CN112947486A - Path planning method and chip of mobile robot and mobile robot - Google Patents
Path planning method and chip of mobile robot and mobile robot Download PDFInfo
- Publication number
- CN112947486A CN112947486A CN202110348383.1A CN202110348383A CN112947486A CN 112947486 A CN112947486 A CN 112947486A CN 202110348383 A CN202110348383 A CN 202110348383A CN 112947486 A CN112947486 A CN 112947486A
- Authority
- CN
- China
- Prior art keywords
- node
- path
- mobile robot
- current position
- starting point
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
- G05D1/0236—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons in combination with a laser
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- General Physics & Mathematics (AREA)
- Aviation & Aerospace Engineering (AREA)
- Electromagnetism (AREA)
- Optics & Photonics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Manipulator (AREA)
Abstract
The invention relates to a path planning method of a mobile robot, a chip and the mobile robot, wherein the path planning method comprises the steps of determining a termination node of a planned path of the mobile robot in a pre-constructed map; when the current position node and the termination node of the mobile robot can reach directly, connecting the current position node and the termination node of the mobile robot to form a first planning path; when the current position node and the termination node of the mobile robot are not directly reachable, searching out an intermediate node which is directly reachable with the termination node from a map area between the current position node and the termination node of the mobile robot, and sequentially connecting the intermediate node and the termination node into a first planning path; and then searching the farthest node which is directly reachable relative to the searching starting point of the mobile robot on the first planned path, and optimally planning the first planned path into a second planned path by directly connecting the farthest node which is directly reachable with the searching starting point.
Description
Technical Field
The invention relates to the technical field of path planning in an indoor environment, in particular to a path planning method and a chip of a mobile robot and the mobile robot.
Background
The path planning is one of the most basic links of the mobile robot navigation, and is to search an optimal or approximately optimal collision-free path from a starting state to a target state according to task requirements. The robot navigation system has the advantages that a good moving path is provided for the robot, and the significance is achieved for improving the navigation performance of the robot. Common path planning algorithms are mainly divided into global path planning and local path planning according to a planning range, wherein the local path planning can help a robot judge whether obstacles exist in the surrounding environment and judge how to avoid the obstacles, the global path planning is more suitable for modeling the primary environment and the environment with dynamic obstacles, and the global path planning is more suitable for planning a path from a starting point to a terminal point for the robot under the condition that a map is known.
At present, the A-point search algorithm is the most classical and stable algorithm so far, heuristic search is carried out, the speed is high, but the planned path is not optimal and is close to an obstacle, so that the number of folding points and turning points of the path is increased. Therefore, the chinese patent CN102799781B searches for the farthest node and updates the search starting point according to the distance between the search starting point of the traversed path and the nodes of the remaining paths, so as to continuously calculate and detect the distance between the latest search starting point and the nodes of the remaining paths, thereby searching for a new farthest node, sequentially circulating until traversing to the end point of the traversed path, and then sequentially connecting the searched farthest nodes to form an optimized path, thereby implementing merging of the redundant nodes searched by the a-algorithm, but greatly increasing the number of node updates and the number of distance operations, and the robot will incur cost expenses such as unnecessary time in the moving process.
Disclosure of Invention
In order to solve the technical problems, the invention discloses a path planning method of a mobile robot, a chip and the mobile robot, which reduces path nodes and inflection points, shortens the path and improves the smoothness of the path, so that the navigation speed of the robot along the planned path is faster. The specific technical scheme is as follows:
the path planning method of the mobile robot comprises the steps of determining a termination node of a planned path of the mobile robot in a pre-constructed map; further comprising: when the current position node and the termination node of the mobile robot can reach directly, connecting the current position node and the termination node of the mobile robot to form a first planning path; when the current position node and the termination node of the mobile robot are not directly reachable, searching out an intermediate node which is directly reachable with the termination node from a map area between the current position node and the termination node of the mobile robot, and sequentially connecting the intermediate node and the termination node into a first planning path; then, on the premise of not updating the search starting point, searching a direct farthest node relative to the search starting point of the mobile robot on the first planned path, and optimally planning the first planned path into a second planned path by directly connecting the direct farthest node with the search starting point, wherein the search starting point is the current position node of the mobile robot; the current position node is the actual physical position of the mobile robot and is fixed and unchangeable; the direct-reaching means that the mobile robot moves along a search starting point of the mobile robot to the ray direction of the currently searched node, and no obstacle is detected on a straight line path from the search starting point to the currently searched node; the direct farthest node is the direct farthest node that is farthest from the search start point.
Compared with the prior art, the method has the advantages that the first planning path with few inflection points and short path only having key nodes is searched by judging the direct condition between the current position node and the termination node of the mobile robot, unnecessary inflection points and inflection points of the first planning path are filtered in a mode that the direct farthest node is directly connected with the current position node, and further distance pose calculation amount in the moving process of the robot is reduced, so that the path optimization planning effect with low calculation power is achieved. The navigation speed of the robot along the planned path is made faster.
Further, the specific method for searching out an intermediate node which is directly reachable from the terminating node from the map area between the current position node and the terminating node of the mobile robot to connect the first planned path includes: setting an obstacle pre-touch node obtained by intersecting a line segment formed by connecting a current position node and a termination node with an obstacle edge as a search center, searching an intermediate node from an obstacle-free map area in an eight-neighborhood manner until the searched intermediate node and the termination node are in direct contact, and sequentially connecting the current position node, the obstacle pre-touch node, the intermediate nodes and the termination node to form the first planned path. According to the technical scheme, the termination node is not searched by only depending on the eight neighborhoods, but whether the termination node can be directly reached is judged in real time in the eight neighborhoods searching process, and the excessive searching calculation amount of the break points and the inflection points is reduced, so that a straight line path directly reaching the termination node from the current position node or the middle node is planned, and the times of turning of the mobile robot in the subsequent planned path are avoided.
