711 results about "Safety zone" patented technology

The invention relates to the field of vehicle intelligent control, in particular to a vehicle control method and a vehicle. According to the method provided by the embodiment of the invention, by monitoring the passive rotation amount of the vehicle door in real time, when the vehicle door is passively rotated due to external force, the target is always clear to guide the corresponding rotating vehicle door to the closed position or the safe area no matter whether the single vehicle door or the two vehicle doors are controlled to rotate at the same time. Therefore, in the whole control process, the vehicle doors cannot be simultaneously located in non-safe areas which are possibly in contact with each other, and the safety of the positions of the vehicle doors in the using process of the vehicle is guaranteed. Meanwhile, the whole process does not need manual processing of the user, and smoother and more efficient vehicle using experience is brought to the user.

The invention belongs to the field of unmanned aerial vehicle emergency control systems, and relates to a risk identification and emergency method when an unmanned aerial vehicle flies in an airspace adjacent to an expressway, and the method comprises the steps: obtaining the balance state of the unmanned aerial vehicle through constructing a six-degree-of-freedom dynamic model and incorporating environmental factors and control intentions; dynamically comparing the balance state with real-time data to obtain a state deviation, deducing the fault probability of the unmanned aerial vehicle according to the state deviation, and realizing sensitive early warning of possible faults of the unmanned aerial vehicle; besides, the method constructs a double-layer linkage framework of an electromagnetic safety boundary and a physical safety boundary, realizes safety risk identification in combination with a fault probability, and ensures that a safety area between the unmanned aerial vehicle and a motorcade on a highway can be represented by a risk value along with speed, motorcade density and interference intensity; the fault probability of the unmanned aerial vehicle flying in the air is considered, when the fault probability is larger than a preset threshold value, the out-of-control state of the unmanned aerial vehicle is judged, a corresponding control strategy is adopted, and the flight safety of the unmanned aerial vehicle during partial or comprehensive out-of-control is guaranteed.

The invention discloses a safety-enhanced trajectory planning method based on an Astar algorithm, and belongs to the technical field of intelligent robot navigation and path planning, and the method comprises the following steps: 1, constructing a grid map, and marking an obstacle region; 2, establishing a security evaluation mechanism, evaluating the surrounding environment of the path node, and quantifying a security index; 3, in a node expansion process, combining a heuristic item and a security index in a cost function to realize priority search for a security region during path selection; 4, key nodes of the obtained initial safety path are extracted based on a Douglas-Peucker algorithm to generate a rectangular safety corridor, and smoothing processing of the initial path is achieved based on a segmented Bezier curve. On the basis of guaranteeing path optimality, safety is used as an auxiliary guiding basis in the path searching process, and the path searching efficiency is improved. Therefore, consideration of the path length and the environmental risk is realized, and the navigation path with higher execution safety is generated.

The invention relates to a mechanical arm autonomous obstacle avoidance method and device based on deep reinforcement learning and a medium, and solves the obstacle avoidance problem of a mechanical arm in the process from an initial position to a target position through a reward function comprehensively designed in the deep reinforcement learning. Multiple aspects of obstacle avoidance of the tail end of the mechanical arm, obstacle avoidance of the mechanical arm body, self-collision avoidance, accurate reaching of a target position, smoothness of a movement track and the like are comprehensively considered. When an environment map is uncertain or obstacles dynamically change, the method has high adaptability. The working area of the mechanical arm is divided into the safety area, the warning area and the dangerous area, so that the mechanical arm can adopt a stricter obstacle avoidance strategy when the mechanical arm is in the dangerous area, and collision between the mechanical arm and the obstacle is avoided. Compared with the prior art, the method has the advantages of high success rate, wide application range, high reliability and the like.

The invention relates to a safe starting control method, device, equipment and medium for a bootstrap drive inverter, and the method comprises the steps: obtaining a detection voltage representing an output filter inductance voltage after responding to any starting event and before formally transmitting a drive signal; comparing the negative voltage with a preset negative voltage safety threshold value; only when the detected voltage is higher than the safety threshold, a driving enable signal is generated to allow the inverter to be normally started; otherwise, generating a driving blocking signal, carrying out detection and judgment again after waiting for preset time delay, and circulating the process until the system state enters the safe area; the method is realized by modifying a control algorithm, no power hardware needs to be added, the starting impact risk is eliminated with low cost, and the contradiction between the hardware limitation of a bootstrap drive circuit and the negative residual voltage possibly existing on the output inductance of the inverter is solved; therefore, the safety problem of direct connection between the impact current and the bridge arm during starting in an unfavorable initial state is solved.

