600 results about "Robot path planning" patented technology

New and Improved methods and apparatus for robotic path planning, selection, and visualization are described A path spline visually represents the current trajectory of the robot through a three dimensional space such as a room By altering a graphical representation of the trajectory—the path spline—an operator can visualize the path the robot will take, and is freed from real-time control of the robot Control of the robot is accomplished by periodically updating the path spline such that the newly updated spline represents the new desired path for the robot Also a sensor that may be located on the robot senses the presence of boundaries (obstacles) in the current environment and generates a path that circumnavigates the boundaries while still maintaining motion in the general direction selected by the operator The mathematical form of the path that circumnavigates the boundaries may be a spline

The invention relates to a flight path planning method based on a sparse A* algorithm and a genetic algorithm and belongs to the technical field of flight path planning of an unmanned aerial vehicle (UAV). According to the characteristics of flight path planning, the method comprises the following steps: planning an initial reference flight path by the utilization of the sparse A*search (SAS) algorithm, wherein constraint conditions are combined into algorithm search, so that useless nodes in a search space can be effectively deleted and the search time is shortened; and when emergent threat occurs during real-time flight of the UAV, performing real-time flight path planning by the utilization of the genetic algorithm and generating a flight path with local optimum or approximate optimum until the threat disappears and the UAV returns the original global optimum reference flight path and continues flying. The method provided by the invention has high real-time performance and rapidity; the searched flight path is closer to the actual UAV optimal flight path; and the method can be applied to the technical fields of robot path planning, urban vehicle path planning and the like under complex environments.

The invention discloses a double-layer planning method based on the combination of global path planning and local rolling prediction collision avoidance planning, so as to solve the problem of path planning for a mobile robot in a dynamic environment. The method mainly comprises two parts: the global path planning and the local rolling prediction collision avoidance planning. The path planning method can better realize robot navigation, and improve intelligence of the robot. The double planning method can be utilized to prevent the blindness of planning in the beginning, and searching space of the problem is reduced; based on the uncertainty of the moving direction of a dynamic barrier and by utilizing the two collision prediction strategies and two corresponding collision avoidance strategies, the dynamic barrier can be avoided well; and particularly, in order to adapt to the change of environment better, in the second layer of planning, a Follow_wall behavior based on behavior method is added, so that when the environment changes, the mobile robot can still arrive at the target without touching the barriers safely.

The invention discloses a mobile robot path planning and obstacle avoidance method and system. The mobile robot path planning method comprises the following steps: establishing a two-dimensional grid map by utilizing known obstacle environment information; in the two-dimensional grid map, establishing a global coordinate system at the place of a mobile robot, and setting a starting point and a terminal point of the mobile robot; determining the shortest path between the starting point and the terminal point through a jump point search algorithm, wherein the shortest path comprises a plurality of local target points connected in sequence; and in the process of controlling the mobile robot to move to each of the local target points, utilizing a local obstacle avoidance algorithm to avoid a dynamic obstacle. The mobile robot path planning and obstacle avoidance method adopts the jump point search algorithm to obtain the shortest path quickly, so that path search efficiency can be improved, and storage space is saved; and through the local obstacle avoidance algorithm, accuracy and real-time performance of mobile robot path planning and obstacle avoidance can be ensured, and autonomous navigation of the mobile robot is realized.

The invention provides a robot path planning method and an apparatus thereof based on a Bezier curve. The method comprises the following steps that: a robot path planning parameter input unit receives and sets a robot state parameter, a constraint condition, a path discretization minimum time resolution; a robot path generation unit generates a group of Bezier curve control points consisting of four 4-dimension vectors according to the robot state parameter and plans out a continuous path between an origin position to a target position of the robot; the robot path generation unit forms a timepoint sequence according to the path discretization minimum time resolution and calculates a discretization path according to the continuous path; a path point parameter detection unit detects whether a speed, an acceleration and a turn radius of each path point which is corresponding to the time points satisfy the constraint condition; if the speed, the acceleration and the turn radius of each path point do not satisfy the constraint condition, the control points are regenerated; otherwise, a planning path output unit receives and outputs a robot path which is planed by the path point parameter detection unit and satisfies the constraint condition.

