46 results about "Collision probability" patented technology

The invention relates to the technical field of equipment control, and provides an autonomous tracking anti-interference control method and system.The confidence coefficient of a sensor is determined by combining the historical precision of the sensor and the current signal quality through a sensing recognition module, and the fusion weight is dynamically adjusted based on the confidence coefficient, so that the target tracking state can accurately reflect the actual motion characteristics of a target; the trajectory planning module takes an interference type, an interference degree and a target tracking state as input parameters cooperatively, and combines an extended state space and a reward function containing an anti-interference reward, so that an explored tracking trajectory can actively adapt to an interference scene; meanwhile, the predicted collision probability is compared with a probability threshold value, so that the global updating triggering opportunity is ensured to be accurate, and the collision risk caused by an unreasonable track is effectively avoided; and the control optimization module generates a targeted feed-forward compensation amount according to the interference type and the interference degree, and generates a control instruction after superposing the basic control amount, thereby realizing cooperation of anti-interference compensation and trajectory tracking control.

The invention relates to the technical field of automatic warehouse material, and discloses an intelligent goods allocation distribution system for automatic warehouse logistics, and the system comprises a goods allocation data collection module; a dynamic state detector; a multi-source data fusion unit; a three-dimensional storage modeling module; intelligently distributing a strategy engine; and a PLC control interface. According to the intelligent goods allocation allocation and scheduling system for automatic warehouse logistics, a goods allocation allocation scheme is generated through a multi-target Pareto optimization algorithm, the balance between carrying distance minimization min sigma alpha * Di and space utilization rate maximization Ut is achieved, and compared with a proportional static allocation rule, the warehouse space utilization rate is increased to 82%; a dynamic grid map technology is integrated, and a track cross risk area (red early warning grid) of the stacker and the AGV is marked in real time, so that the equipment collision probability is reduced by 90%; and in combination with a goods relevance knowledge graph, special goods such as medicines are clustered and stored according to temperature zones, and the energy consumption of cross-temperature-zone operation of equipment is reduced by 35%.

The invention relates to the technical field of space optimization, and discloses a container loading space optimization method based on robot collaboration, and the method comprises the steps: building a multi-dimensional physical model of a package through obtaining the point cloud data and weight distribution of the package; generating a loading scheme containing a target pose, a pressure tolerance threshold and a loading sequence based on a reinforcement learning algorithm; the mechanical arm generates a motor current-position composite control instruction according to a pre-trained grabbing dynamical model, and accurate grabbing is achieved; in the loading process, the pose of the parcel is monitored in real time through a Kalman filtering algorithm, when deviation exceeds a threshold value, a local space KD tree is constructed, a collision probability gradient field is calculated, and a compensation scheme meeting stability constraints is generated; and finally, updating the quad-tree index and feeding back to the reinforcement learning algorithm for online optimization. The problem that in the robot loading process, the grabbing force control is not accurate, and the efficiency is reduced due to execution deviation accumulation is effectively solved, and efficient and accurate automatic loading is achieved.

Technologies and techniques for determining a trajectory of an assisted-operated motor vehicle. At least one object is detected in an environment of the motor vehicle and at least one uncertainty with respect to the object is determined. A future environment with the object is predicted via an electronic computing device, as a function of the detected environment and the detected object, wherein a risk value for a planned trajectory is determined on the basis of a collision probability. A most probable impact constellation and accident severity for the most probable impact constellation is determined, wherein the collision probability and the accident severity is weighted in a risk value, and wherein the trajectory is determined as a function of the determined risk value.

This invention relates to a method for determining the collision probability of a vehicle (10) with an object (20, 25). The three-dimensional positions (x, y, z) and orientations of the vehicle (10) and the object (20) are detected. The vehicle (10) is approximated by at least one first geometry, wherein the at least one first geometry comprises a portion of the vehicle. The method is performed accordingly in the case of the object (20, 25). A first fuzziness (US1) and a second fuzziness (US2) are determined with respect to the geometry for either the vehicle (10) or the object (20, 25). A Minkowski difference (D') is formed for each combination of the at least one first geometry and the at least one second geometry. A third fuzziness (US3) is normalized by a transformation (TN). The transformation (TN) is used to calculate a computational volume (BK). The collision probability of the vehicle (10) with the object (20, 25) is determined based on the spatial union (D') of the computational volume (BK).

