robust collision detection by using the disconnect axis theorem; and S8, carrying out robust tracking control by adopting Tube-MPC. According to the invention, safe and stable obstacle avoidance control can be realized under complex disturbance and fault positioning conditions.

The invention discloses a mechanical arm tail end posture constraint path optimization method based on constraint manifold. A discrete constraint manifold point set which is high in posture precision, robust in singular point, uniform in space distribution and constrained in kinematics is generated based on a Monte Carlo method, a weighted damping pseudo-inverse method, an attenuation type learning rate gradient descent iteration method and voxel density optimization; based on measurement of a laser tracker, the relation between static environment information and a target point relative to a mechanical arm base coordinate system is constructed; a coarse path is obtained through a sampling method, and a feasible path on a constraint manifold meeting attitude constraint and having no collision is generated based on a search strategy of Euler distance difference + maximum joint angle variation + collision detection + index reconstruction criterion; and in combination with a multi-target weighted CHOMP algorithm, the feasible path is optimized into a collision-free and smooth path which meets the requirements of attitude constraint and kinematics constraint. According to the method, the problems of insufficient consideration of attitude constraint, low efficiency, local convergence and the like of traditional path planning are solved.

The invention discloses an automatic driving vehicle decision-making method, which comprises the following steps of: firstly, acquiring vehicle surrounding environment data through a multi-sensor fusion technology, carrying out danger grade division on obstacle vehicles based on distance and lane information, and aiming at the obstacle vehicles with different danger grades, carrying out decision-making on the obstacle vehicles; a deep learning model and an intention recognition method based on a Frenet coordinate system are adopted for track prediction, balance between prediction precision and calculation efficiency is achieved, a reinforcement learning framework containing a state space, an action space and a multivariate reward function is constructed on the decision-making level, behavior decision-making of a self-vehicle is achieved through a dual deep Q network, and the decision-making efficiency of the self-vehicle is improved. And the driving safety is ensured by combining real-time collision detection. According to the invention, intention identification and track prediction capabilities of the automatic driving vehicle to surrounding vehicles in a complex road environment are effectively improved, and safe and smooth automatic driving behaviors conforming to traffic rules are realized through an intelligent decision-making mechanism.

The invention discloses an additive and subtractive composite manufacturing process planning method for element runner structure features, which comprises the following steps: S1, analyzing the feature structure of a runner, optimizing the runner for additive and subtractive composite manufacturing, and splitting a multi-runner structure into a plurality of single-runner structures; s2, a machining strategy is set, namely, the single runners are machined one by one in sequence, and a single-runner additive machining strategy is machining along a centroid shaft; s3, developing a collision detection algorithm for flow channel additive and subtractive machining, and circularly solving a machining area segmentation plane by using the collision detection algorithm along a flow channel centroid shaft to obtain a flow channel additive and subtractive alternate area division scheme; s4, generating specific additional material and subtractive material processing procedures; and S5, post-processing to generate a processing code, and importing the processing code into additive and subtractive composite manufacturing equipment for processing. According to the invention, the process planning result without collision and with high processing efficiency can be quickly and efficiently obtained.

The invention relates to the technical field of image processing, in particular to a rapid collision detection method based on a three-dimensional digital virtual scene, and the method comprises the steps: collecting the static point cloud information of a to-be-detected region and the laser reflection intensity of the point cloud; determining a unit normal vector and curvature corresponding to each point cloud; determining a characteristic value of each point cloud; based on the characteristic values among the point clouds and the numerical distribution of the curvature, obtaining growth conditions of a region growth algorithm, and segmenting all the point clouds based on the region growth algorithm to obtain an edge structure region, a noise region and a building region; after the point clouds in the noise area are removed, the complexity of each edge structure area is obtained, an abnormal point discrimination threshold value in a filtering algorithm is adjusted, and all the point clouds are filtered; and constructing a BIM model based on the filtered point cloud data to carry out collision experiment simulation. The invention aims to improve the processing quality and precision of the point cloud so as to improve the accuracy of collision detection.

The invention relates to the technical field of computers, and relates to a scheduling simulation method and device for unmanned equipment, a program product and equipment. The method comprises the steps that a task configuration file is analyzed, simulation scene information and simulation task information are obtained, and the simulation task information at least comprises a test mode and task parameters; the unmanned simulation devices are loaded according to the test modes and the task parameters, a state machine is created for each unmanned simulation device, and the state machines are used for conducting state conversion control on the unmanned simulation devices in the simulation process based on scheduling information and / or simulation task information of the scheduling system; based on the simulation scene information and the simulation task information, starting the unmanned simulation equipment to execute a simulation process, and executing collision detection based on a dynamic octree on the unmanned simulation equipment in the simulation process to obtain detection information; and the simulation process is finished, a simulation result is generated according to the task completion information and the detection information, and the simulation result is used for evaluating the scheduling system.