A system, method, and computer readable medium. A method for robotic path planning includes receiving a robotic path for a robot and associating a plurality of zones with each location in the robotic path. The method also includes selecting for each location one of the zones associated with the location and simulating motion of the robot over the robotic path using the locations and selected zones. The method further includes determining whether a collision occurred in the simulated motion of the robot. The method still further includes, if there was a collision, identifying a location associated with the collision, selecting a new zone for the identified location other than the currently selected zone, and repeating the steps of simulating motion of the robot and determining whether a collision occurred. The method also includes, if there wasn't a collision, assigning to each location its currently selected zone.

The invention discloses an indoor map building method for improving robot path planning efficiency. The method combines a topological map and a grid map, the planning problem happens in space represented by topological nodes, and planning of global space is avoided. In addition, laser is used for identifying a door in the indoor environment, a topological relationship between rooms is built, the process is merged in particle filter SLAM (simultaneous localization and mapping) algorithm, the grid map represented by the environment and the topological map based on the grid map can be obtained finally, and the path planning algorithm in robot navigation is simpler and more efficient.

The invention relates to the technical field of robots, in particular to a robot path planning method and device in an indoor dynamic environment and a robot. Known obstacle environment information and obstacle expansion information are taken as reference in global path planning, a local path is generated according to dynamic obstacle information and obstacle expansion information in local path planning, is spliced with a global path with the minimum path cost value sum and replaces the global path with the minimum path cost value sum in a local window to obtain a target obstacle avoidance path, and the robot is controlled with a path fitting control algorithm to move along the target obstacle avoidance path so as to avoid dynamic obstacles. The obstacle environment information acquired in the global path planning is more complete, global environment is taken into consideration in the global path with the minimum path cost value sum, and the local path is generated according to the dynamic obstacle information and the obstacle expansion information in the local path planning, so that the robot can adapt to the changing environment during operating in the local window and is enabled to walk along the finally planned target obstacle avoidance path.

A method, medium, and apparatus for performing path planning of a mobile robot is provided. The apparatus for performing path planning of a mobile robot includes a coarse map generation unit to generate a coarse map composed of a plurality of cells; a fine map generation unit to generate a fine map composed of a plurality of sub-cells into which at least one of the plurality of cells is divided, and a path generation unit to control the fine map generation unit to generate the fine map with respect to a specified position in the coarse map generated through the coarse map generation unit. The method of performing path planning of a mobile robot includes generating a coarse map composed of a plurality of cells, generating a fine map composed of a plurality of sub-cells into which at least one of the plurality of cells, which neighbors the cell where an obstacle exists, is divided, generating a moving path whereby the mobile robot can pass a narrow passage by using the fine map, and updating the coarse map by reflecting the moving path.

The invention discloses an accompanying robot path planning method and system based on obstacle virtual expansion. The method includes a step of constructing an environment map, namely a step of constructing a two-dimensional occupancy grid map according to an actual scene, with each grid being labeled as an obstacle zone or a walkable zone; a step of setting initial coordinate positions of an accompanying robot and a movable target in the grid map; a step of constructing a sliding window for the robot; a step of subjecting the obstacle zones to expansion processing, namely a step of performing initial expansion on grids where an obstacle is according to a shortest distance between the center of the robot and a body edge, determining the number of grid layers expanded on the basis of the minimum impassable zone, adopting the grids in the expanded zones as obstacle virtual expansion grids, and labeling the grade of danger of obstacle influences on the obstacle virtual expansion grids; and a step of planning a path for the accompanying robot based on an A* algorithm and an incremental path planning process. Incremental path updating is performed by adopting a path of the last moment,thus saving path planning time and increasing the response speed of the accompanying robot.