The invention discloses a space target collision early warning method based on GPU parallel computing and a J2 perturbation item, aims to solve the problems of high computing complexity and poor real-time performance of existing CPU processing space target collision risk assessment, and provides a multi-stage screening method based on GPU parallel computing and the J2 perturbation item. The method comprises the following steps: reading a TLE and calculating near / distant points and a reference check point at a GPU (Graphics Processing Unit); combining according to C (N, 2) and screening according to epoch, height and geocentric distance; taking a check point state as an initial value in a check interval, and adopting single-precision J2-RK iterative screening to obtain events NJ2pre and tJ2pre; the events are screened by using double-precision J2-RK in front and back check sections, and minimum distances distJ2 and tJ2 are output; and finally, SGP4 / SDP4 is used for parallel actuarial calculation to obtain a minimum distance distDC, a relative speed, a collision probability and the like. The method gives consideration to real-time performance and precision, significantly reduces the O (n) calculation cost, and is suitable for large-scale in-orbit target early warning.

An adaptive extended keeping reservation threshold probability mechanism system with resource watching window and dynamic back-off for contention-based 5G / B5G sidelink and a method thereof are disclosed. An adaptive extended Sigmoid mechanism can be applied to reduce a contention collision probability for the different types of flows contending a usage resource; a watching window can be applied to guarantee certain probability and reserve resource for a high priority flow; using dynamic truncated binary exponential (TBE) back-off mechanism can stagger the flows occurring resource collision to avoid the same consecutive collision, so as to effectively reduce contention collision probability, and improve resource usage rate and the probability of successful flow transmission. Therefore, the effect of minimizing collision probability and access delay and maximizing successful probability and throughput can be achieved.

The invention provides a path determination method, and belongs to the technical field of path planning, and the path determination method comprises the steps: obtaining at least two candidate paths; path evaluation information of each candidate path is determined, the path evaluation information comprises at least one of collision probability, smoothness and dynamics feasibility, the collision probability represents the feasibility of collision between the candidate path and an obstacle, the smoothness represents the smoothness of the candidate path, and the dynamics feasibility represents the feasibility of collision between the candidate path and the obstacle. The dynamics feasibility represents the degree that the candidate path meets the dynamics of the target object; and determining the candidate path of which the path evaluation information meets a preset condition from the at least two candidate paths as a target path. According to the embodiment of the invention, the path most suitable for the movement of the target object can be effectively determined, so that the accurate control of the movement of the target object is realized.

The application belongs to the technical field of robot control, and discloses a mobile robot dynamic obstacle avoidance planning system and method based on visual navigation, real-time motion parameters such as obstacle position, speed and acceleration are extracted based on pose semantic perception results, which are input into a social LSTM network together with obstacle semantic types and robot motion parameters, interaction behaviors such as avoidance and following among multiple obstacles are captured through a social pooling layer, the influence of robot motion on obstacle trajectory is quantified through an interaction modeling layer, and a trajectory probability distribution and a prediction confidence of 3-5 time steps are output, while a collision probability, a minimum collision time and a minimum control amount required for collision avoidance are accurately calculated; through a lightweight Transformer double-branch shared network, a pose solution and obstacle semantic segmentation share feature extraction backbones, and robot motion constraints are integrated to realize multi-task parallel output of single-frame data, and perception link delay is shortened.

