129 results about "Robot path" patented technology

The invention proposes a robot path planning algorithm based on a particle swarm optimization algorithm and a dynamic window method, and relates to the field of control theories and electronic information, and the method comprises the steps: introducing an inertia weight updating strategy based on a state factor, setting adaptive parameters and crossover and mutation operators to improve the global search capability, increase the population diversity, and improve the robot path planning precision. On-line self-adaptive updating of inertia weight and learning factors is realized on line in combination with Q-learning, gene combination modes are enriched through crossover operators, convergence and exploratory performance of the algorithm are improved, an obstacle avoidance strategy of a traditional DWA algorithm is improved, weight parameters of a dynamic window evaluation function are dynamically adjusted according to real-time information of a target and an obstacle, and an obstacle avoidance algorithm is established. According to the method, the global planning is adopted, the path points generated through global planning are adopted as temporary targets, fusion of MOQLCOPSO and the improved DWA algorithm is achieved, local optimum is effectively avoided, the planning efficiency and path safety are improved, and the method is suitable for mobile robot navigation under the complex three-dimensional terrain.

The invention discloses a multi-robot path coordination system based on reinforcement learning, and the system comprises a state collection module which is used for collecting the operation state and environment perception information of each robot, and generating an original data set; the state modeling module is used for constructing local state representation for each robot in each decision period; the opponent perception module is used for executing opponent learning perception training and outputting opponent parameter estimation vectors; the improved LOLA module is used for generating a final estimation result on the basis of self-strategy updating of the traditional LOLA; the strategy updating module is used for correcting the updating direction of the reinforcement learning strategy of the local machine and generating a feasible action set; the arbitration decision module is used for executing arbitration solution in combination with the candidate path action distribution to generate a scheduling result; and the execution feedback module is used for issuing the control action to a robot executor for execution, generating a path coordination result and storing the path coordination result. According to the invention, path coordination of multiple robots is realized.

The invention discloses a dynamic obstacle avoidance and path optimization method based on a body intelligence robot, and relates to the technical field of robot path planning, and the method comprises the following steps: collecting map data and task constraint data; performing path planning analysis on the map data and the task constraint data based on a set path optimization algorithm to generate initial planning path data; according to the intelligent robot dynamic obstacle avoidance and path optimization method, a robot actual driving path prediction model is constructed, and a target function is constructed for the deviation between the robot actual driving path prediction model and the real-time path planning data of the next time period to carry out minimization analysis; and the real-time path planning data of the next time period is optimized, so that the robot runs according to the optimized real-time path planning data to obtain an actual running path which fits the original real-time path planning data, and the running error of the robot is reduced.

The invention discloses a photovoltaic cleaning robot path optimization method based on a hybrid algorithm. The method is used for improving the operation performance of a robot in a multi-region environment. The method comprises the following steps: S1, constructing a plurality of target optimization functions based on a scene; s2, constructing an initialized population based on a plurality of target optimization functions, and constructing a total target function value matrix X; s3, calculating fitness values of all individuals; s4, performing non-dominated sorting on all individuals in the total objective function value matrix X according to the fitness values of all the individuals, dividing the individuals into a plurality of hierarchies, and enabling the individuals in each same hierarchy not to be dominated; s5, crowding degree calculation: selecting an individual with the largest crowding degree distance in the non-dominated hierarchy; and S6, performing particle swarm optimization and speed updating, and outputting a current optimal solution. The invention has the advantages of high efficiency and energy conservation.

The invention discloses an inspection robot path planning method and system based on environmental perception, and relates to the technical field of path planning, and the method comprises the steps: traversing an inspection target region to determine a plurality of environmental perception point locations; obtaining a plurality of environmental perception data sets; performing data fusion processing on the plurality of environment perception data sets to generate a three-dimensional environment model; determining an initial planning path of the inspection robot; performing environment adaptability analysis on the initial planning path, and determining a target planning path; and controlling the inspection robot to execute an inspection task in the inspection target area according to the target planning path, and feeding back inspection state data in real time. According to the method and the device, the technical problems of low task execution efficiency and poor reliability of the inspection robot caused by lack of dynamic optimization of the inspection robot path planning in the prior art are solved, and the technical effects of realizing accurate planning and dynamic environment adaptation of the inspection robot path and improving the task execution efficiency and reliability of the inspection robot are achieved.