The invention relates to a multi-robot path planning method based on a time window. According to the method provided by the invention, a feasible path of a new robot is planed through a point time window and an edge time window of a node occupied by an existing robot; and when the time window of the robot is disturbed, a path of each robot is dynamically re-planned, so that the conflict of a plurality of robots in a system can be avoided. According to the multi-robot path planning method provided by the invention, a plurality of times of iteration are not needed, and the possibility is only calculated on a limited path set; and the relative calculated quantity is relatively small so that the multi-robot path planning method is more suitable for being applied to a real dispatching scene.

The invention discloses an intelligent robot route planning method. The intelligent robot route planning method comprises steps of (1) dividing an operation space into a plurality of n-meter*m-meter rectangle virtual zones, (2) controlling the intelligent robot to transverse every virtual zone in an H-shaped movement, (3) constructing a grid map with distance information, angle information, collision information and obstacle information in a H-shaped movement of the intelligent robot, and marking a passing point, an obstacle point and a collision point, (3) realizing a map in real time, determining whether a whole operation space finishes traversing, if yes, entering the step (4), if no, returning to the step (2), and (4) controlling the intelligent robot to perform one time of an along-the-border behavior and marking the along-the-border behavior points on the constructed map. The intelligent robot route planning method can construct an effective grid map with errors in a controllable range according to the distance information, angle information, collision information and obstacle information of the robot behavior and realizes a low cost and efficient robot route planning.

The invention discloses a robot path planning method and system based on an improved artificial potential field method, and the method comprises the steps: firstly finding local target points in a visual scope of a laser radar; secondly planning a reachable path from the current position of a robot to the local target points; and finally controlling and driving the robot to move to circularly detect the local target points till the robot reaches a final target point. The method employs the artificial potential field method to plan the path of the robot, solves a problem of a local minimal point appearing in path planning through a conventional artificial potential field method, and improves the conventional artificial potential field method, i.e., improving a gravitational potential function. Meanwhile, the method enables the whole task to be divided into a plurality of local target points, thereby achieving the optimal path. The method improves the instantaneity of path planning, environmental suitability and efficiency.

The invention relates to a method for planning robot paths on the basis of path expansion ant colony algorithms. The method has the advantages that the ant colony algorithms are applied to the field of robot path planning, path expansion ant colony algorithm optimization strategies are proposed, the robot path optimizing efficiency can be optimized, information element distribution time-varying characteristics, information element updating strategies, path location inflection point optimization and local optimal path expansion are introduced, and location inflection point parameters and general evaluation are additionally used as evaluation standards for the paths; as verified by simulation analysis and practical experiments on the three algorithms, the method is high in robot path planning and searching capacity on the basis of the path expansion ant colony algorithm optimization strategies and is high in algorithm efficiency, and the found paths are short; phenomena that the algorithms run into local optimization can be effectively inhibited, the optimal paths of robots can be searched, and the robots can quickly avoid obstacles to safely arrive at target points.

The invention relates to a smooth path planning method for mobile robots based on a dynamic complex environment, and belongs to the field of robot path planning. The method comprises the steps of starting; searching for an optimal path; conducting smooth treatment on the optimal path; ending. The step of searching for the optimal path uses a two-way RRT algorithm with the idea of gravity of an artificial potential field to perform path searching, that is, the artificial potential field gravity guides a random tree to grow toward a target direction, and the RRT algorithm is prevented from randomly sampling the global; a two-way A* algorithm after a heuristic function is improved is adopted to add angle factors based on distance factors, the units of distances and angles are normalized, thepath planning time is greatly reduced, and the convergence speed of paths is improved; smoothing treatment is conducted on the optimal path, a Freudian smoothing algorithm is adopted to remove redundant nodes, a B-spline method is used three times for smoothly connecting remaining nodes, and the smooth optimal path is finally obtained.