The application relates to a satellite collision probability estimation method, device and readable storage medium. The satellite collision probability estimation method comprises the following steps: forward propagation of a non-Gaussian relative velocity probability density function to obtain a reference velocity histogram, so as to determine an initial parameter set of a Gaussian mixture model; every first preset time interval, a plurality of sets of distance residuals and angle residuals of a first satellite and a second satellite in a running state are updated, so as to update the parameter set of the Gaussian mixture model; every second preset time interval, the relative positions of the first satellite and the second satellite are updated, and the instantaneous collision volume of the first satellite and the second satellite is determined by using the separation axis theorem; the mean values of Gaussian components in the updated parameter set are substituted into a static spherical harmonic coefficient table for query, so as to obtain the relative position probability density of the first satellite and the second satellite; and the collision probability is obtained based on the instantaneous collision volume and the relative position probability density, so that fast and accurate estimation is realized.

The invention belongs to the technical field of automatic driving, and particularly relates to an automatic driving complex scene safety decision-making system based on digital twinning, which comprises an environment sensing module, a data processing module, a cloud decision-making module, a digital twinning rehearsal module and a vehicle judgment and execution module, the data acquisition module is used for acquiring vehicle surrounding data and vehicle state data; the data processing module is used for processing the original data of the environment sensing module in real time to generate an obstacle information list; the cloud decision module takes security as a main target; the digital twin rehearsal module is based on a high-precision vehicle dynamics model and a safety rule base; and the vehicle judgment and execution module is used for judging whether the cloud instruction is invalid. According to the automatic driving complex scene safety decision-making system based on digital twinning, the collision probability of vehicles in a complex intersection scene can be effectively reduced, and the real-time performance and safety of automatic driving decision-making are improved.

The invention discloses a multi-form robot motion control system based on AI perception decision. The multi-form robot motion control system comprises a perception fusion module, a multi-mode prediction module, a form management module, a motion control module and a control optimization module. The invention relates to the technical field of robot intelligent control, in particular to a polymorphic robot motion control system based on AI perception decision-making, according to the scheme, discrete morphologies are linearly combined into unified hybrid dynamics through micro-hybrid weights, and a multi-modal predicted safety violation probability and entropy regularization learning morphological strategy are combined to obtain a multi-modal robot motion control system. Smooth low-frequency switching and continuous balancing of energy consumption and risks are achieved, and coupling with model prediction control is achieved; the multi-modal collision probability is merged into model prediction control cost and constraint, hybrid dynamics is adopted for solving, high-frequency whole-body inverse dynamics is mapped into constrained joint torque, safety filtering is combined, priority avoidance and smooth executable control are guaranteed, energy consumption is reduced, and the task success rate and safety are improved.

Some implementations described herein relate to a system for generating identifiers. The system receives, from a device, a request to generate a plurality of identifiers. The system determines, based on receiving the request and by performing a parameter locking operation, a compute region parameter associated and a timestamp parameter. The system generates, based on the compute region parameter and the timestamp parameter, a set of one or more identifiers of the plurality of identifiers. Respective portions of each identifier, of the set of one or more identifiers, may indicate the compute region parameter, a version parameter associated with the parameter locking operation, the timestamp parameter, a counter value parameter, and an action parameter. The system processes, using a scrambling technique, the set of one or more identifiers and provides the set of one or more identifiers to the device.

The present application discloses a method, device, equipment and medium for sorting and conveying equipment directly distributed by a power supply station. The present application obtains a barcode collision probability model for each first transmission path; the barcode collision probability model is obtained based on the historical equipment transportation data statistics of all the first transmission paths; the first equipment to be packaged is classified, and the first equipment is placed on the corresponding conveyor belt according to the classification result; the classification result includes the position to be placed of the first equipment; with the conveyor belt as the starting point and the position to be placed as the end point, the optimal transmission path for the first equipment is searched from all the first transmission paths according to the barcode collision probability model. Through the present application, the equipment transportation efficiency can be improved while reducing the probability of the barcode falling or being damaged due to collision, thereby improving the accuracy of equipment sorting.

