293results about How to "Avoid collision risk" patented technology

The invention discloses an automatic ship berthing and leaving method based on video monitoring and image recognition, which comprises the following steps: S1, acquiring real-time video data, and carrying out image preprocessing; s2, extracting target feature information by using a target detection model based on an OfficientDet algorithm; s3, generating environment sensing information by using a multi-modal sensor fusion technology; s4, based on the environment perception information, constructing and updating a three-dimensional dynamic map of the surrounding environment of the ship in real time; s5, performing global path planning by adopting a fast extension random tree-star algorithm; s6, local dynamic obstacle avoidance is carried out in combination with a two-stage neural network algorithm; s7, based on the global path planning result and the local dynamic obstacle avoidance strategy, the adaptive control system accurately adjusts the speed, course and attitude of the ship according to the real-time environment change; and S8, performing big data analysis and historical data mining by using the cloud computing platform. According to the invention, image recognition and deep learning technologies are utilized to realize automatic berthing and unberthing of the ship, and the method has the advantages of high efficiency and accuracy.

The invention relates to the technical field of vehicle control, in particular to an unmanned vehicle control method based on deep learning, and the method comprises the following steps: collecting the multi-modal data of weak participants in a road environment in real time, and recognizing the weak participants; the behaviors of the weak participants at the next moment are predicted through multi-dimensional information fusion, and behavior intention prediction of the weak participants is carried out; the path planning and control strategy of the vehicle is adjusted in real time through the self-adaptive decision control module; and when the predicted behavior intention of the weak participant has high uncertainty or potential risk, an emergency avoidance mechanism is automatically triggered, the risk level of the current traffic environment is dynamically evaluated, an optimal avoidance path is generated, and emergency stop or detour operation is executed. According to the method, double guarantees of high-dimensional analysis of behavior intentions of participants and real-time control of vehicles are combined, and the driving safety in a complex traffic scene is ensured.

The invention discloses an intelligent scheduling method and system for an aircraft jumping hangar. The method comprises the steps that the hangar obtains local aircraft flight operation data in real time; the hangar acquires stop request information of the jump flight aircraft in real time, performs data communication with the aircraft control center in real time according to the stop request information, acquires flight operation data of the aircraft, and performs data synchronization on the state of the aircraft and the hangar; acquiring real-time scene operation data of the hangar, and performing aircraft cluster scheduling according to the real-time scene operation data of the hangar; the state data of the hangar and the aircraft are obtained and synchronized in real time, deep reinforcement learning and mixed integer programming are combined, the scheduling strategy is dynamically adjusted, load balancing and optimal resource utilization are achieved, the problems of scheduling chaos and errors caused by communication faults in an existing hangar scheduling system are solved, and the scheduling efficiency is improved. The DRL model optimizes task allocation, ensures load balance and reduces waiting time by learning real-time states of an aircraft and a hangar.

The invention discloses a well industrial and mining unmanned driving simulation test method based on cluster hardware-in-the-loop, and relates to the field of unmanned driving simulation, and the method comprises the steps: constructing a simulation environment of an operation map; building a cluster hardware-in-the-loop simulation system on the constructed operation map simulation environment, and simulating an ore drawing machine, a draw shaft, a transport vehicle and a carry-scraper on the simulation system; when a plurality of loading points or unloading points exist in the constructed operation map simulation environment, calculating an optimal loading point, an optimal unloading point and an optimal driving route of each transport vehicle to realize transport vehicle scheduling simulation; the cluster hardware-in-the-loop simulation system adopts a distributed calculation architecture to perform parallel simulation calculation on a plurality of ore drawing machines, draw shafts, carry-scrapers and transport vehicles. Aiming at the low simulation test efficiency of the underground unmanned vehicle in the prior art, the underground simulation test efficiency is improved.

The invention relates to the technical field of crane control, in particular to an intelligent tower crane anti-collision accurate hoisting system based on multi-sensor fusion, which comprises a data acquisition module, a data processing module, a safety early warning module, a control execution module, a data processing module, a data processing module and a control module, an alarm module electrically connected with the safety early warning module and the data processing module and used for receiving the alarm signal sent by the safety early warning module; a hoisting control instruction is generated based on the alarm signal and the real-time three-dimensional position coordinates of the hoisted object sent by the data processing module; according to the method, the lifting control instruction is executed, the lifting arm angle, the rotation angle and the lifting height of the tower crane are adjusted, accurate lifting and anti-collision control are achieved, and the safety, accuracy and efficiency of the tower crane are comprehensively improved through organic combination of advanced technologies such as multi-sensor fusion, an intelligent algorithm and self-adaptive control.