The invention relates to the technical field of track obstacle avoidance, and discloses a track robot path obstacle avoidance data updating method and system, and the method comprises the steps: carrying out the vector assembly of multi-dimensional features in a real-time environment data flow of a track robot, and obtaining a primary feature vector, carrying out abnormal mode identification on the primary feature vector and a historical normal mode library to obtain a dynamic abnormal feature; according to the dynamic abnormal features, reconstructing a local topology of a pre-stored path knowledge graph to generate an obstacle influence domain; analyzing the field intensity distribution change trend of the obstacle influence domain to obtain a gradient field, and mapping the dominant direction of the gradient field into a conflict resolution strategy; correcting a predetermined path of the orbital robot to obtain a conflict-free path trajectory fragment; performing efficiency judgment on the conflict-free path trajectory fragments to obtain a multi-dimensional evaluation result; fusing multi-dimensional evaluation results to obtain an emergence type motion strategy; the efficiency of updating the path obstacle avoidance data of the rail robot can be improved.

The invention discloses a multi-delivery robot path collaborative optimization system and a scheduling method, and aims to solve the problems of non-uniform scheduling load, unsmooth path, weak conflict avoidance capability and poor dynamic adaptability of existing multi-robot scheduling. The system comprises a central scheduling module, a distribution robot terminal, an environment sensing module and a map management module, and realizes task analysis, state monitoring, path planning and conflict coordination. According to the method, region division and task balanced distribution are completed by improving a DARP algorithm, path coverage efficiency and smoothness are optimized by fusing a BA * algorithm, a cattle farming method and a TEB algorithm, multi-type path conflicts are solved by adopting a time window reservation and distributed negotiation strategy, and dynamic adjustment under new task access, robot faults and environment sudden change is supported. According to the method, the load balance, the path optimization effect and the conflict avoidance capability of multi-robot collaborative distribution can be remarkably improved, the efficient and stable execution of the distribution task is ensured, and the method is suitable for terminal distribution scenes such as communities and office buildings.

The invention discloses a tunnel construction robot path planning method and system based on deep reinforcement learning, and relates to the technical field of tunnel construction automation and robot navigation, and the method comprises the steps: pre-defining a state space and an action space of robot path planning in a tunnel construction environment, and building a dynamic reward function; constructing a deep reinforcement learning architecture based on a lightweight action network and a comment network, and training an action-comment network based on state-action pair data in an experience pool by taking the sum of an accumulated reward and an entropy regularization item of a maximization strategy as a target; and on the basis of the current state information of the tunnel construction robot, the optimal moving action of the next step is obtained by utilizing the trained action network, and path planning of the robot is realized. According to the method, the deep reinforcement learning technology is applied to the tunnel construction scene, and the autonomous decision-making ability and the path planning precision of the robot in the dynamic construction environment are optimized and improved in combination with real-time data acquisition and processing of the complex tunnel environment.

The application discloses an amphibious robot path planning control method, characterized in that comprising the following steps: step 1: according to the environment terrain elevation model already introduced in the amphibious robot system, the global optimal path from the starting point to the target point is calculated by using the HHO algorithm; step 2: according to the real-time geographical position of the amphibious robot, the navigation is started according to the global optimal path; step 3: when the amphibious robot encounters an obstacle, it is judged whether the obstacle is a known obstacle, and the amphibious robot is controlled to avoid the obstacle according to the specific situation of the obstacle. In the process of navigation of the robot, two different obstacle avoidance strategies are carried out according to whether the obstacle is a known obstacle, the real-time position of the robot can be dynamically positioned and corrected, and dynamic obstacle avoidance can be safely and quickly carried out, so that the robot is more accurate in the process of navigation on the preset route.