Techniques for determining a collision probability between a candidate trajectory associated with a vehicle and an object (e.g., a vehicle or pedestrian) in the vehicle's environment. In some cases, the techniques include selecting a set of sampled states, where each sampled state represents a predicted state (e.g., a predicted position and / or orientation) of the object at a future time. The set of sampled states may then be used to determine the collision probability. In some cases, the set of sampled states associated with a future time t may be determined based on: (i) a probability distribution (e.g., a Gaussian distribution) associated with the predicted object state at the future time t, and / or (ii) a covariance of the probability distribution. In some cases, the set of sampled states selected based on a distribution includes a set of sigma points each associated with a probability.

This invention provides a collision avoidance method and system for the reclaimer arm of a stacker-reclaimer, relating to the field of data processing technology. The method includes acquiring first, second, and third information; performing three-dimensional modeling based on the first information to obtain a three-dimensional model; simulating the stacker-reclaimer's operating scenario based on the second, third, and three-dimensional model to obtain the simulation results; obtaining fourth information; and obtaining a target collision avoidance scheme. This invention, through operating scenario simulation and risk simulation processing of the stacker-reclaimer, can pre-simulate operational conditions, accurately identify potential collision risks, effectively reduce the probability of collisions between the reclaimer arm and surrounding equipment, and utilizes a deep learning model for multi-objective optimization. The resulting target collision avoidance scheme not only avoids operational interruptions caused by frequent collision avoidance or accidental collisions but also enables the stacker-reclaimer to complete reclaiming tasks more smoothly and efficiently, reducing waiting time and operational adjustments, and improving operational efficiency.

The embodiment of the invention aims at providing an unmanned aerial vehicle control method and device for stock ground three-dimensional modeling and a medium. The method comprises the steps that multiple sets of collection points matched with a target area are generated according to the attribute of the target area to be modeled; wherein the number of collection points included in each group of collection points is different; performing iterative optimization on the multiple groups of collection points by adopting a genetic algorithm, and selecting a group of collection points with the maximum fitness in an iterative optimization result as target collection points; and planning an optimal path based on the target acquisition point, and controlling the target unmanned aerial vehicle to execute a modeling task according to the optimal path. According to the method, the number and the positions of the optimal collection points are calculated by carrying out collection point analysis iteration on the target area, so that the optimal path of flight modeling of the unmanned aerial vehicle is planned, the time required by blind repeated flight when the unmanned aerial vehicle executes a task is greatly shortened, the number of required unmanned aerial vehicles is reduced, and the collision probability is reduced; and the modeling task execution efficiency is improved.

This invention relates to the field of intelligent warehousing system technology, specifically disclosing an obstacle avoidance algorithm suitable for multi-wheel differential speed robot systems in warehousing environments. Based on the magnitude of the error obtained from obstacle position information, the algorithm sets collision probabilities for each location point in the environment, significantly improving the safety of the algorithm in practical applications. By outputting the optimal execution result in position space, it effectively eliminates errors in speed conversion, significantly improving the reliability and safety of obstacle avoidance, and providing a reliable obstacle avoidance solution for warehousing and logistics robots. The algorithm constructs an external contour polygon and obtains a position error shape polygon based on changes in the robot's movement position information; it combines these polygons to generate obstacle shapes containing position errors; it sets relative velocity obstacles and generates position obstacle information based on the relationship between the mass point and the combined polygon; and it sets the collision probability of the mobile robot's location area in the warehousing scenario based on the magnitude of the position obstacle and the error information in the environment.

The invention relates to a pedestrian-vehicle intelligent early warning system and method based on a mobile terminal. The system comprises a risk vehicle screening module which collects real-time position and speed data of pedestrians and vehicles, generates a position track sequence through Kalman filtering smoothing, calculates a relative distance and a speed difference, and judges through a preset threshold value to obtain a high-risk vehicle set; the collision probability calculation module extracts high-risk vehicle image features, obtains a vehicle recognition result through convolutional neural network matching, estimates real-time motion state parameters through extended Kalman filtering in combination with pedestrian trajectory prediction data, and calculates trajectory intersection points and collision risk probability; the early warning sequence generation module extracts the highest probability vehicle real-time distance to calculate the predicted collision time, if the predicted collision time is smaller than a preset threshold value, the predicted collision time is marked as an emergency level, and pushing queues are ranked and distributed according to a dynamic priority algorithm to obtain an early warning pushing sequence. By adopting the system, the data stability and the recognition accuracy can be improved, the early warning response time is shortened, and the accident probability is reduced.