The invention relates to a mechanical arm dynamic obstacle avoidance method based on intelligent task supervision. The mechanical arm dynamic obstacle avoidance method comprises the following steps that S1, a position information set is collected; s2, basic behaviors and composite behaviors are constructed for null-space behavior control based on the state of the mechanical arm and the requirement of trajectory planning, and behavior priorities are set as action information; s3, a control obstacle function is set based on the safety distance requirement of the mechanical arm; s4, constructing a deep reinforcement learning training model; and S5, the position information set and the action information are input into a deep reinforcement learning training model, a corresponding reward is obtained according to a set reward function, and if the distance, obtained according to the information, between the tail end of the mechanical arm and the obstacle is smaller than the minimum safety distance, input of the mechanical arm is taken over by a control obstacle function. The flexibility and adaptability of the mechanical arm in the dynamic obstacle environment are effectively improved, and collision accidents are avoided.

The invention relates to a multi-ship anchoring scheduling path planning method based on an improved RRT algorithm. The method comprises the following steps: S1, constructing a multi-ship anchoring scheduling destination selection mechanism; s2, constructing a multi-ship anchoring scheduling evaluation index selection mechanism; s3, calculating ship scheduling priorities according to the multi-ship anchoring scheduling evaluation indexes; s4, constructing a multi-ship anchoring scheduling collision avoidance decision-making mechanism; and S5, calculating a multi-ship anchoring scheduling path planning result. The method can be used for coping with the situation that multiple ships need to be moored and dispatched at the same time, the berthing sequence and the sailing path of the ships are optimized, and therefore the ship anchoring dispatching waiting time is minimized, the sailing distance of all dispatched ships is reduced as much as possible, and the berth utilization rate is increased; the method is of great significance in the aspects of multi-ship scheduling in complex water areas, ship emergency evacuation, comprehensive management of water transportation hubs and the like.

The invention discloses a vehicle path planning method in a V2X environment, and particularly relates to an improved RRT path planning method based on a dynamic search step size of tabu search. The method mainly comprises the following steps: initializing a starting point and an ending point, taking the starting point as a root node of a tree, and generating a search map according to real-time road and obstacle information by using a V2X technology; randomly generating points within a limited angle, generating a new node according to a dynamic search step length, detecting whether the new node intersects with an obstacle in the map, and if so, abandoning the node; if the current node is not intersected with the new node, adding the new node into the RRT spanning tree, adding a path between the current node and the new node into the path RRT spanning tree, and adding the accessed nodes into a taboo list to avoid re-accessing the nodes in subsequent search; checking whether the new node is close to the target point, if so, stopping searching, and finishing path planning; and repeating the above steps until the path connecting the starting point and the target point is found or the maximum number of iterations is reached.

The invention discloses a BIM (Building Information Modeling) and genetic algorithm-based tower crane optimization method, system and equipment and a storage medium, and the method comprises the following processes: selecting a tower crane model according to a construction environment and requirements; carrying out BIM modeling on the construction site to obtain a BIM model, and determining the position range of the tower crane; based on the construction site data and the tower crane model in the BIM model, establishing a tower crane mathematical model, and establishing a target function with minimum construction time and cost as a target; and solving the target function by adopting a genetic algorithm to obtain an optimal tower crane arrangement position. The optimization efficiency is improved, the collision risk is avoided, the cost is reduced, and the safety is improved.

The invention discloses an intelligent material rack for SMT material tray storage and taking. The intelligent material rack comprises a material rack body and a plurality of supporting regulation and control frames installed on the material rack body. A plurality of first tray boxes and second tray boxes which are arranged in a staggered mode are installed on the top face of the supporting regulation and control frame, and a self-locking driving assembly for driving the first tray boxes and the second tray boxes to synchronously and reversely move is arranged in the supporting regulation and control frame. One SMT material tray is correspondingly placed in each first material tray box and each second material tray box, clamping blocking frames are connected to the two sides of the top face of each first material tray box and the two sides of the top face of each second material tray box, and magnetic telescopic clamping pieces which are magnetically attracted or repelled with the clamping blocking frames are arranged at the tops of the clamping blocking frames; and clamping and jacking assemblies for clamping or jacking the SMT trays are symmetrically arranged in each first tray box and each second tray box. According to the SMT charging tray, the problem that the adjacent SMT charging trays are difficult to take and place is solved, and meanwhile the problem that workers move back and forth when taking and placing are solved.