Further, when the current position node and the termination node of the mobile robot are not directly reachable, a node with the minimum preset path cost is selected from the neighborhood of the obstacle pre-touch node as the intermediate node, so that the node selected from the neighborhood of the obstacle pre-touch node is expanded to a map area without obstacles; and then updating the search center by using the intermediate node, selecting a node with the minimum preset path cost in the neighborhood of the intermediate node as a new intermediate node, and repeating the steps until the intermediate node and the termination node are detected to be directly reachable.
Compared with the prior art, the technical scheme has the advantages that the planning touch point where the straight line of the current position node and the termination node is intersected with the edge of the obstacle is used as a new starting point, 8-field search is conducted on the barrier-free area until the area is traversed to reach the middle node which can reach the termination node, obvious guidance is achieved, the calculation amount of the path cost of the middle node and the derivative nodes in the searching process is further reduced, the map value of the node is read instead, the complex calculation of redundant path nodes is reduced, and the path searching efficiency is improved.
Further, the selected extending direction of the connection line of all the intermediate nodes does not point back to the current position node of the mobile robot or the obstacle pre-touch node. After the current position node, the obstacle pre-touch node, the intermediate nodes and the corresponding path cost values are searched and traversed, the intermediate nodes and the corresponding path cost values are stored in a linked list memory space according to a traversal sequence, so that the grid positions and the cost values can be compared in a subsequent searching process. Thereby leaving the necessary travel path for the mobile robot.
Further, when the current position node of the mobile robot is not directly reachable from the terminating node, on the premise that the search starting point is not updated, searching a farthest node on the first planned path, which is directly reachable from the search starting point of the mobile robot, and optimally planning the first planned path into the second planned path by directly connecting the farthest node with the search starting point specifically includes: after the search starting point of the mobile robot is determined, searching the farthest node which can be reached directly relative to the search starting point of the mobile robot one by one in the remaining nodes of the first planned path along the extending direction of the first planned path, and then connecting the search starting point of the mobile robot with the farthest node which can be reached directly; when a termination node is searched along the extending direction of the first planning path, combining a path segment between the direct farthest node and the termination node and a segment obtained by the connection to form a second planning path; wherein the achievable ratio is: the mobile robot moves from the search starting point to a straight line path of the target node along the ray direction from the search starting point to the target node on the first planning path without an obstacle; the direct farthest node is a direct target node farthest from the search start point; the target node comprises the current position node, the obstacle pre-touch node, the intermediate node searched in the eight-neighborhood mode sequentially and the termination node.
Compared with the prior art, on the premise that the current position node of the mobile robot is not changed as a search starting point, the technical scheme only takes the current position node of the mobile robot as the search starting point to obtain the direct farthest node, and filters the direct farthest node and redundant nodes of the current position node on the first planning path in a manner of directly connecting the direct farthest node with the current position node to optimize the second planning path with less folding points and small turning angles, so that the smoothness is more beneficial to the movement of the mobile robot.
Further, after the farthest node capable of directly reaching is found, the node between the farthest node capable of directly reaching and the current position node, which belongs to the first planned path, is deleted, and then a connection line between the farthest node capable of directly reaching and the current position node of the mobile robot and a remaining path segment of the first planned path are connected and combined to form the second planned path. The calculation storage space is reduced, and the moving speed of the mobile robot in the second planned road is improved.
A chip for storing program code, said chip being configured to perform said path planning method for a mobile robot. The practicability and the easy implementation degree of the planning path of the mobile robot provided with the chip are improved.
A mobile robot is provided with the chip and is used for executing the path planning method of the mobile robot. So as to achieve the effect of path optimization planning with low computational power. The navigation speed of the robot along the planned path is made faster.
Drawings
Fig. 1 is a flowchart of an embodiment of a method for planning a first planned path.
Fig. 2 is a flowchart of an embodiment of a method for optimized planning of a first planned path based on fig. 1.
Fig. 3 is a schematic diagram of planning a first planned path according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of optimally planning a first planned path into a second planned path according to an embodiment of the present invention.
Fig. 5 is a flowchart of a path planning method for a robot according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail below with reference to the accompanying drawings in the embodiments of the present invention. The embodiments described below and the features of the embodiments can be combined with each other without conflict. In the following description, specific details are given to provide a thorough understanding of the embodiments. However, it will be understood by those of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits may be shown in block diagrams in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, structures and techniques may not be shown in detail in order not to obscure the embodiments.
The embodiment of the invention discloses a path planning method of a mobile robot, which specifically comprises the following steps of: s501, controlling the mobile robot to start planning a path at a current position node, and then entering S502; before step S501 is executed, a terminal node of a planned path of the mobile robot is determined in a pre-constructed map, or a start node of the planned path is determined, and the terminal node and a node searched and planned by a routing algorithm in a subsequent step are stored in a storage space of a table. Preferably, the storage space of the table may be an array with a start node at the head end and a stop node at the tail end, in which all path nodes except the start node are adjacent to their previous nodes in logical positions, and used for storing the latest searched valid path node in the path planning stage and providing the reference path node and its parameters as references in the path optimization process.
Step S502, judging whether the current position node and the termination node of the mobile robot can be directly reached, if so, entering step S504, and if not, entering step S503. The current position node is the actual physical position of the mobile robot and is fixed and unchangeable.
Step S504, connecting the current position node of the mobile robot with the termination node to form a first planned path; then, the process proceeds to step S506, and the first planned path formed in step S504 is not optimized.