The invention provides a construction site safety supervision method and system based on multi-mode intelligent perception, and relates to the technical field of highway construction supervision. A construction area is scanned through a 5G camera, multi-mode intelligent sensing data such as videos, positioning and environment sensors are fused, a three-dimensional model of a construction site is constructed, and the positions of equipment and personnel are accurately determined. Beidou positioning and safe area setting are combined, real-time safety detection is carried out, illegal intrusion of external vehicles and personnel is effectively prevented, and construction of equipment and personnel outside a safe area is avoided. According to the method, illegal behaviors of not wearing safety helmets and the like are intelligently identified by using AI, post-accident tracing is realized through the Internet of Things, accurate traffic guidance information is published in combination with Atdes and Baidu maps, the collision risk and potential safety hazards are reduced, and the safety of a highway construction site is comprehensively improved.

The invention relates to the technical field of geo-fence triggering, in particular to a multi-mode positioning data fused GEO fence triggering method and triggering system. The method comprises the following steps that according to the distance between equipment and the fence boundary, a layered positioning strategy is adopted to demarcate a safe area, a transition area and a critical area; when the device is located in the safe area, outputting a coarse position coordinate of the device and a corresponding coarse positioning confidence coefficient by adopting a low-power-consumption coarse positioning algorithm; when the equipment is located in the transition area, fusing the GPS data and the IMU data by adopting an adaptive fusion algorithm to obtain an intermediate fusion position, an intermediate fusion speed and an intermediate positioning confidence coefficient; fusing the multi-modal data when the equipment is located in the critical zone, and predicting the probability that the equipment invades the fence by combining a trajectory risk assessment algorithm based on the equipment acceleration and the distance between the equipment and the fence boundary. Through hierarchical positioning strategy and multi-modal data fusion, the problems of insufficient precision and high power consumption of a single positioning mode in a complex scene are solved.

The invention relates to the technical field of virtual reality redirection, and particularly provides a redirection walking method and system based on deep reinforcement learning, a terminal and a storage medium, and the method comprises the steps: obtaining the physical positions of a user in a real space and a virtual space in real time; dividing a walkable area of a user in a real space, and calculating a space feasible entropy in the real space; calculating a real-virtual environment state; based on the real-virtual environment state and the space feasible entropy, reward functions of deep reinforcement learning are calculated, and the reward functions comprise a position reward function, a space alignment reward function and a reset penalty function; judging whether the walking state of the user needs to be reset or not, and if not, using a position reward function and a space alignment reward function; and if so, calculating the optimal reset direction, and guiding the walking path of the user to the optimal safe area. According to the invention, the collision probability between the user and the obstacle is greatly reduced.

An apparatus for controlling autonomous driving of a vehicle is introduced. The apparatus may comprise a controller configured to determine, in a merging section on a road, at least one area of a safety area, a yield area, or a stop area, wherein the safety area may comprise a first part of the merging section designated for vehicles that have a right of way, the yield area may comprise a second part of the merging section designated for vehicles that should yield to traffic on the road, and the stop area may comprise a third part of the merging section designated for vehicles that should stop before merging onto the road, and determine a driving strategy of the vehicle for the at least one area, and a brake configured to, based on the driving strategy, adjust a speed of the vehicle.

The invention discloses a simulator supporting multiple debugging permissions. According to the embodiment of the invention, the simulator supporting multiple debugging permissions comprises a simulator management module which comprises a configuration unit, and the configuration unit is used for configuring the debugging permissions; a storage unit of the simulator hardware module is divided into a safe area and a non-safe area; the security area is used for storing security data, the non-security area is used for storing non-security data, and the debugging permission comprises a security mode and a limited mode; in the security mode, allowing access to the security area and the non-security area; and in the limited mode, the access to the safe area is prohibited, and the access to the non-safe area is allowed. According to the emulator supporting the multiple debugging permissions, debugging requirements of different security levels can be effectively distinguished, and flexible access control is provided for development and maintenance while data security is guaranteed.