The invention relates to the technical field of computers, and discloses a steering wheel control method based on an SBW system, and the method comprises the steps: obtaining corresponding real-time steering angle data through a steering angle sensor installed on a steering wheel, detecting a steering intention corresponding to a driver based on the real-time steering angle data, converting the steering intention into a steering electric signal, and outputting the steering electric signal; transmitting the steering electric signal to an electronic control unit through a high-speed communication bus; corresponding vehicle speed data and corresponding environment data in the current state of the vehicle are obtained, and the electronic control unit determines corresponding target steering torque based on the real-time steering angle data, the vehicle speed data and the environment data; a corresponding control instruction is generated based on the target steering torque, a motor installed on a steering mechanism is driven to generate corresponding steering torque according to the control instruction, and real-time road surface feedback corresponding to the driver is collected. The performance of the steering system can be improved.

The invention discloses a vehicle path planning method in a V2X environment, and particularly relates to an RRT vehicle path planning method based on vehicle trajectory prediction in the V2X environment. The method mainly comprises the following steps of initializing a starting point and an ending point of an algorithm, acquiring driving information of surrounding vehicles by using a V2X technology, generating an initial sampling area, predicting tracks of the surrounding vehicles in a period of time in the future according to a vehicle track prediction algorithm, and taking the predicted tracks as predicted virtual obstacles. Adjusting the initially generated sampling area, adopting an optimized sampling area strategy to obtain an optimized sampling area, taking a starting point as a root node of the tree, randomly generating a new node in a fan-shaped area with a specified direction angle at a fixed step length, and checking whether the new node intersects with an obstacle or not. And if no collision exists, adding the node and the path into the RRT tree. And if the new node is close to the terminal point, stopping searching. Otherwise, continuing iteration until the path is found or the maximum number of iterations is reached.

The embodiment of the invention provides an unmanned aerial vehicle inspection method and device for power transformation equipment. The method comprises the following steps: acquiring a virtual substation model of a target substation, wherein the virtual substation model is generated by performing three-dimensional model construction on the target substation and comprises a plurality of candidate virtual substation equipment areas and a plurality of candidate virtual visual positioning identifiers; determining at least two target virtual visual positioning identifiers from a plurality of candidate virtual visual positioning identifiers included in the virtual substation model in response to an inspection triggering operation on a target virtual power transformation equipment region in a plurality of candidate virtual power transformation equipment regions included in the virtual substation model; and generating an unmanned aerial vehicle inspection route based on the at least two target virtual visual positioning identifiers. According to the scheme, the inspection route can be automatically generated on the intelligent inspection platform according to the arrangement of the virtual power transformation equipment in the transformer substation model, and the unmanned aerial vehicle in the transformer substation is pointed to fly to inspect the power transformation equipment through the inspection route.

The invention discloses a vehicle motion trail prediction method and system, and belongs to the technical field of surface mine unmanned driving. The method comprises the following steps: preprocessing vehicle motion trail data collected in real time, inputting the preprocessed vehicle motion trail data into a pre-trained machine learning model, and predicting to obtain a motion trail of a vehicle at a future moment; determining the grade of the collision risk according to the predicted motion track of the vehicle at the future moment, and providing an early warning signal according to the grade of the collision risk; the method is suitable for mining vehicles, and can solve the problems of low prediction precision and slow response speed.

The present invention relates to a multi-ship anchoring scheduling path planning method based on an improved RRT algorithm, comprising the following steps: S1, constructing a multi-ship anchoring scheduling destination selection mechanism; S2, constructing a multi-ship anchoring scheduling evaluation index selection mechanism; S3, calculating the ship scheduling priority according to the multi-ship anchoring scheduling evaluation index; S4, constructing a multi-ship anchoring scheduling collision avoidance decision-making mechanism; S5, calculating the multi-ship anchoring scheduling path planning result. The present invention can be used to deal with the situation where multiple ships need anchoring scheduling at the same time, optimize their berthing sequence and navigation path, thereby minimizing the ship anchoring scheduling waiting time, reducing the navigation distance of all scheduled ships as much as possible, and improving the berth utilization rate; it has important significance in multi-ship scheduling in complex waters, emergency evacuation of ships, and comprehensive management of water transportation hubs.