The invention relates to the technical field of photovoltaic module vegetation shielding intelligent defect elimination, discloses a photovoltaic module vegetation shielding intelligent defect elimination system and an application method, and thoroughly solves the technical problem that obstacle information cannot be updated in real time in traditional mowing robot path planning through cooperative linkage of an intelligent diagnosis platform and a defect elimination unmanned aerial vehicle. The intelligent diagnosis platform accurately locates an abnormal area based on historical and real-time electrical parameters of a photovoltaic array, the defect-eliminating unmanned aerial vehicle carries multiple modules to realize integrated operation of positioning, identification, distance measurement and cleaning, a fixed path does not need to be preset, an operation strategy can be dynamically adjusted in real time according to on-site sheltering objects, and an operation blind area caused by path stiffness is effectively avoided; and meanwhile, the shielding part is determined through three-dimensional modeling and accurate distance measurement, and force-position hybrid control is adopted in the cleaning process to avoid damage to the photovoltaic panel and the bracket, so that the equipment damage risk is greatly reduced, and the manual secondary maintenance cost is reduced.

The invention discloses a robot path recognition method and system, and belongs to the technical field of robots, and the system comprises an acquisition module, a recognition module, a coffee cup shape recognition result acquisition module, a coffee cup position recognition result acquisition module, a determination module, a position posture acquisition module and a path recognition module. The method comprises the following steps: acquiring an environment image including a coffee making area, and performing multi-stage identification and processing on the image, including determining candidate block images of suspected coffee cups, obtaining coffee cup structure standard parameters for shape matching, and identifying a coffee making area range for position judgment. And finally, fusing the shape and position identification results to determine a target coffee cup so as to confirm the moving path of the coffee cup. The method can effectively solve the problem that in the prior art, due to the fact that coffee powder is attached to a camera lens, an image is blurred, coffee cup recognition is inaccurate, and path planning deviation is caused.

The application discloses a new energy automobile sky screen flexible collinear assembly production line, and relates to the technical field of new energy automobile part automation assembly. The control system is provided with a multi-vehicle parameter library, and calls sky screen profile size, edge curvature, adsorption partition, glue coating path, glue gun relative height compensation and pressing segmented force control parameters according to a vehicle type identification signal. The vision detection system outputs a sky screen pose deviation and converts the sky screen pose deviation into a robot path compensation amount, and uniformly corrects a grabbing, glue coating and installation path. After glue coating, a defect position is converted into a path arc length coordinate and glue supplement, re-coating or alarm are executed. During installation, interlocking control is carried out based on a pressing force, a pressing force growth slope and a suction disc release signal. The production line improves the positioning precision, glue coating quality and glass anti-damage ability of collinear assembly of multi-vehicle curved surface sky screens.

The present application relates to the technical field of track obstacle avoidance, and discloses a track robot path obstacle avoidance data updating method and system, the method comprising: assembling a plurality of dimensional features in real-time environment data flow of the track robot into a vector group to obtain a primary feature vector, and performing abnormal mode identification on the primary feature vector and a historical normal mode library to obtain dynamic abnormal features; reconstructing a local topology of a pre-stored path knowledge graph according to the dynamic abnormal features to generate an obstacle influence domain; analyzing a field strength distribution trend of the obstacle influence domain to obtain a gradient field, and mapping a dominant direction of the gradient field into a conflict resolution strategy; correcting a predetermined path of the track robot to obtain a conflict-free path trajectory segment; performing efficiency determination on the conflict-free path trajectory segment to obtain a multi-dimensional evaluation result; and fusing the multi-dimensional evaluation result to obtain an emergent motion strategy; the present application can improve the efficiency of track robot path obstacle avoidance data updating.

The application discloses a path generation method of a robot, an electronic device and a computer readable storage medium. The method comprises the following steps: acquiring a grid map of a current environment; determining a target grid in an idle state from the grid map; performing inflation processing on the target grid to obtain a grid inflation area; determining a key grid from the grid inflation area, the distance between the key grid and a grid in an occupied state being less than a first preset distance and greater than a second preset distance, the second preset distance being less than the first preset distance; and determining an optimal path of the robot in the current environment according to the key grid. In the foregoing manner, the robot wall-following path can be quickly and accurately generated.