The invention discloses an aircraft deployment method based on a dynamic airspace network and reinforcement learning, and relates to the field of air traffic management, and the method comprises the steps: obtaining flight information and task priority weight information of each flight in a historical time period and a current time period; dynamically dividing the airspace into an independent sub-airspace and a shared airspace by using flight information in a historical time period; calculating the safe area of each flight through a space-time buffer zone model, and determining a flight path according to the safe area; and according to the flight information, the airspace division result and the flight path, a release action instruction set including height adjustment, course correction and speed change is generated, and real-time deployment is performed on the flight. The technical effects of the invention lie in that airspace changes can be responded in real time, flight paths of flights are optimized, potential conflicts are reduced, and the airspace utilization rate is improved, so that the air traffic control efficiency and the flight safety are improved.

According to the motion planning method and device for the multi-mechanical-arm cooperative task, a large number of potential conflicts are actively avoided in the early stage of task allocation through division of a virtual wall and a safety area and a danger area, the difficulty and the calculated amount of follow-up track collaboration are remarkably reduced, and the success rate and the efficiency of planning are improved. Cost and load balance are considered in the task allocation stage; in the path point sorting stage, minimizing the total movement distance and the total completion time is taken as a target; and track generation adopts a time optimal algorithm. The layered decoupling design avoids the huge calculation overhead of centralized planning, and meanwhile, the quality of a final solution is ensured through the optimization strategy of each stage. The innovative cost function takes collision distance into consideration, and guides the planner to select a safer path. Through layered and ordered collision solution strategies, such as deceleration, local re-planning and optimal waiting, it is ensured that a collision-free solution can be always found in a complex dynamic environment, and robustness is high.

An autonomous mobile device (AMD) may move around a physical space while performing tasks. The AMD may have sensors with a field of view (FOV) facing forward. As the AMD moves forward, a safe region is determined based on data from those forward-facing sensors. The safe region describes a geographical area that is clear of obstacles during recent travel. If the AMD moves outside of the FOV, such as moving backwards, a check is made as to whether the AMD remains within the safe region. If a portion of the AMD moves beyond the safe region, the AMD stops. This prevents the AMD from colliding with obstacles that are outside of the safe region and also outside of the FOV while moving.

The invention relates to the technical field of intelligent security and protection, and discloses an intelligent security and protection alarm method and system based on an intelligent park. The method comprises the following steps: acquiring original security and protection data by using sensing equipment arranged in a smart park; performing standardization and redundancy elimination processing on the original security and protection data, dividing safety areas of the park through a pattern recognition algorithm, calculating a load intensity index of each area, and generating a security and protection situation summary; according to the security situation summary, a heuristic search algorithm is adopted to determine alarm trigger parameter initial values including detection sensitivity and alarm intervals, and a basic alarm parameter group is generated; performing nonlinear correction on the basic alarm parameter group, and outputting an environment perception alarm parameter group; training the historical security data set by adopting a neural network model, and analyzing the interaction between the load and the threat to obtain a threat diffusion model; and comparing the threat diffusion model with the real-time security data points, performing difference measurement, reconstructing alarm trigger logic according to a measurement result, and completing autonomous regulation and control of security and protection of the smart park.

The invention discloses an under-mine environment accurate positioning system based on a UWB technology, and relates to the technical field of data processing and positioning, an underground area is divided into a safe area and a dangerous area by obtaining the structure risk value of each sub-area and combining the structure risk value and the position information of the corresponding sub-area, and the safe area and the dangerous area are accurately positioned. A plurality of rescue robots are arranged in the underground area; acquiring position information of the mobile tag, displaying the position information on an electronic map, generating an air quality coefficient, and dividing the plurality of sub-regions into risk regions and safety regions according to the air quality coefficient; and sending inquiry information to the miner, acquiring a corresponding safety coefficient, and if the acquired safety coefficient is lower than a safety threshold value, planning a support path to the miner for the rescue robot, so that the rescue robot rescues the miner along the support path. After the miner is found according to the position information of the miner, the miner is rescued through guidance of the rescue robot, and the miner is prevented from getting lost and being lost.