The invention discloses an intelligent formwork erecting robot which comprises a mechanical claw, a vehicle body, steering wheels, an obstacle avoidance camera and a mechanical arm. The plurality of steering wheels are respectively mounted at the bottom of the vehicle body at intervals, so that the vehicle body can move on a formwork erection site through the steering wheels; a plurality of mounting storage grooves are formed in the vehicle body, so that the plurality of mechanical arms can be folded and stored in the plurality of mounting storage grooves; each mechanical arm is a folding telescopic mechanical arm, one end of each mechanical arm is rotatably connected into the corresponding mounting storage groove through a rotating shaft, the other end of each mechanical arm can extend to the outside of the vehicle body, and a mechanical claw used for erecting a formwork is mounted at the other end of each mechanical arm; the obstacle avoidance cameras are embedded in the outer wall of the vehicle body, and the multiple obstacle avoidance cameras are arranged in the circumferential direction of the vehicle body at intervals. The invention relates to the technical field of constructional engineering, and can solve the problems of complex structure and high cost of a formwork erection robot in the prior art.

The invention relates to the technical field of vehicle driving intelligent control based on the Internet of Vehicles, and discloses a vehicle driving intelligent control method based on the Internet of Vehicles, which is characterized in that obtaining of starting place and destination information of a user is the basis of a navigation system, it is ensured that an optimal path from the current position of the user to the destination can be accurately calculated, and the system generates a plurality of paths; distance, time, road conditions and the number of traffic lights are comprehensively considered, diversified choices are provided, the traffic lights serve as segmentation points to divide routes, the system carries out refined path analysis, the driving strategy of each road section is adjusted in a personalized mode, the overall driving efficiency is improved, lanes of each road section are distinguished in detail, the system can accurately plan and adjust the routes, and the driving efficiency is improved. A high-precision map and real-time vehicle information provide data support for dynamic adjustment of a driving strategy, and by analyzing road and vehicle data, the system can recognize dangerous points in advance and optimize a driving path to help a user to make an optimal choice.

The unmanned ship global path planning method provided by the invention covers the whole process from departure to sailing to an open sea area and then to entering the port, firstly sets detailed sailing routes and parameters, distinguishes three routes of departure, open sea area and entering the port, configures or dynamically calculates the resolution and safety distance of each segment of A star planning grid, and finally calculates the global path of the unmanned ship according to the resolution and safety distance of each segment of A star planning grid. Dividing a planning area according to navigation routing points, obtaining sea chart obstacle data in the planning area, performing data point interpolation processing, planning a path by applying an A star algorithm of a corresponding grid resolution under the condition of considering the safe distance of the unmanned ship aiming at each section of area, and performing path point simplification smoothing to ensure that all obstacles are avoided; and finally, seamlessly splicing the three paths of departure, open sea area and arrival to form a complete and safe global navigation path. According to the method, specific requirements of different sea areas are considered, a more refined path planning strategy is provided, an efficient and safe navigation scheme is provided for the unmanned ship, and the accuracy and efficiency of path planning are improved.

The invention belongs to the technical field of underwater terrain detection, and provides a distributed multi-AUV underwater area detection method based on an anti-cluster game, and the method carries out the following steps for any one of a plurality of AUVs: carrying out underwater terrain detection based on the position of the AUV at the current moment and an effective coverage distance range, and carrying out the self-updating of an information graph carried by the AUV; information graphs carried by the AUV and information graphs carried by other AUVs in the neighborhood of the AUV are mutually updated; executing an optimal dynamic response algorithm based on a local game to determine the positions of the AUV and the next target point of other AUVs in the neighborhood of the AUV; determining a target velocity vector of the AUV at the next moment based on an anti-cluster strategy; and updating the current moment and returning to execute the first step until the detection of the underwater area is completed or the end moment is reached. According to the method provided by the invention, the coverage efficiency of the plurality of AUVs for distributed exploration of the underwater area can be effectively improved.

The invention provides proton treatment equipment and a control method thereof, and the proton treatment equipment comprises an equipment body which is provided with a treatment cabin; a treatment bed; a detection assembly; a treatment component; the processor is used for controlling the treatment bed, the detection assembly and the treatment assembly to work; the processor is further used for controlling the detection assembly to collect CT image data of the focus of the patient. Performing reconstruction processing on the CT image data to generate a three-dimensional CT image of the focus of the patient, and performing registration processing on the treatment plan image of the patient and the three-dimensional CT image to generate positioning deviation data; based on the positioning deviation data, controlling the treatment bed to drive the patient to move to a corresponding treatment position; when the patient moves to the preset treatment position, the treatment assembly is controlled to conduct proton beam irradiation treatment on the focus of the patient. According to the invention, the treatment cabin with the closed skin design is adopted, the collision risk caused by exposure of a mobile device is avoided, and the fan beam CT is adopted, so that the image guide precision is improved, and the positioning error is reduced.