Step S503, searching out an intermediate node which is directly reachable with the termination node from the map area between the current position node and the termination node of the mobile robot so as to connect a first planned path, and then entering step S505. The search can adopt a conventional A-heuristic search path algorithm, including neighborhood search traversal; on the map of the embodiment of the invention, a ray is sent from the current position of the mobile robot to the termination node, and the area through which the ray passes may include an obstacle point, a planned target point and the termination node, so that the direct judgment of the connecting line between the current position node and the termination node of the mobile robot needs to be carried out, unnecessary node calculation is avoided on the basis of adhering to the shortest principle, and a part of inflection points are effectively avoided relative to the path drawn by the A-ray calculation rule, so that the path connected by the remaining nodes ensures that the angle of rotation each time when the robot moves is small, and the path is smoother.
And step S505, on the premise of not updating the search starting point, starting from the search starting point, searching a direct farthest node relative to the search starting point of the mobile robot on the first planned path, and optimally planning the first planned path into a second planned path by directly connecting the farthest node with the search starting point. Wherein, the searching starting point is the current position node of the mobile robot; the direct is as follows: the mobile robot does not detect an obstacle on a straight line path moving from the search starting point to the currently searched node along the ray direction from the search starting point to the currently searched node on the first planned path; the direct farthest node is the direct farthest node that is farthest from the search start point. Alternatively, the farthest node that is directly reached is a node that is located farthest from the current position node of the mobile robot except the end node, on the first planned path, and that is not an obstacle node in the attribute of the node through which the line segment connected to the search start point of the mobile robot passes, that is, a node at which the mobile robot is located farthest from the current position node of the mobile robot in the current walking direction from the search start point, but the line segment connected to the search start point of the mobile robot becomes unreachable as long as the line segment passes through the obstacle node.
In this embodiment, the direct reaching is to ignore the influence of the body width of the mobile robot, that is, to ignore the position relationship between the body edge of the mobile robot and the obstacle, and to directly consider only the position relationship between the body center of gravity of the mobile robot and the obstacle edge, and only one ray scanned by the center of gravity is covered by the walking of the mobile robot.
The direct-reaching means that the mobile robot moves along a ray direction of a current position node of the mobile robot towards a currently searched node, and no obstacle is detected on a straight-line path from the current position node to the currently searched node; or on a pre-constructed map area, a line segment formed by connecting the currently searched node and the current position node of the mobile robot does not pass through the node position for marking the obstacle, specifically: the mobile robot will not detect obstacles on the route from the current position node to the searched node, and the nodes of the obstacles are marked in the map in advance and can be stored in the storage space of the table. Therefore, the current location node may also be regarded as a starting node at which the mobile robot starts to calculate the planned path.
Compared with the prior art, the first planning path with few inflection points and short path is searched by judging the direct condition between the current position node and the termination node of the mobile robot, and unnecessary inflection points and inflection points of the first planning path are filtered in a mode that the farthest node which can be directly reached is directly connected with the search starting point, so that the distance pose calculation amount in the moving process of the robot is reduced, and the path optimization planning effect with low calculation power is achieved. The navigation speed of the robot along the planned path is made faster and easier to control when the robot moves along the second planned path.
As an embodiment, as shown in fig. 1, a path planning method for a first planned path is disclosed, including:
step S101, planning a route is started on a map constructed in advance, and then the process proceeds to step S102. This is that the mobile robot starts planning a navigation path at the current position node with the end node whose target position is pre-marked.
Step S102, judging whether the current position node and the termination node of the mobile robot can reach directly, if so, entering step S103, otherwise, entering step S104; it is necessary to determine whether an obstacle exists on a connection line between a current position node of the mobile robot and the termination node, and determine whether the mobile robot can travel straight from the current position to the termination node.
Step S103, connecting the current position node and the termination node of the mobile robot to form a first planned path, ending the path planning task, enabling the subsequent mobile robot to walk from the current position node to the termination node according to the first planned path, reducing unnecessary bent nodes, and enabling the subsequent mobile robot to reach the terminal point in a straight line mode, wherein the mobile path is more in line with the motion of the robot.
Step S104, under the condition that an obstacle exists on a connecting line of a current position node and a termination node of the mobile robot, setting an obstacle pre-touch node obtained by intersection of a line segment formed by connecting the current position node and the termination node and an obstacle edge as a search center, and then entering step S105. The obstacle pre-touch node is not necessarily the position where the mobile robot actually physically collides with the obstacle, but the mobile robot walks along the direction of the current position node pointing to the termination node and can touch the obstacle; and if the obstacle pre-touch node is not detected to be in the storage space of the table, the obstacle pre-touch node is stored in the storage space of the table.
Step S105, searching an intermediate node in the eight-neighborhood searching mode to the map area without obstacles, and then, the step S107 is carried out. Specifically, when the current position node of the mobile robot is not directly reachable from the terminating node, a node with the minimum preset path cost is selected as the intermediate node from the neighborhood of the obstacle pre-touch node, so that the node selected from the neighborhood of the obstacle pre-touch node is expanded to a map area without obstacles until a connecting line between the intermediate node and the terminating node does not pass through the obstacle node.
It should be noted that the eight-neighborhood searching method used in this embodiment is some specific steps of the a-algorithm in the prior art, and is capable of planning a node path that walks around the edge of an obstacle according to the position of the obstacle mark, and each node that is searched by the eight-neighborhood searching method of the a-algorithm is used as a path.