The invention relates to the technical field of environment monitoring, in particular to an environment parameter real-time early warning method and system for a digital chicken house, and the method comprises the following steps: collecting ammonia gas concentration, temperature and humidity and illumination intensity data in a chicken house, uniformly integrating and generating a monitoring record, extracting a safety interval, counting the exposure time of ammonia gas, and judging a multi-factor deviation state; and carrying out conjoint analysis on environment distribution change, and outputting a risk state and early warning information. According to the method, multi-source environment data are integrated through a unified time reference, the time sequence consistency among parameters is improved, the identification capability of low-concentration long-term exposure is enhanced by screening an ammonia gas safety interval and counting the exposure duration, and a multi-factor time sequence offset feature is constructed by collecting the deviation state of temperature and humidity and illumination intensity; the conjoint analysis of exposure and deviation distribution is combined, the continuity and accuracy of environmental risk judgment are improved, high-risk time periods and monitoring data thereof are extracted, and the positioning and response efficiency of abnormal states is enhanced.

The invention relates to the field of vehicle intelligent control, in particular to a vehicle control method and device, electronic equipment and a storage medium. According to the method, judgment is not made only according to tiny changes of the position of the vehicle door, but the passive rotation amount of the vehicle door is obtained as a key initial condition. And when it is detected that the passive rotation amount is not zero, the state of the vehicle door is not directly changed, and whether the first vehicle door meets the preset condition or not is further judged. Only when the first vehicle door meets the preset conditions that the memory function of the maximum opening angle of the vehicle door is executed within the preset time or the release position of the first vehicle door is located within the angle subset range of the safety area, the first vehicle door and the second vehicle door are allowed to execute the active rotation function. Therefore, even if the passive rotation amount is caused by slight position change, as long as the first vehicle door does not meet the preset condition, the back door is still not locked at will and loses the electric function, so that the situation that the vehicle door function is abnormal due to unintentional fine operation of a user is effectively avoided.

The invention discloses an intelligent monitoring and early warning method and system for a dangerous large project on a building construction site, and the method comprises the steps: carrying out the fusion processing of multi-source data, such as displacement, inclination and axial force, collected by edge Internet of Things equipment, extracting the characteristics of structural deformation and load change, and constructing a comprehensive situation representation; a high-risk area and a safety area of a construction site are identified by adopting clustering analysis, a spatial proximity relationship between the areas is established, a risk coupling degree is calculated, and a differentiated monitoring strategy is delimited according to the spatial proximity relationship; performing time sequence density analysis on the abnormal event data, fitting a risk evolution curve, positioning a situation mutation node, and establishing association mapping of construction conditions and risk steps; according to the method, a transmission path is tracked based on a risk attenuation rule, a preliminary early warning sequence is generated, an early warning trigger threshold value is determined through adaptive grading and boundary matching, a graded early warning instruction is output after gradient verification, and timely and accurate early warning information can be provided for safety management and control of dangerous engineering.

The invention relates to a robot dog dynamic balance and fall self-recovery method and device for a complex terrain, and the method comprises the steps: building a robust local elevation map through fusing multi-sensor data and quantifying the motion uncertainty of a robot; and a safe foot region set defined by the convex polygon is extracted through geometric feature analysis and plane segmentation. Then, collaborative planning of the trunk and the landing point is carried out in combination with a user instruction and the region set. In a control layer, a nonlinear model predictive control algorithm is adopted, a safety area is used as a hard constraint, and incomplete speed constraint is applied to a wheel type foot end, so that an optimized trunk track and a foot end force reference are output. The whole-body controller converts an upper-layer instruction into an accurate joint torque through a multi-task optimization framework with a weight. When instability is detected, the system can autonomously plan and execute a recovery action sequence including curling, controllable rolling and cooperative supporting.