The invention belongs to the technical field of vehicle driving control, and particularly relates to an adaptive cruise safety self-evolution method, device and system based on a safety boundary. The method comprises the steps that vehicle driving data and environment information are collected and preprocessed, and a time sequence data set containing the state, control input and corresponding reward values of a vehicle in all time steps is obtained; secondly, dynamically evaluating the safety distance between the vehicle and surrounding obstacles through a control obstacle function, determining a safety area, and constructing and updating a safety driving boundary function of the vehicle at the same time; the MPC controller takes a safe driving boundary function as a constraint condition and takes a stable approaching target speed and a vehicle following distance as targets to obtain a control input sequence; and the vehicle executes corresponding operation according to the control parameters, and continuously adjusts the weight matrix of the MPC through an online optimization algorithm, so that the control parameters are gradually optimized. According to the method, adaptive adjustment of the MPC parameters is realized, so that the safety and the adaptive capacity of the vehicle in a complex traffic environment are improved.

The utility model discloses an egg conveying device, relates to egg conveying field, including frame, drive unit and N egg support, said frame includes feed box, discharge box and support base, the support base is fixedly equipped with two parallel vertical plate, the lower section of vertical plate is provided with two chute, the outside of chute is provided with L-shaped adjusting seat, and the L-shaped adjusting seat is provided with the feed box, discharge box and support base. The feeding box is connected with the henhouse egg belt, the discharging box is connected with the egg collecting conveying line, an integrated path of egg tray picking, continuous conveying and accurate discharging is constructed, 2-3 times of transfer links of traditional sectional conveying are reduced, on one hand, the occupied area of equipment is reduced, no additional connecting mechanism is needed, and the production cost is reduced. The installation and debugging complexity and fault points are reduced, and on the other hand, the collision risk caused by repeated transfer of eggs is avoided.

The invention relates to the technical field of nuclear waste liquid transport vehicles, and discloses an intelligent transport vehicle for nuclear power plant radioactive waste liquid sampling and a control method.The transport vehicle comprises a chassis, a storage part arranged on the chassis and a mechanical arm used for grabbing a carrier containing nuclear waste liquid; the storage part is internally provided with a plurality of carrying positions for placing the carriers, each carrying position is internally provided with a weighing module and a positioning module, and the weighing modules and the positioning modules are electrically connected with the mechanical arm; the positioning module is used for detecting and positioning the position of the carrier placed on the carrying position and outputting positioning information; when the mechanical arm places the grabbed carrier on the carrying position, the mechanical arm adjusts the lowering position of the carrier according to the positioning information of the grabbed carrier by the positioning module, so that the lowering position of the carrier is matched with the position of the weighing module; therefore, the total weight of the carrier and the nuclear waste liquid contained in the carrier can be accurately obtained. The carrier is positioned and calibrated at the specific height, positioning and lowering of the carrier are guided, the collision risk of the carrier during lowering can be effectively avoided, and potential safety hazards are reduced.

The invention discloses a parking space screening method, a vehicle, a storage medium and a product, and relates to the technical field of automatic driving, and the method comprises the steps: obtaining a driving environment image of the vehicle, and generating a target reference gray value of the driving environment image based on a gray value of a drivable region pixel point in the driving environment image; and marking the parking space in the driving environment image as a non-selectable parking space under the condition that the target reference gray value is smaller than a preset dim brightness threshold value. Namely, the parking space determined through the driving environment image is marked as the non-selectable parking space, so that the parking space in a dark scene is not selected for parking when the vehicle is automatically parked, and the safety risk of automatic parking of the vehicle is reduced.

The invention relates to the technical field of operation distance control methods, in particular to an overhead line engineering machinery operation safety distance management and control method based on high-precision positioning and laser point cloud data, which comprises the following steps of: establishing a comprehensive space model comprising a line trend, a line height and a three-dimensional terrain; the planned construction path is mapped to the comprehensive space model, the minimum distance between the position of the engineering machinery in the whole planned construction path and the overhead line is calculated, and the maximum operation range of the engineering machinery is obtained and compared; the content of the construction project planning book is analyzed, when the minimum distance between the engineering machinery and the overhead line is analyzed, the actual operation range of the engineering machinery at the position is judged, and comparison is carried out; the construction path of the engineering machinery is monitored in real time during construction, and deviation from the planned construction path is avoided; according to the invention, the collision risk of the engineering machinery and the overhead line in the construction process is effectively prevented, the accurate control of the construction path is ensured, and the overall construction safety is improved.