And S107, judging whether the currently searched intermediate node and the end node can be directly reached, if so, entering the step S108, and otherwise, entering the step S106. That is, whether the terminating node can be directly reached or supports clear visibility relative to the currently searched intermediate node is judged, whether an obstacle exists on the connecting line between the intermediate node and the terminating node searched in step S105 is judged, which is the judgment that needs to be performed each time one of neighborhood intermediate nodes is searched, so that the calculation amount of the path cost of the intermediate node in the searching process is reduced, and instead, the directability between two nodes is judged by reading the map value of the node, for example, when an obstacle exists, the corresponding map grid mark is 1, otherwise, the corresponding map grid mark is 0, so that the searching efficiency and the obstacle detection efficiency are improved, and the complex calculation of redundant path nodes is reduced.
It is worth noting that the obstacle pre-touch node is a first search center close to the obstacle planned by search, and subsequently, in the process of judging whether the intermediate node and the termination node can reach directly, the screened search center (intermediate node) is not necessarily close to the edge of the obstacle, so that the operation complexity is reduced.
And step S106, under the condition that the currently searched intermediate node and the termination node are not directly reachable, updating the search center determined in the step S104 by using the intermediate node searched in the step S105, and returning to the step S105 to continue searching in an eight-neighborhood mode. Therefore, the path cost calculation is not needed to be carried out on a node-by-node basis until the terminal point appears in the neighborhood of a certain node.
And S108, sequentially connecting the current position node in the step S102, the obstacle pre-touch node obtained in the step S104, the intermediate node sequentially searched and obtained in the previous step and the termination node into a first planned path. In this embodiment, the current position node is regarded as a starting position of the first planned path, the obstacle pre-touch node is regarded as a search center of eight neighborhoods in the foregoing steps to search for intermediate nodes, the intermediate nodes are also regarded as being continuously updated in the search process of the eight neighborhoods in the foregoing steps, and finally, the current position node, the obstacle pre-touch node, the intermediate nodes and the termination node are sequentially connected as the first planned path under the condition that the currently searched intermediate node and the termination node are directly reachable.
In the steps, a planning touch point where a straight line of a current position node and a termination node intersects with an obstacle edge is used as a new starting point, 8-neighborhood search is carried out on a barrier-free area until the planning touch point traverses to an intermediate node which can reach the termination node, obvious guidance is provided, the calculation amount of the path cost of the intermediate node and the derivative node thereof in the search process is reduced, instead of reading the map value of the node, the complex calculation of redundant path nodes is reduced, and the path search efficiency is improved. The first planned path planned and processed in this way can enable the mobile robot to directly reach the end point in a straight line mode as much as possible, and the actual motion situation of the mobile robot is better met.
In some practical navigation scenes, based on the foregoing steps, for a mobile robot equipped with a laser radar or a vision camera, the mobile robot emits a ray to a preset target point at a current position point, if there is no obstacle between the two points, the first obstacle encountered by the emitted ray is the target point, if there is an obstacle between the two points, the first obstacle encountered by the ray is the obstacle point, at this time, the eight-field search is used to extend to an obstacle-free area until the ray emitted at a certain point can directly reach the target point.
Preferably, the step may constrain the search condition in the process of searching for the nodes in the eight neighborhoods, so that the extending and expanding directions of the connecting lines of all the selected intermediate nodes do not return to the current position node of the mobile robot or the obstacle pre-touch node, thereby avoiding searching back the traversed path and reducing the working efficiency of the mobile robot. It should be noted that, after the search traversal, the current position node, the obstacle pre-touch node, the intermediate nodes and the path cost values corresponding to the intermediate nodes are stored in the storage space of the table according to the traversal order, so that the grid positions and the cost values are compared in the subsequent search process. Thereby leaving the necessary travel path for the mobile robot.
Preferably, when the new intermediate node found in step S105 is sent to the storage space of the table, it is first detected whether the grid coordinate of the new intermediate node coincides with the existing grid coordinate of the current position node, the obstacle pre-touch node, or the intermediate node in the storage space of the table; if no coincidence occurs, the new intermediate node is stored in the storage space of the table; if the path cost value corresponding to the new intermediate node is smaller than the path cost value corresponding to the node with the grid coordinate coincidence in the storage space of the table, the new intermediate node is stored in the storage space of the table to replace the node with the grid coordinate coincidence in the storage space of the table, so that the path node with lower path cost is stored, the principle of the shortest path is met, the length of the subsequent backtracking path is smaller, and the path planning efficiency is improved; and if the path cost value of the new intermediate node is greater than or equal to the path cost value corresponding to the node with the grid coordinate coincidence in the memory space of the linked list, giving up the new intermediate node, and directly reading the node with the grid coordinate coincidence in the memory space of the table as the search center. Therefore, the planned and connected path is shorter on the premise of not influencing the main extension trend of the searched intermediate node.
As shown in fig. 3, illustrating a schematic diagram of the mobile robot planning a path from a1 to the terminating node P at the current position node a1, the current position node a1 of the mobile robot may be regarded as a starting position node in the embodiment shown in fig. 3, and the mobile robot may be regarded as a circle having a certain body diameter width on a map.
As shown in fig. 3, if there is an obstacle 1 in the connection line (dashed line in fig. 3) between the current position node A1 and the terminating node P (the ray (dashed line in fig. 3) from the current position node A1 to the terminating node P passes through the obstacle 1), an intersection point a2 between the connection line A1P and the edge of the obstacle 1 is set as an obstacle pre-touch node, and this obstacle pre-touch node a2 is a position where the mobile robot is likely to physically collide with the obstacle 1, and in some scenarios, the mobile robot does not necessarily touch the obstacle 1 at the a2 position due to error influence such as map drift, but the a2 position is one of the positions close to the obstacle 1.