The invention discloses an inspection robot path planning method combining map grids with potential field method obstacle avoidance; the inspection robot path planning method comprises the following steps: 1, global grid method path planning: using the grid method to obtain the global optimal path from a start point to an object point; 2, moving to the object point: determining whether obstacles are encountered or not, moving to the object point is no obstacle is detected, planning a local obstacle avoidance path if an obstacle is detected until reaching the object point; 3, planning the local obstacle avoidance path, using the artificial potential field method with changeable parameters to carry out obstacle avoidance path planning, determining whether the object point is reached or not, returning to step 2 if not, and finishing the tour if the object point is reached. The inspection robot path planning method can solve the problems that the robot inspection path planning in the prior art is poor in efficiency, thus enlarging the robot inspection time.

The invention relates to a pruning robot system. The system comprises a signal label device and a robot. The signal label device is used for detecting and storing information of trees and agricultural crops, information positioning and auxiliary positioning. The robot comprises a central processing device, a positioning navigation device, a cloud platform terminal and a map building device. The central processing device is used for storing and analyzing data of each part of the robot and sending a movement instruction to each part of the robot. The positioning navigation device is used for positioning and navigating the robot and planning a path and providing obstacle-avoiding navigation for the robot based on an electronic map. The cloud platform terminal is connected and communicated with the central processing device and is used for storing data of the trees and the crops and detection information of the robot and for planning a movement line for the robot based on information data with a computer experiment. The map building device is used for building a three-dimensional electronic map corresponding to a garden by means of on-site detection and construction through the robot. The pruning robot system achieves positioning in the garden, robot path planning, pruning information collection and automatic pruning.

Embodiments of the invention provide a robot path planning method and a robot planning a route. The method comprises the following steps of according to a pose of a robot and control information of a speedometer, acquiring an initial pose of the robot; according to the initial pose and data observed by a sensor, creating a prior map; according to a rapid expansion tree algorithm of adaptive adjustment, calculating a global path used to control walking of the robot in the prior map; acquiring real-time detection data of the sensor of the robot, and determining whether the sensor detects a barrier in the global path when the robot is in a walking process; and when the sensor detects the barrier in the global path, establishing a dynamic window model to plan a local barrier avoiding route of the robot so as to make the robot avoid the barrier according to the local barrier avoiding route.

The invention discloses a physical modeling-based robot obstacle avoidance path planning method, which comprises the following steps of: setting a gravitational field grid and a distance information grid of a robot working region to establish a robot double-grid information graph; based on the double-grid information graph, searching all feasible paths by using a directional ergodic method; calculating a comprehensive evaluation value of a gravity value and a distance value; and taking a path scheme corresponding to the maximum value as a robot optimal obstacle avoidance path planning scheme.By using the method, the defect that geometric attributes of moving objects and obstacles in robot path planning are not considered is overcome; during path searching after double grids are established by the method, robot obstacle avoidance path planning is performed according to the value of the double grids; and thus, the problems of the shortest path and moving safety are both taken into consideration, the efficiency of path planning is increased, and damage accidents which probably occur in path optimization are reduced.

The invention provides a multi-robot path planning and coordination collision prevention method based on fuzzy logic. The method comprises the steps of confirming an input variable and an output variable of a fuzzy controller by setting up the fuzzy controller with robots as a system, using related languages to describe the input variable and the output variable of the fuzzy controller, confirming a qualitative reasoning principle according to the fuzzy control theory, setting up fuzzy control rules according to input signals and output signals of the fuzzy controller, selecting a subordinating degree function of each input language variable and a subordinating degree function of each output language variable, finally, conducting defuzzification, conducting voting on the basis of the maximum principle of the subordinating degree functions, conducting corresponding motions on the robots, and completing the task for planning a path of a single robot. On the basis of the method, the other robots are regarded as dynamic front barriers, and the aim of coordination collision prevention of the multiple robots can be achieved.