Some implementations described herein relate to a system for generating identifiers. The system receives, from a device, a request to generate a plurality of identifiers. The system determines, based on receiving the request and by performing a parameter locking operation, a compute region parameter associated and a timestamp parameter. The system generates, based on the compute region parameter and the timestamp parameter, a set of one or more identifiers of the plurality of identifiers. Respective portions of each identifier, of the set of one or more identifiers, may indicate the compute region parameter, a version parameter associated with the parameter locking operation, the timestamp parameter, a counter value parameter, and an action parameter. The system processes, using a scrambling technique, the set of one or more identifiers and provides the set of one or more identifiers to the device.

The invention provides a material taking arm anti-collision method and system of a stacker-reclaimer, and relates to the technical field of data processing, and the method comprises the following steps: obtaining first information, second information and third information; performing three-dimensional modeling processing based on the first information to obtain a three-dimensional model; performing operation scene simulation of the stacker-reclaimer based on the second information, the third information and the three-dimensional model to obtain an operation scene simulation result; fourth information is obtained; and obtaining a target anti-collision scheme. Through operation scene simulation and risk simulation processing of the stacker-reclaimer, the operation condition can be rehearsed, the potential collision risk can be accurately identified, the collision probability of the reclaiming arm and the peripheral equipment is effectively reduced, multi-target optimization is performed by using the deep learning model, and the target anti-collision scheme is generated, so that the anti-collision efficiency of the stacker-reclaimer is improved. According to the stacker-reclaimer, operation interruption caused by frequent collision avoidance or accidental collision can be avoided, the stacker-reclaimer can complete the reclaiming task more smoothly and efficiently, the waiting time and operation adjustment are reduced, and the operation efficiency is improved.

A data transmission method and a device thereof are provided for tag access. The provided method includes: An answer device receives first signaling sent by a read / write device. The first signaling carries target flag information. The target flag information is used to determine the answer device. First flag information of the answer device matches the target flag information. The answer device determines a first slot, and sends first access information to the read / write device in the first slot. In the provided method, the first slot is determined, to avoid collision of different slots in a same slot in a next round, reduce a collision probability, and improve tag access efficiency.

The embodiment of the application provides a driving simulation display management method and system, which can solve the problem that the existence of the driver's visual blind area may cause the driver to fail to discover the surrounding pedestrians and vehicles in time, and increase the collision probability, but the driver is difficult to obtain the practice in this aspect after the driving test training or even the driving test. The method comprises the following steps: in the case that a student uses a terminal device to perform driving simulation training, acquiring position information of a target vehicle model and element models in a driving scene model driven by the student; calculating a position relationship between a student's visual field and the element models based on model contour parameters and the position information; in the case that a target element model is shielded by a body structure of the target vehicle, improving display transparency of the body structure of the target vehicle shielding the target element model, so that the student can observe the target element model under the body structure layer.

Systems and methods are provided herein for an AV to more efficiently, quickly, and accurately determine a likelihood of collision with another object, for example, by recursive triangulation. A candidate trajectory of the AV is then selected for controlling the AV based on the determined likelihood(s) of collision. According to one example, the likelihood of collision is determined by: 1) recursively triangulating a convex hull that defines all of the locations in which a collision would occur between the object and the AV (e.g., in a manner similar to the Sierpiński method), and 2) multiplying the area of each resulting triangular region by the value of a probability density that defines all of the locations in which a collision would occur between the object and the AV function in that region.