After determining the obstacle pre-touch node a2, selecting a node A3 with the minimum preset path cost as the intermediate node in the neighborhood of the obstacle pre-touch node a2 with the node a2 as a search center; then, it is determined that there is an obstacle 1 in the connection between the node A3 and the terminating node P (the ray from the node A3 to the terminating node P passes through the obstacle 1), the search center is updated using the node A3, the node a4 with the minimum preset path cost is selected as an intermediate node in the neighborhood of the node A3, and it is determined that the connection between the node a4 and the terminating node P also passes through the obstacle 1.
Then, the method continues to select the node a5 with the minimum preset path cost in the neighborhood of the node a4 as an intermediate node in the manner of the eight neighborhoods of the foregoing embodiment, and then determines that the connection to the node a5 and the terminating node P does not pass through the obstacle 1 but passes through the obstacle 2. Similarly, it can be determined that the connection between the intermediate node a6 and the terminating node P and the connection between the intermediate node a7 and the terminating node P all pass through the obstacle 2; until: and taking the intermediate node A7 as a search center, selecting a node A8 with the minimum preset path cost in the neighborhood of the node A7 as an intermediate node, judging that the connection line between the intermediate node A8 and the terminating node P does not pass through the barrier 2 and the barrier 1, determining that the intermediate node A8 and the terminating node P can be directly reached, and finishing the judgment and continuing the search in an eight-neighborhood mode.
Then, the node a1, the node a2, the node A3, the node a4, the node a5, the node a6, the node a7, the node A8, and the node P are connected in sequence, as shown by the solid line with black arrows in fig. 3, that is, the first planned path is obtained.
As another embodiment, in a case that the current position node of the mobile robot is not directly reachable from the terminating node, on the premise that the search starting point is not updated, the method for searching the farthest node on the first planned path that is directly reachable from the search starting point of the mobile robot and optimally planning the first planned path into the second planned path by directly connecting the farthest node with the search starting point specifically includes:
after the search starting point of the mobile robot is determined, starting from the current position node of the mobile robot, searching the farthest node which is directly reached relative to the search starting point of the mobile robot from the nodes in the rest nodes of the first planned path one by one along the extending direction of the first planned path. Specifically, from a current position node, searching nodes which can be reached directly on a first planning path one by one along the extending direction of the first planning path, and respectively calculating the distances between the nodes which can be reached directly and the current position node until the nodes are traversed to a termination node, so that under the condition that the nodes at the current position and the termination node of the mobile robot are not reached directly, the nodes at the farthest positions which can be reached directly are obtained by comparison; wherein the achievable ratio is: the mobile robot does not have an obstacle on a straight line path from the search starting point to the target node along the ray direction from the search starting point to the target node on the first planning path, and it should be noted that the calculation for detecting whether the obstacle exists on the straight line path from the search starting point to the target node is not like the calculation of a cost function for the node in a, but in the embodiment, only whether a grid covered by a line segment between the search starting point and the target node is an obstacle is read, and the calculation cost is far lower than the calculation of the node in a; the directly farthest node is the target node farthest from the search start point in order to exclude the inflection point on the first planned path as much as possible. The target node comprises the current position node, the obstacle pre-touch node, the intermediate node searched in the eight-neighborhood mode sequentially and the termination node.
And then connecting the search starting point of the mobile robot with the furthest node which can reach directly, specifically, when the terminal node is searched along the extending direction of the first planning path, combining and connecting a path segment between the furthest node which can reach directly and the terminal node and the segment obtained by the connection into the second planning path.
Because the furthest node capable of being reached directly is a necessary target node for the mobile robot to reach the termination node through fewer turns and shorter path length from the starting position, and the path section between the furthest node capable of being reached directly and the search starting point belongs to the first planned path has more nodes, larger turning angles and is attached to the edge of an obstacle, the path node belonging to the first planned path between the furthest node capable of being reached directly and the search starting point is not connected to the second planned path any more, so that the second planned path becomes smoother than the first planned path without optimized planning, and the mobile robot can walk on the second planned path more safely and quickly.
Compared with the prior art, the embodiment backtracks the first planned path on the premise of not updating the search starting point of the mobile robot, and eliminates redundant nodes between the furthest node which can reach directly and the search starting point on the first planned path as path nodes by directly connecting the furthest node which can reach directly and the search starting point, so that the second planned path obtained through optimization is smoother, the mobile robot can be controlled to move to the termination node on the second planned path by fewer break points and smaller turning angles, the movement of the mobile robot is facilitated, and the calculation burden of the coordinate position in the movement process is reduced.
It should be emphasized that, in the prior art, in order to overcome the problem of multiple inflection points and multiple inflection points of a planned path, the chinese patent CN102799781B needs to calculate distance information between each visible intermediate search starting point processed between a planning starting point and a planning end point for merging redundant nodes, in this process, the iterative calculation number of node distances is the result of the cumulative sum of the number of path nodes, assuming that there are n nodes between the starting node and the end node, the present invention starts from the search starting point of a mobile robot, in the remaining nodes of the first planned path, in the process of searching for the farthest nodes which are directly reachable relative to the search starting point of the mobile robot node by node along the extending direction of the first planned path, rays are transmitted to the nodes on the first planned path one by one from the fixed search starting point which is the starting node of the first planned path, if the line segment between the search starting point and the corresponding node passes through the obstacle, the mobile robot cannot directly cross to reach the corresponding node; if the line segment between the search starting point and the corresponding node does not pass through the obstacle, the mobile robot can directly cross over to reach the corresponding node and select the farthest node pointed by the ray to connect, so as to eliminate redundant path nodes between the farthest node and the current position node, and detect the map values of n nodes at most, because the invention does not update the search starting point relative to the Chinese patent CN 102799781B; n is the number of path nodes connected into the first planned path, including the current location node and the termination node. In the optimization method described in chinese patent CN102799781B, in order to obtain the farthest node required for the optimized path, a new farthest node and an updated judgment starting point are determined from the starting node by calculating the distance and the position where the farthest node meets the obstacle, and at least the accumulation times of numbers 1 to n, that is, n + (n-1) +.9 +2+1 times, are performed, and the number of generated distance operations is much greater than that of the present embodiment, so that the distance calculation amount is greatly increased, and the robot has unnecessary control trouble and time and other cost expenses in the moving process.