The invention discloses a nuclear magnetism safety interval confirmation device, and the device comprises a quantum noise suppression module which is used for eliminating radar signal noise caused by the quantum tunneling effect on the surface of a metal object in an ultrahigh field intensity environment; the multi-sensor fusion center is used for integrating the radar cleaning signal, the real-time magnetic field intensity data and the terahertz penetrability detection result to generate fused object position information; the dynamic magnetic field reconstruction engine is used for calculating a magnetic field distortion gradient by analyzing Hall sensor array data and a magnetohydrodynamic model in real time; the nonlinear danger scoring module is used for receiving object distance, magnetic field gradient, existence time and object classification data; the hierarchical response system is used for triggering a corresponding response according to the danger score; and the cesium atomic clock synchronization module is used for eliminating a timing error caused by a time crystal effect through a block chain timestamp verification mechanism. According to the invention, risk closed-loop control in a high-field-intensity MRI environment is truly realized.

The invention discloses a multi-ship cooperative target searching method and system for a complex searching scene, and the system is disposed on a ship body, and comprises an information collection module, a top task cooperative distribution module, a main control module, a communication module, a ship motion decision module, and a shore end interaction control center. The invention provides a method for realizing multi-ship collaborative collision avoidance motion planning based on an MADDPG algorithm in combination with an APF algorithm. An APF-MADDPG model is constructed, a network structure is trained through LSTM, parameters are adaptively designed by using a trained deep network, so that each intelligent ship can efficiently generate a navigation collision avoidance route, in addition, a regular and symmetrical elliptical safety area is set for the ship, and the safety area is divided into 18 areas. The refined distance information between the ship and other intelligent ships in each safety detection area and the collision risk degree are added into the state space of each ship, and the robustness and generalization ability of the model are enhanced.

The invention relates to the technical field of ship offset early warning, and provides a ship offset early warning method for a deep-sea mining in-situ pilot production system, which can solve the problem that the existing mother ship offset monitoring mode is too simple, improve the accuracy of judging the position of a ship body and perform effective early warning. Comprising the following steps: S100, establishing an information transmission network and carrying out data acquisition; s200, carrying out coordinate conversion on the collected real-time longitude and latitude information of the ship and the vehicle, and calculating a relative distance between the ship and the vehicle; s300, calculating a ship offset area of the mining system, calculating an allowable offset of a mining ship relative to a mining vehicle, dividing operation states according to the offset, and determining a reasonable ship offset area map; and S400, the ship deviation safety early warning area is built in a system early warning program, monitoring data are read at regular time, monitoring information such as environment monitoring information, ship-vehicle distance and the like and umbilical cable length monitoring information are read in real time, and the ship deviation state is judged in real time according to the ship deviation safety area.

The invention discloses a safe area management method and system for a zoo, and relates to the field of animal positioning. The safe area management method for the zoo comprises the following steps: monitoring an image and multiple environmental parameters of an animal activity area in real time; identifying the position and the moving track of the animal in the image; when it is detected that the position and the moving track of the animal are abnormal, early warning is given out; performing three-dimensional modeling on the animal activity area; identifying a dynamic obstacle in the animal activity area; and analyzing a movable area and a movable path of the animal according to the dynamic obstacle. According to the invention, recognition and prediction of complex animal behaviors are realized, and an early warning mechanism of animal abnormal behaviors is perfected.

The invention provides a dynamic security division method and related equipment, and relates to the technical field of artificial intelligence. The method comprises the steps that environment element description information and user element description information are obtained from a spatial ontology knowledge model, the environment element description information is information for describing environment element categories, and the user element description information is information for describing user element categories; according to a preset security interaction rule, security interaction information between the environment element description information and the user element description information is constructed, and the security interaction rule is used for determining whether a security interaction relationship exists between the environment element and the user element; performing security assessment according to the security interaction information to obtain a security assessment result; and carrying out security division on the area in the application scene space according to a security evaluation result. According to the method and the device, security area division is carried out for the user in the application scene space, the space security guarantee of family members is improved, and the application scene space customized for area security is provided for the user.

The invention provides a head-eye posture fused driver state grading intervention method and system, and the method comprises the steps: dividing a fixation region which comprises a safety region, an alarm region and a dangerous region based on an in-vehicle three-dimensional coordinate system; calculating an initial line-of-sight vector according to the driver face key points, obtaining a final line-of-sight vector by combining line-of-sight deviation angle correction, and obtaining a fixation point coordinate based on the eye point coordinate and the final line-of-sight vector; based on fixation point coordinates and fixation area matching, the driver fixation area category is judged; and acquiring the current vehicle speed and the fixation duration in the fixation area, inputting the current vehicle speed and the fixation duration into a pre-trained decision model to obtain a graded intervention strategy, and executing an intervention action according to the strategy. The accuracy of the fixation point position is ensured through fusion of the head posture and the sight line deviation; a grading intervention strategy is obtained by combining the fixation point position, the fixation duration and the vehicle speed, interference to normal driving is reduced, effective early warning can be achieved in the risk accumulation stage, and the method has adaptability to complex vehicle use scenes.

