598 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 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.

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 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 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.

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 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.

The invention relates to a robot path planning algorithm based on an optimized ant colony algorithm. The algorithm comprises the following steps: S1, initializing an inspiring factor to construct thecomprehensive inspiring information for the movement of the robot according to a target gravitation generated by an artificial potential field and an ant colony algorithm; S2, updating pheromone in the art colony algorithm by adopting a wolves distribution rule; and S3, optimizing a planned path by utilizing a path optimization algorithm. By adopting the robot path planning algorithm, an optimum path can be rapidly and efficiently planned.

The invention discloses a mobile robot path planning method based on the binary quantum particle swarm optimization, which is characterized by comprising steps of 1, simplifying a robot into a point moving in a two-dimensional space, and then sensing the present position of the robot and the present positions of obstacles via the visual system, 2, processing all the obstacles sensed by the visual system of the robot into convex polygons, 3, discretizing the two-dimensional space into series grids, and performing binary encoding for eight probable motion directions of the robot at each grid, 4, defining the distance of the path between the starting point and the destination point as a target function required to be solved by the method, and 5, overall optimizing the target function in the step 4 by utilizing the binary quantum particle swarm optimization aiming to the discrete characteristics of robot path planning problems to obtain the optimum mobile robot path. The invention has the advantages of simple process, easy realizing, good robustness, high solving efficiency and the like.