As an embodiment, an embodiment of an optimized planning method for a first planned path (a planning method for a second planned path) is specifically disclosed, and as shown in fig. 2, the method specifically includes:
step S201, after the foregoing embodiment goes to step S108 or step S103, starts to optimally plan the first planned path, and then proceeds to step S202.
Step S202, judging whether the current position node and the termination node of the mobile robot can be directly reached, if so, entering step S203, and otherwise, entering step S204. Of course, after the foregoing embodiment goes to step S103, the process may directly proceed to step S203 without determining whether there is an obstacle on the connection line between the current position node and the terminating node of the mobile robot.
And step S203, optimizing the first planned path. In some implementations, the end node is a target node on the first planned path that is farthest from the current location node, but in other implementations of navigation that require a turn-around, the end node is not the node on the first planned path that is farthest from the current location node. In the embodiment, in order to save search calculation resources of path nodes and reduce unnecessary inflection points for planning, the terminating node is directly set as a direct farthest node by ignoring a distance factor, so that the mobile robot directly crosses over in an unobstructed area, thereby greatly reducing calculation cost and improving search efficiency.
Step S204, after determining the search starting point of the mobile robot, traversing the target nodes (node a1, node a2, node A3, node a4, node a5, node a6, node a7, node A8, and node P shown in fig. 4) along the extending direction of the first planned path (as indicated by the black arrow in fig. 4), and not updating the search starting point until the target nodes are traversed to the end node; in this embodiment, the search starting point is the current position node, and the target nodes are traversed from the current position node a1 along the extending direction of the first planned path, where the target nodes include the current position node, the obstacle pre-touch node, the intermediate node, and the end node, and the backtracking of the first planned path in the fixed direction is started by performing this step.
Step S205, determining whether there is no obstacle in the connection between the current target node traversed (searched) on the first planned path and the search starting point of the mobile robot, if yes, going to step S206, otherwise, going to step S207. Namely, whether an obstacle exists on a straight line path moving from the current position node of the mobile robot to the current target node or not is judged.
Step S206, determining that the current target node is a direct node and is a direct node relative to the search starting point of the mobile robot, recording the relative distance between the current target node and the search starting point, and then entering step S208.
Step S207, finding a next target node along the extending direction of the first planned path, and then proceeding to step S208. Wherein the current target node and the next target node are two adjacent nodes on a first planned path. And sequentially and circularly traversing the nodes until the direct farthest node relative to the search starting point of the mobile robot is found.
Step S208, determining whether the target node searched in the previous step (step S207 or step S206) is a termination node, if yes, step S209 is performed, otherwise, step S205 is performed, and the neighboring target node is continuously traversed along the first planned path until the termination node is traversed. When it is determined in step S208 that the target node searched for in the foregoing step (step S207 or step S206) is the end node, step S206 records at most the distance between the immediately reachable target node preceding the end node and the search start point, and after step S209 is entered, the distance between the end node and the search start point is not recorded any more, because step S202 has already determined whether the search start point and the end node of the mobile robot are reachable, it is determined that the search start point and the end node of the mobile robot are not reachable.
Step S209, obtaining a direct target node corresponding to the maximum distance from the distances of all direct target nodes recorded in the previous step with respect to the search starting point, determining the direct target node as the farthest node, and then proceeding to step S210. In step S209, the distances of all the directly reachable target nodes recorded in the foregoing steps with respect to the current position node may be sorted in descending order or descending order, so as to obtain the directly reachable target node corresponding to the maximum distance. Wherein all the directly reachable target nodes recorded in the previous step do not include the termination node.
It should be noted that, in order to avoid repeated searching of the target nodes, each searched target node (including the intermediate node that has been searched in the first planned path) may be marked or put into a separate array, so as to reuse the data for detection, and only the necessary route is reserved.
Step S210, connecting the search starting point and the farthest node determined in step S209 that can be reached directly, deleting a path segment between the farthest node determined in step S209 that can be reached directly and the search starting point on the first planned path (referring to all nodes belonging to the first planned path between the farthest node determined in step S and the search starting point, but excluding the farthest node determined in step S211). At this time, the target nodes connected in step S210 are all between the search start point and the node farthest from the current position node.
And step S211, combining and connecting the residual path segments of the first planned path and the line segments obtained by connecting in the step S210 into a second planned path.
Compared with the prior art, the second planned path without unnecessary inflection points is derived in the steps S201 to S211 based on the mathematical principle that the straight line between two points is the shortest, so that the search times of the target nodes are reduced, the calculation storage space is reduced, and the moving speed of the mobile robot in the second planned path is increased. The smoothness and the safety of the path are improved. Compared with the first planned path, the second planned path eliminates a part of redundant path nodes in the first planned path, so that the robot needs to rotate at smaller angles, fewer nodes and fewer break points when moving along the second planned path, and the path is smoother.