The invention provides an unknown environment route planning method of an underwater cleaning robot, which is a self-adaptive learning fuzzy control method for planning a track in an unknown environment. The method is characterized in that: by simulating the route planning thought, obstacle avoiding through and intelligent thoughts for making a decision for determining the priority of quick planning and obstacle avoiding, three different sub fuzzy controllers are put forward correspondingly for solving three kinds of problems. Meanwhile, according to the estimation of the movement results of a controlled robot, the rule base of the fuzzy controller is modified correspondingly to make the fuzzy controller can handle more complex external disturbance and effectively solve the problem of U-shaped obstacles and symmetric obstacles, so that the robot can complete a planned task and arrive at a destination in a more complex environment. The method eliminates the uncertainty influences of an underground complex environmental factor on the route planning of the robot, improves the movement safety of the robot and enables the robot to well adapt to the complex underground industrial environment.

The invention discloses a path planning method for the intelligent inspection robot of a substation. The method includes the following steps that: layered characterization is performed on the operating environment of an inspection robot within a substation, and a layered map is created; the electronic text of the work ticket of the substation is analyzed, and work task information is obtained; andoptimal path planning is carried out through comprehensively using the layered map and the work task information. According to the method of the invention, on the basis of a characteristic that the electric power industry pays much attention to safety, constraint conditions such as a maintenance plan and a constraint condition that branch paths in the substation are narrow are comprehensively considered; path planning is performed in advance, and therefore, an inspection area can be avoided reasonably, an equipment inspection sequence can be optimized, and the inspection efficiency and intelligence level of the intelligent inspection robot of the substation can be improved with safety requirements satisfied.

An apparatus, method and computer-readable medium planning a path of a robot by planning an optimal path while satisfying a dynamic constraint. In a process of searching for a motion path from a start point to a goal point while extending a tree from a start point of a configuration space to generate a path, along which a manipulator of the robot is moved in order to perform a task, an optimal path is generated responsive to the dynamic constraint of the manipulator of the robot to generate stable motion satisfying momentum and Zero Moment Position (ZMP) constraint. Accordingly, path planning performance is improved and a path satisfying a kinematic constraint and a dynamic constraint is rapidly obtained.

The invention relates to a path planning method for mobile robots based on a particle swarm optimization algorithm. The prior path planning method for the mobile robots has single path selection and is easy to come to a dead end. The method comprises the concrete steps of: modeling the environment first; using a polygon to represent an obstacle; using a point to represent a robot, using a small square frame to represent the original position of the robot; and using a cross to represent a target point, wherein a starting point of the robot is marked as S, and the target point is marked as G; planning paths of the robot by utilizing the particle swarm optimization algorithm; and finally performing the deep first search on the planned paths. The method adds the deep first search into a polar coordinate particle swarm. By the method, the robot can effectively find one collision-free path in most of complex environments, and finally reach target points.

The invention provides a robot path planning method based on elliptic constrains so that a robot can avoid an obstacle under the condition that the shape and position of the obstacle in the environment are not known. The method includes the following steps of obtaining robot movement information, obstacle information and target environment information, determining the conditions under which the robot collides with the obstacle, and setting up a movable obstacle avoiding model based on the elliptic constrains according to the conditions under which the robot collides with the obstacle, wherein the constrain conditions satisfied by the elliptic include that the robot is located in the ellipse, the detected obstacle point is located outside the ellipse, and the final target point is located on the boundary of the ellipse or outside the ellipse, and global path planning is conducted through the Bug path planning algorithm. The shortest advance path of the robot is planned, and the aim of avoiding the obstacle in real time is achieved.