The invention relates to a mechanical arm coordinate conversion calibration method and device based on an optical tracking system, and the method comprises the steps: installing the optical tracking system, and fixing an optical calibration plate on a base of a to-be-calibrated mechanical arm; adjusting the joint of the mechanical arm to be calibrated to a standard zero position; sampling sample points in a plurality of directions perpendicular to the base flange plate through an infrared optical probe; performing circle center calculation based on a space circle equation, and determining a coordinate axis of the base; determining an intersection point on a base shaft and a base center point of the mechanical arm; calculating a space coordinate transformation matrix of the base according to the center point of the base and the X axis and the Y axis of the base; and the conversion module is used for converting the mechanical arm base into a coordinate system of the optical tracking system in real time based on the position of the optical calibration plate. Compared with the prior art, the problems that in a traditional method, operation is complex, the calculated amount is large, and the environmental influence is large are effectively solved, the positioning workload of the mechanical arm is remarkably simplified, and the working efficiency and operation safety of the mechanical arm are improved.

The invention provides a vehicle control method, a vehicle, a storage medium and a computer program product. The method comprises the steps that first position information and vehicle speed information of a target vehicle and second position information of a dangerous target object are acquired, and speed information of the dangerous target object is acquired; based on the first position information, the vehicle speed information, the second position information and the dangerous target object speed information, performing verification processing to obtain a target verification result, the target verification result being used for determining a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object; according to the target verification result, a collision prediction result is determined, and the collision prediction result is used for determining whether there is a collision risk between the target vehicle and the dangerous target object; and controlling braking of the target vehicle based on the collision prediction result. According to the vehicle control method and device, the technical problems of low safety and poor adaptability of a vehicle control method provided in the related technology are solved.

The invention relates to the technical field of angle steel tower climbing robots, in particular to an angle steel climbing foot and a climbing robot. The abutting telescopic rod is installed on the installation base and can stretch out and draw back to be close to or away from the angle steel main materials according to needs, so that the abutting part can flexibly adapt to the angle steel main materials of different positions and sizes. Meanwhile, a hinge seat is installed at the telescopic end of the abutting telescopic rod, two clamping plates hinged to the hinge seat are opened and closed to form a V-shaped clamping opening, the V-shaped clamping opening can accurately cover the V-shaped outer wall face of the angle steel main material, and the folding assembly is arranged on the moving path, away from the angle steel main material, of the hinge seat; the main function is that the V-shaped clamping opening is closed and kept in a closed state in a non-working state, so that the space volume of the two clamping plates is reduced, the risk that the clamping plates collide with inclined materials or other obstacles on angle steel main materials when the angle steel climbing foot moves or adjusts the position can be effectively avoided, and the use safety and convenience are improved.

The invention provides a welding seam path planning method and system based on robot kinematics and a medium. The method comprises the following steps: acquiring three-dimensional data of a welding seam; establishing a robot kinematics model; a coordinate conversion step; a path planning step; a collision detection and optimization step: performing collision detection in combination with a collision detection algorithm in the path planning process, and entering an optimization sub-step if it is detected that a collision risk exists on the robot path; if the collision risk does not exist, determining the current motion parameter as an optimized motion parameter, and determining a path corresponding to the current motion parameter as a final planning path; and a path execution control step: applying the optimized motion parameters to a robot control system, and controlling the robot to carry out movement and welding operation along the final planned path. According to the method, path continuity is achieved, the collision risk is avoided, the accuracy and safety of the welding process are improved, and wide market prospects and economic benefits are achieved.

The invention provides a vehicle control method and system and a storage medium. The method comprises the following steps: detecting a shifting mode of a steering shifting rod; the current driving intention of the driver of the vehicle is recognized based on the shifting mode of the steering shifting rod; acquiring current environment information of the vehicle; determining whether a current driving intention of the driver can be executed based on the current environment information; when it is determined that the current driving intention of the driver can be executed, the vehicle is controlled to execute the current driving intention of the driver. According to the invention, intelligent decision and execution of the vehicle based on the driving lever operation of the driver can be realized.