As can be seen from fig. 3 and 4, the foregoing steps S201 to S211 are mainly performed on the partial path close to the obstacle 1 and the obstacle 2 in the first planned path, and the direction from the current position node a1 to the terminating node P is taken as the extending direction of the first planned path, and the nodes a2, A3, a4, a5, a6, a7, and A8 that have been searched and planned in the embodiment of fig. 3 are optimized, that is, redundant nodes are removed from the first planned path to optimize the remaining node connections to the second planned path. Specifically, in the embodiment shown in fig. 4, the node a1 is used as the search starting point, and the farthest node which is directly reachable from the search starting point of the mobile robot is searched for node by node in the remaining nodes of the first planned path from a1 along the extending direction of the first planned path. The line connecting the current position node a1 and the termination node P passes through the obstacle 1; with the current position node a1 as a center, starting from node a2 along an extension direction of an original first planned path (a connection line with a black arrow between node a1, node a2, node A3, node A4, node A5, node A6, node a7, node A8 and node P), rays are transmitted to node a2, node A3, node A4, node A5, node A6, node a7 and node A8 in sequence, as shown in fig. 4, a connection line between node a2 and node a1, a connection line between node A3 and node a1, a connection line between node A4 and node a1, a connection line between node A5 and node a1, a connection line between node A6 and node a1, a connection line between node a7 and node a1 (on a route where the corresponding movement is free of obstacles) and the two nodes are farthest straight lines, and then the selected information of the selected nodes is recorded; and the connection between node A8 and node a1 crosses barrier 2, then node A8 is not a direct node; if the connection between the node P and the node a1 passes through the obstacle 1, the node P is not a direct node, and although the distance between the node P and the current position node a1 is greater than the distance between the direct node and the current position node a1, the optimal planning of the first planned path may be terminated, and in some implementation scenarios, the optimal planning of the first planned path may be stopped when the connection between the node A8 and the node a1 passes through the obstacle 2, because it is determined whether the connection between the node P and the current position node a1 is direct.
By comparing the distance values in an ordered manner, node a7 is the furthest node that can go through, and then connects current position node A1 with node a7, the mobile robot traverses fewer break points, and smaller bending angles during walking along path A1a7 relative to the path segment between current position node A1 and node a7 of the first planned path.
As shown in the black solid line segment A1A7 in fig. 4, the line segment A1A7 is combined with the original line segment A7A8 and the original line segment A8P in the first planned path to form a second planned path, and as a result of optimizing the first planned path, the node A2, the node A3, the node A4, the node A5, and the node A6 are deleted, so that the original path segment A2A3, the path segment A3A4, the path segment A4A5, the path segment A5A6, and the path segment A6A7 in the first planned path are deleted, as shown by the thin dashed lines with arrows in fig. 4. The optimization planning process does not calculate a cost function for the nodes like an a-algorithm, more time is only required to read whether the grid passed by each connection line is an obstacle, the first planning path in fig. 3 is optimized, and then a part of redundant path nodes are removed, and the turning angle of the second planning path is reduced, as shown in fig. 4, when the first planning path is moved to a path node a6 of the first planning path, a 90-degree turning angle is required to be moved to a node a7, and the second planning path decomposes 90 degrees into smaller turning angles, specifically: the turning positions are only the node A7 and the node A8, and the turning angles at the node A7 and the node A8 are not larger than 90 degrees, so that the movement of the mobile robot is facilitated, most redundant path nodes are reduced and the burden of operation control is reduced compared with the first planning path shown in the embodiment of FIG. 3.
The embodiment of the invention also discloses a chip for storing the program code, and the chip is configured to execute the path planning method of the mobile robot in the embodiment. The first planned path planned by the embodiment avoids complex calculation of redundant nodes, and further improves the path searching efficiency. And optimizing the planned second planned path on the basis of the first planned path, thereby further improving the smoothness and the safety of the path. Therefore, after the algorithm of the embodiment is converted into a chip, the practicability and the easy implementation degree of the planning path of the mobile robot provided with the chip are improved.
The embodiment of the invention also discloses a mobile robot which is provided with the chip and used for executing the path planning method of the robot. So as to achieve the effect of path optimization planning with low computational power. The navigation speed of the robot along the planned path is made faster. The mobile robot includes but is not limited to a visual navigation robot and a laser navigation robot.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. The path planning method of the mobile robot comprises the steps of determining a termination node of a planned path of the mobile robot in a pre-constructed map; it is characterized by also comprising:
when the current position node and the termination node of the mobile robot can reach directly, connecting the current position node and the termination node of the mobile robot to form a first planning path;
when the current position node and the termination node of the mobile robot are not directly reachable, searching out an intermediate node which is directly reachable with the termination node from a map area between the current position node and the termination node of the mobile robot, and sequentially connecting the intermediate node and the termination node into a first planning path; then, on the premise of not updating the search starting point, searching a direct farthest node relative to the search starting point of the mobile robot on the first planned path, and optimally planning the first planned path into a second planned path by directly connecting the direct farthest node with the search starting point, wherein the search starting point is the current position node of the mobile robot; the current position node is the actual physical position of the mobile robot and is fixed and unchangeable;
the direct-reaching means that the mobile robot moves along a search starting point of the mobile robot to the ray direction of the currently searched node, and no obstacle is detected on a straight line path from the search starting point to the currently searched node; the direct farthest node is the direct farthest node that is farthest from the search start point.
2. The path planning method according to claim 1, wherein the specific method of searching for an intermediate node which is directly reachable from the terminal node in the map area between the current position node and the terminal node of the mobile robot to connect the first planned path comprises:
setting an obstacle pre-touch node obtained by intersecting a line segment formed by connecting a current position node and a termination node with an obstacle edge as a search center, searching an intermediate node from an obstacle-free map area in an eight-neighborhood manner until the searched intermediate node and the termination node are in direct contact, and sequentially connecting the current position node, the obstacle pre-touch node, the intermediate nodes and the termination node to form the first planned path.