The invention relates to the technical field of robot path control, and discloses a robot path control method based on automatic operation. The method comprises the following steps: acquiring three-dimensional point cloud data of a robot working environment, and generating an environment grid map through spatial rasterization processing; a dynamic obstacle track is extracted based on the map, and a dynamic obstacle avoidance constraint condition is constructed in combination with kinematics parameters of the robot. After the path search space is initialized according to the constraint condition, a candidate path set is generated by adopting a heuristic strategy, and an optimized path meeting a preset threshold value is screened out through smoothness and energy consumption evaluation. And inputting the optimized path into a track generator to generate a continuous motion track of each joint of the robot. And pose deviation is monitored in real time during operation, and track re-planning is triggered if the deviation exceeds a fault-tolerant threshold value. According to the method, the environment sensing precision and the path generation efficiency are improved, and the stable operation of the robot in a complex dynamic environment is ensured.

The application discloses a kind of sensing optical cable laying robot path planning and obstacle avoidance system and method thereof, belong to robot path planning technical field.The system includes environment perception, data preprocessing, path planning, obstacle avoidance control and post-processing module.Method is obtained environment information by laser radar and camera and pre-processing, based on improved dynamic RRT algorithm carries out path planning, introduces adaptive step adjustment mechanism, according to environment complexity, obstacle distance and path curvature Dynamic adjustment step, combine real-time obstacle detection and dynamic replanning function Generation smooth path;PID control algorithm is used to adjust the speed and steering angle of robot to realize obstacle avoidance, and the post-processing module optimizes the evaluation path.The application improves the real-time performance, path quality and environmental adaptability of the robot in complex dynamic environment, ensures efficient, safe and accurate laying of optical cable.

This invention belongs to the field of flexible manufacturing systems technology and discloses a path-execution cooperative control method for multiple mobile transport robots based on Petri nets. The method includes: acquiring current system state information; determining the effective starting point and first effective target based on the current task sequence information of each mobile transport robot; updating the current position index by combining historical path cache, and reusing or re-determining discrete path sequences according to preset conditions; injecting the path sequences as spatial constraints into the Petri net execution model, and constructing an executable transition binding instance set by combining the current system state, robot execution state, and resource enabling relationships; selecting and advancing compatible transition binding instances from the instance set to form execution fragments, and updating the system state accordingly, thereby achieving rolling closed-loop cooperative control of the multiple mobile transport robot system. This invention is beneficial for improving the consistency of path planning and execution processes and the efficiency of system resource coordination.

A kind of multi-robot path planning method based on course depth reinforcement learning, utilize the thought of course learning, design each stage of course learning, by changing the number of robots in each stage, and map size and the number of obstacles, realize the task from easy to difficult;Build a reinforcement learning environment, define the observation space of robot in the environment, action space and the reward function of environment, formulate the operation rules of robot in the environment;Design a network structure to adapt to the changing number of robots in the environment, use Qatten algorithm to train network model, the present application can solve the problem of multi-robot path planning in continuous space, its advantage lies in that it can realize path planning faster and better than traditional algorithm, improve the efficiency of path planning.

The invention discloses a multi-robot path scheduling method and device, electronic equipment and a storage medium. The method comprises the following steps: generating an initial path; dividing the preliminary path into a plurality of sub-paths, predicting entering time and leaving time of the robot in each sub-path, and obtaining a pre-occupation time period of the robot in each sub-path based on the entering time and the leaving time; detecting whether each sub-path is occupied by other robots in the corresponding pre-occupation time period; if not, the robot is indicated to be occupied; if so, generating a replacement sub-path and / or generating waiting time; and after each sub-path is detected, obtaining an execution path based on each replacement sub-path and / or the waiting time, and indicating the robot to move to the position of the target task point based on the execution path. The path is divided into a plurality of sub-paths, and occupation management is performed only when the robot is about to enter the corresponding sub-paths, so that the utilization efficiency of overall path resources is improved.

The invention discloses a robot speed control method and device based on single-target planning, and relates to the technical field of robot control. Robot motion control basic parameters are obtained, and the constant advancing speed of the first robot serves as a decision variable; wherein the robot motion control basic parameters comprise structural parameters, path geometric features, kinematics parameters and a speed safety threshold value of the robot, the robot path adopts an Archimedes spiral, and the U-turn path is planned into two sections of tangent arcs; constructing a target function by taking maximization of the decision variable as a target; setting constraint conditions based on robot motion control basic parameters; constructing a single-target constraint optimization model by combining the target function, the constraint condition and a robot speed calculation model; the single-target constraint optimization model is solved, and the maximum speed of the robot in the U-turn area is calculated through simulation. The problem of how to control the performance speed of the robot and guarantee the safety of the performance process of the robot is solved.