The invention discloses a pressure regulating and speed regulating system of a drilling machine derrick lifting hydraulic cylinder. The pressure regulating and speed regulating system comprises a hydraulic system, a derrick area, a regulating control box and a safety area display monitoring unit. The adjusting control box is connected with the hydraulic system, the derrick area and a diesel generating set of an original lifting system through lines, and the hydraulic system is connected with the diesel generating set and the derrick area through lines. The diesel generating set supplies power to the whole system, the derrick area measures the inclination angle of a derrick and the displacement of an oil cylinder and transmits the measurement result to the adjusting control box, the adjusting control box sends an instruction to the hydraulic system according to the measurement result to conduct system pressure reduction, and the safety area display monitoring unit is used for displaying various parameters of the system. And an operator can check conveniently. The invention further discloses a method for regulating the pressure and the speed of derrick lifting by using the system. The device solves the problems that an existing system does not have closed-loop control, misoperation is prone to occurring, out-of-tolerance cannot be adjusted by itself, and equipment failures are caused due to the fact that pressure reduction cannot be achieved.

The present application relates to the technical field of robot safety, and discloses a safe area-based protection method, apparatus and device, and a safe area-based configuration method, apparatus and device. The method comprises: acquiring safe area configuration information for at least one reference object, wherein relative distance information between different reference objects meets a preset distance condition, the reference object includes a robot, and the robot is a robot in a motion state; on the basis of the safe area configuration information corresponding to each reference object, generating a safe area corresponding to each reference object; and when it is detected that a moving object is present within an area range of the safe area corresponding to the at least one reference object, and attribute information of the moving object meets a preset adjustment condition, adjusting the motion state of the robot. The present application aims to solve safety problems in the working process of existing industrial robots.

The present application relates to the technical field of intelligent city infrastructure safety monitoring, and discloses a real-time response system for safety events of intelligent pedestrian tiles. The system comprises a real-time state monitoring module, a dynamic event detection module, a multi-dimensional event difference analysis module, a safety area correlation positioning module and a self-adaptive response generation module. The sensor array collects tile pressure distribution, surface humidity and temperature fluctuation data, and combines historical event data to construct a dynamic prediction model to output potential safety event probability values. A multi-dimensional difference analysis generates an event-level difference feature matrix, and a spatial topology network and environmental parameters are used to generate a safety event heat distribution map and locate high-risk areas. Finally, response parameters are adaptively configured. The system realizes real-time sensing, accurate positioning and dynamic response of safety events in urban pedestrian areas.

A method for operating a computing device for a control unit of a motor vehicle. The computing device including a processor core, and is configured to control an exchange of data between a connectivity zone and a security zone. The security zone includes at least one component which is necessary to drive the vehicle and has an elevated relevance with regard to safety. The connectivity zone including at least one component whose operation requires communication outside of the vehicle but is not required to drive the vehicle and does not have an elevated relevance with regard to safety. At least one first program executable by the computing device is assigned to a non-trustworthy zone, and at least one further program is assigned to a trustworthy zone. The component of the connectivity zone is assigned to the non-trustworthy zone, and the component of the security zone being assigned to the trustworthy zone.

In a safety boundary generation method, an image of a surrounding environment captured by a camera in a head-mounted display device is received. Three-dimensional reconstruction is performed based on the image of the surrounding environment to obtain a three-dimensional environment model. The three-dimensional environment model indicates a three-dimensional representation of the surrounding environment of a user that wears the head-mounted display device. Ground detection on the three-dimensional environment model is performed to obtain a plurality of ground boundary points. Each of the plurality of ground boundary points is an intersection point between a ground plane and an obstacle in the surrounding environment. A safety boundary is determined based on the plurality of ground boundary points. A region enclosed by the safety boundary is a safety region for the user to interact with the head-mounted display device. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.