A collision avoidance system (1) for a ground vehicle is described, comprising a first transceiver device (4) associated with an obstacle (B), configured to generate and transmit one or more wireless signals (SG_B_i) at a pre-established time interval, the first wireless signal (SG_B_1) carrying an obstacle identification code (ID_1); a second transceiver device (3) associated with the ground vehicle (A), configured to transmit one or more wireless signals (SG_A_i) and receive the one or more wireless signals (SG_B_i) including the first wireless signal (SG_B_1) carrying the obstacle identification code (ID_1); a processing unit (20) configured to process collision data of the vehicle (A), comprising: a first calculation module (21) configured to determine, from the wireless signals (SG_B_i) and (SG_A_i), a trajectory (D_TRJ) of the ground vehicle (A) and the obstacle (B); a second calculation module (23) configured to determine, based on the trajectory (D_TRJ), a collision probability between the ground vehicle (A) and the obstacle (B); an alert module (24) configured to generate and send a collision probability signal between the ground vehicle (A) and the obstacle (B) according to a high collision probability between the ground vehicle (A) and the obstacle (B). The invention further describes a corresponding method and computer program.

The application discloses a kind of space debris on-orbit real-time autonomous avoidance method, system and spacecraft, belong to spacecraft on-orbit safety control technical field.The method is solidified and burned in on-board chip by light-weight AI model of knowledge distillation, structured pruning and 8-bit quantization;Adopt "standard strategy library+AI fine-tuning" architecture, call pre-stored orbit lag / advance / out-of-plane maneuver template, generate candidate trajectory by on-orbit fine-tuning of template parameter by solidified AI;Safety check is carried out based on simplified dynamics model, to ensure that meet off-target distance, fuel and attitude stability constraint;Build double-threshold emergency redundancy mechanism, select fuel optimal trajectory generation instruction execution in normal mode, when collision probability is too high or chip is abnormal, immediately call pre-stored emergency instruction sequence, directly execute after being quickly analyzed by propulsion controller.The application shortens response time from hour level to minute level, significantly improves the autonomous survival ability and mission reliability of spacecraft under extreme working conditions.

This invention relates to the field of space optimization technology and discloses a method for optimizing container loading space based on robot collaboration. This method constructs a multi-dimensional physical model of the package by acquiring point cloud data and weight distribution. A loading scheme including target pose, pressure tolerance threshold, and loading sequence is generated based on a reinforcement learning algorithm. The robotic arm generates motor current-position composite control commands based on a pre-trained grasping dynamics model to achieve precise grasping. During loading, the package pose is monitored in real time using a Kalman filter algorithm. When the deviation exceeds a threshold, a local spatial KD tree is constructed and the collision probability gradient field is calculated to generate a compensation scheme that satisfies stability constraints. Finally, the quadtree index is updated and fed back to the reinforcement learning algorithm for online optimization. This method effectively solves the efficiency decline problem caused by inaccurate grasping force control and accumulated execution deviations during robot loading, achieving efficient and precise automated loading.

This disclosure provides a control method, apparatus, medium and self-propelled device for a self-propelled device, the method comprising: receiving a command from a user to set a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters; determining a corresponding collision probability and / or cleaning miss probability based on the setting command; and performing cleaning of a target area based on the collision probability and / or cleaning miss probability.

This application relates to a method, apparatus, computer device, and storage medium for determining collision probability. The method includes: determining the number of collision detection operations based on model parameters in a discretized three-dimensional model of the propeller; performing collision detection operations based on the number of detections and recording the number of collision events; and determining the collision probability of an object colliding with the propeller based on the number of collision events and the number of detections. This quantitatively assesses the probability of an object colliding with the propeller, thereby determining the probability of the object passing through the propeller. Using this probability provides data support for the analysis of the rejection characteristics of aircraft propellers and the design of aircraft propellers, enabling researchers to design aircraft more accurately. This is of great significance for improving the overall resistance of aircraft to foreign object impacts and engine ingestion capabilities, and enhancing aircraft flight safety.