The invention discloses a robot path planning method based on an adaptive fuzzy and hybrid strategy, and belongs to the technical field of robot motion planning, and the method comprises the steps: carrying out environment perception, and obtaining environment information; the method comprises the following steps: on the basis of an RRT-Connect algorithm framework, fusing a fuzzy control theory, a hierarchical hybrid expansion mechanism and a dynamic path optimization thought to obtain an improved RRT-Connect algorithm; and an improved RRT-Connect algorithm is utilized, and robot path planning is realized based on environment information. According to the method, the fuzzy control theory is utilized to endow the path planning process with a macroscopic intelligent decision-making capability, and a microscopic accurate execution and fault-tolerant capability is provided through a hierarchical mixed strategy, so that the method is an efficient and robust universal solution; the success rate, efficiency and path quality of path planning of the robot in a complex high-dimensional space are remarkably improved, and more efficient and better collision-free path generation can be achieved.

The invention relates to the technical field of power grid inspection, in particular to a power grid inspection path safety optimization method and system based on an ant colony algorithm, and the method comprises the following steps: based on a power transmission line corridor, collecting and sorting load monitoring data in a partitioned manner, filing to form a node load density sequence, and configuring an inspection task in combination with a robot path trajectory and node space distribution. And extracting node disturbance characteristics, judging the interference level of the path section, adjusting the passing probability according to the level, and optimizing the routing inspection priority data. According to the method, node load density fluctuation trend data is introduced, a path segment and load node space correlation system is dynamically established, disturbance characteristic indexes are used for path risk level judgment, and the traffic probability is adaptively updated according to the path segment interference level, so that the dynamic adjustment of the inspection sequence is realized; the active response to the load change trend in the path planning process is enhanced, the safety of the inspection task in the load sensitive area is remarkably improved, and the rationality of inspection resource allocation and the operation continuity are promoted.

The invention provides a path adjustment method and system and a robot, and the method comprises the steps: traversing path points to be driven in a global path from an initial point, and generating a local path initial point group through the traversed path points; under the condition that the inflection point is traversed, traversal is stopped, and if the included angle formed by the waypoint and the waypoint adjacent to the waypoint before and after the waypoint is larger than an angle threshold value, the waypoint is the inflection point; and performing local path adjustment based on the obtained local path initial point group. According to the path adjustment method and system and the robot provided by the invention, the robot finishes traversing when traversing to the inflection point, so that the robot cannot directly move towards the path point behind the inflection point when the robot obtains the local path and runs to the inflection point along the local path; therefore, the probability that the robot cannot accurately reach the break angle where the inflection point is located can be reduced, and the probability that the robot collides with an obstacle located near the inflection point when driving towards the path point behind the inflection point before reaching the inflection point is reduced.

The invention relates to the technical field of industrial robots, and discloses a digital twinning multi-robot cooperation wheel type polishing method and device, a storage medium and a system.The digital twinning multi-robot cooperation wheel type polishing method comprises the steps that 1, a digital twinning model is constructed; 2, virtual simulation and path planning are carried out; step 3, cooperative scheduling and task allocation; 4, performing real-time feedback and adaptive adjustment; by arranging the step 2 and the step 3, a virtual model of a workpiece can be updated in real time and surface characteristics and shape changes can be reflected by introducing a digital twinning technology, then the polishing process is optimized, precision and consistency are improved, cooperative scheduling of robot paths and tasks is achieved through virtual simulation and a dynamic optimization algorithm, and the polishing efficiency is improved. The path conflict between the robots is reduced to the maximum extent, the efficiency and precision of multi-robot cooperation are improved, the cooperation strategy is dynamically adjusted, the production efficiency is greatly improved, and the machining time is shortened.