The invention relates to a path planning method for improving RRT algorithm, and belongs to the technical field of robot path planning. The method introduces a target gravity strategy to overcome theshortcomings of the RRT algorithm. In the process of expansion, a random tree is randomly expanded when encountering obstacles; when no obstacles are encountered, the target gravity strategy is introduced to correct the expansion direction of the random tree; and a two-way expansion method is introduced to extend from a starting point and a target point respectively. The improved method improves planning efficiency and smoothes a planned path. Finally, the planned path is smoothed to be smoother.

The invention relates to a transformer substation inspection robot path planning navigation method. The method comprises the steps that a robot walks one circle around a transformer substation, and a two-dimensional grid map of the transformer substation is generated; transformer substation equipment image information is scanned, and a feature image is selected to serve as a road and equipment identification basis; an optimal inspection path is planned; surrounding environment information is scanned to generate a two-dimensional grid map of the surrounding environment, the position where the inspection robot is located is identified by comparing the surrounding environment map with the transformer substation map, and rough positioning is achieved; surrounding equipment image information is acquired, the equipment position is identified by comparing the surrounding environment image information with an equipment feature image, errors generated in the map matching link are corrected, and then higher-precision positioning is achieved; whether map matching positioning and visual positioning are in a same area or not is inspected, if yes, it is proved that positioning is accurate, and if not, it shows that positioning is wrong, and then map matching positioning and visual positioning are conducted again. Therefore, the positioning navigation reliability and accuracy are greatly improved.

The invention, which belongs to the field of intelligent algorithm optimization, provides a reinforced learning robot path planning algorithm based on a potential field in a complex environment, thereby realizing robot path planning in a complex dynamic environment under the environmental condition that a large number of movable obstacles exist in a scene. The method comprises the following steps:modeling environment space by utilizing the traditional artificial potential field method; defining a state function, a reward function and an action function in a Markov decision-making process according to a potential field model, and training the state function, the reward function and the action function in a simulation environment by utilizing a reinforcement learning algorithm of a depth deterministic strategy gradient; and thus enabling a robot to have the decision-making capability of performing collision-free path planning in a complex obstacle environment. Experimental results showthat the method has advantages of short decision-making time, low system resource occupation, and certain robustness; and robot path planning under complex environmental conditions can be realized.

The invention discloses a robot path planning method adopting multi-subgroup coevolution particle swarm optimization to perform real-time rolling optimization obstacle avoidance processing, which can enable a robot to realize autonomous navigation in a working condition with stationary obstacles at unknown positions. The method has the following advantages: the method can realize autonomous navigation of the robot in a working condition with stationary obstacle at unknown position; the method introduces group mass center strategy to the multi-subgroup coevolution, so as to increase the search capacity of the population; compared with a conventional path planning method which adopts PSO (Particle Swarm Optimization) and CPSO (Coevolution Particle Swarm Optimization), the method provided by the invention adopts survival of the fittest strategy, thereby being more advantageous in respect to rate and accuracy of evolution convergence; the method provided by the invention can real-timely plan an effective obstacle avoidance path in a complex obstacle environment, and has the advantages of good robustness, high solving efficiency, and the like.

The invention belongs to the field of autonomous path planning of robots and provides a robot path planning method based on an elliptical tangent line structure. According to the method disclosed by the invention, an obstacle area is encircled by virtue of an ellipse, binary searching of the path is performed by utilizing tangent line generation of points to the ellipse, and the searched path is subjected to smooth transition by virtue of an arc edge of the ellipse. The method comprises the following steps: bad point rejection and cost map generation on the acquired data, performing minimum encircling ellipse generation and other operations on a specific obstacle area, performing a series of processing such as tangent line generation of points to the ellipse, approximate common tangent generation of the ellipse to ellipse and the like, obtaining all alternate paths from an initial point to a target point, and finally selecting the optimal path through a cost function. According to the path planning method provided by the invention, the problems in the traditional method that the calculated quantity is great, the path is not smooth enough and the like are solved, an optimal and smooth path can be obtained in less time, and the application requirement on rapid path planning in a two-dimensional robot space can be met.