The invention discloses a robot path navigation method based on multi-modal perception, relates to the technical field of intelligent robots, and can solve the problems of insufficient utilization of visual semantic information, limited perception capability of a three-dimensional geometric structure and difficulty in migration from simulation to reality in the prior art. The method comprises the steps of collecting multi-source original data and generating three-dimensional Gaussian splashing visual representation and voxelization geometric representation; constructing a high-throughput simulation training framework, and integrating the three-dimensional Gaussian splash model as a plug-and-play renderer to a vectorization physical simulator; extracting visual semantic features through a pre-trained visual encoder, and extracting three-dimensional geometric features through a grouped convolutional neural network; fusing the visual semantic features, the three-dimensional geometric features and the ontology perception features through a recurrent neural network to generate potential representation; and training the navigation strategy network based on the potential representation and migrating deployment. According to the invention, efficient semantic perception navigation and steady simulation-to-reality migration of the robot in a complex environment are realized.

The invention relates to the technical field of nondestructive testing and automatic control, and discloses a fan blade detection robot path optimization navigation system fused with phased array data, which comprises an omnidirectional mobile wall-climbing platform, a phased array acquisition unit, an active fluid coupling unit and a control center. The acoustic texture analysis module calculates an optimal physical direction vector, and the path planning resolving module compares the mechanical course angle, decomposes the deviation into an electronic deflection component and a mechanical rotation component, and sets a threshold value to judge an electronic dominant or electromechanical cooperative compensation mode. And the multi-axis motion control module drives probe beam deflection and omnidirectional wheel vector motion accordingly. The active fluid coupling unit adjusts the flow rate by using a feedforward feedback strategy to maintain a stable liquid film. And the defect tracking module guides the robot to realize defect centering or contour following based on the signal-to-noise ratio gradient vector. Through electromechanical asynchronous cooperation and active coupling control, the problems of acoustic beam distortion and trajectory tracking of anisotropic materials are solved.

The invention belongs to the technical field of distribution robot path adjustment, and discloses a distribution robot autonomous path adjustment method based on intelligent visual prediction, and the method comprises the steps: firstly, employing an improved MaskR-CNN segmentation model to distinguish a dynamic target from a static target, complementing the visual leak detection in a rain and fog environment through the combination with laser radar data, and carrying out the detection of the dynamic target and the static target; the association relationship classification of avoidance type, parallel type and other scenes is accurately completed; through graph attention LSTM, by taking the dynamic target as a node and the association relationship as an edge, capturing key features such as motion association between the targets, and outputting a speed abrupt change rate and track synchronization degree; and finally, predicting a group association trajectory by using group motion constraint Kalman filtering, and adjusting a safety distance according to a scene association risk level. The whole process comprehensively covers interaction scenes such as pedestrian avoidance of electric vehicle turning and parallel track extrusion of multiple electric vehicles, so that misjudgment of emergency situations is effectively avoided, and the distribution safety in a complex interaction scene is improved.

The invention discloses a path planning method and device, equipment and a storage medium. The method comprises the following steps: acquiring position information of a robot on a plurality of data sampling points during map construction; screening a plurality of central key points in the plurality of data sampling points based on the position information corresponding to the plurality of data sampling points; determining neighbor points of each key point in a plurality of key points obtained by expanding the central key point; and based on the position information of the multiple key points and the position information of the neighbor points of the key points, determining a moving path of the robot moving from the current position to the target position. Therefore, the working area of the robot can be effectively covered by utilizing the data sampling points in the map construction period of the robot and generating the possible track points of the robot in the map, so that a large number of invalid areas are avoided during path searching, and the efficiency of planning the robot path is improved.

The invention discloses a rescue robot path planning method and system based on sound source localization, and relates to the related field of robot path planning technology.The method comprises the steps that rescue environment audio data in a stereo format is collected in real time; analyzing acoustic features of the rescue environment audio data by adopting a pre-trained sound source localization model, and outputting sound event types and position data contained in the audio; determining a rescue target according to an output result of the pre-trained sound source localization model, and fusing data acquired by the rescue unmanned aerial vehicle to obtain an environment model of the rescue area; and based on the rescue target position information and the rescue area environment model, a secondary optimization path planning algorithm is adopted to formulate a rescue route of the rescue robot, and dynamic obstacle avoidance in the advancing process of the robot is realized through a dynamic window method. The problem that the rescue robot path planning precision is insufficient in a vision-limited post-disaster environment is solved, the method for determining the position information of the rescue target from the auditory perspective is expanded, and the robot path planning efficiency is improved.