3. The path planning method according to claim 2, wherein when the current position node and the terminating node of the mobile robot are not directly reachable, a node with the minimum preset path cost is selected as the intermediate node in the neighborhood of the obstacle pre-touch node, so that the node selected from the neighborhood of the obstacle pre-touch node is expanded to an obstacle-free map area;
and then updating the search center by using the intermediate node, selecting a node with the minimum preset path cost in the neighborhood of the intermediate node as a new intermediate node, and repeating the steps until the intermediate node and the termination node are detected to be directly reachable.
4. The path planning method according to claim 3, wherein the selected extending direction of the connection line of all the intermediate nodes does not point back to the current position node of the mobile robot or the obstacle pre-touch node.
5. The path planning method according to claim 4, wherein when the current position node of the mobile robot is not directly reachable from the terminating node, the method of searching for the farthest node on the first planned path that is directly reachable from the search starting point of the mobile robot without updating the search starting point, and optimally planning the first planned path as the second planned path by directly connecting the farthest node to the search starting point specifically comprises:
after the search starting point of the mobile robot is determined, searching the farthest node which can be reached directly relative to the search starting point of the mobile robot one by one in the remaining nodes of the first planned path along the extending direction of the first planned path, and then connecting the search starting point of the mobile robot with the farthest node which can be reached directly;
when a termination node is searched along the extending direction of the first planning path, combining a path segment between the direct farthest node and the termination node and a segment obtained by the connection to form a second planning path;
wherein the achievable ratio is: the mobile robot moves from the search starting point to a straight line path of the target node along the ray direction from the search starting point to the target node on the first planning path without an obstacle; the direct farthest node is a direct target node farthest from the search start point;
the target node comprises the current position node, the obstacle pre-touch node, the intermediate node searched in the eight-neighborhood mode sequentially and the termination node.
6. The path planning method according to claim 5, wherein after the farthest direct node is found, a node between the farthest direct node and the search starting point and belonging to the first planned path is deleted, and then a connection line between the farthest direct node and the search starting point and a remaining path segment connection of the first planned path are combined into the second planned path.
7. A chip for storing program code, characterized in that the chip is configured to perform the path planning method of a mobile robot of any of claims 1 to 6.
8. A mobile robot equipped with the chip of claim 7 for performing the path planning method of the mobile robot of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110348383.1A CN112947486A (en) | 2021-03-31 | 2021-03-31 | Path planning method and chip of mobile robot and mobile robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110348383.1A CN112947486A (en) | 2021-03-31 | 2021-03-31 | Path planning method and chip of mobile robot and mobile robot |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112947486A true CN112947486A (en) | 2021-06-11 |
Family
ID=76231411
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110348383.1A Pending CN112947486A (en) | 2021-03-31 | 2021-03-31 | Path planning method and chip of mobile robot and mobile robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112947486A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114200965A (en) * | 2022-02-21 | 2022-03-18 | 中国民航大学 | Planning method for safe moving path of airplane |
| CN114200939A (en) * | 2021-12-10 | 2022-03-18 | 江苏集萃智能制造技术研究所有限公司 | Robot anti-collision path planning method |
| CN114460968A (en) * | 2022-02-14 | 2022-05-10 | 江西理工大学 | Unmanned aerial vehicle path searching method and device, electronic equipment and storage medium |
| CN115328173A (en) * | 2022-10-14 | 2022-11-11 | 深圳市功夫机器人有限公司 | Mobile robot control method based on laser radar and mobile robot |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108981710A (en) * | 2018-08-07 | 2018-12-11 | 北京邮电大学 | A kind of complete coverage path planning method of mobile robot |
| CN110231824A (en) * | 2019-06-19 | 2019-09-13 | 东北林业大学 | Intelligent body paths planning method based on straight line irrelevance method |
| CN111289005A (en) * | 2020-03-16 | 2020-06-16 | 江苏理工学院 | Path finding method based on A star optimization algorithm |
-
2021
- 2021-03-31 CN CN202110348383.1A patent/CN112947486A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108981710A (en) * | 2018-08-07 | 2018-12-11 | 北京邮电大学 | A kind of complete coverage path planning method of mobile robot |
| CN110231824A (en) * | 2019-06-19 | 2019-09-13 | 东北林业大学 | Intelligent body paths planning method based on straight line irrelevance method |
| CN111289005A (en) * | 2020-03-16 | 2020-06-16 | 江苏理工学院 | Path finding method based on A star optimization algorithm |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114200939A (en) * | 2021-12-10 | 2022-03-18 | 江苏集萃智能制造技术研究所有限公司 | Robot anti-collision path planning method |
| CN114200939B (en) * | 2021-12-10 | 2024-02-27 | 江苏集萃智能制造技术研究所有限公司 | Robot anti-collision path planning method |
| CN114460968A (en) * | 2022-02-14 | 2022-05-10 | 江西理工大学 | Unmanned aerial vehicle path searching method and device, electronic equipment and storage medium |
| CN114200965A (en) * | 2022-02-21 | 2022-03-18 | 中国民航大学 | Planning method for safe moving path of airplane |
| CN115328173A (en) * | 2022-10-14 | 2022-11-11 | 深圳市功夫机器人有限公司 | Mobile robot control method based on laser radar and mobile robot |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112947486A (en) | Path planning method and chip of mobile robot and mobile robot | |
| CN109059924B (en) | Accompanying robot incremental path planning method and system based on A-x algorithm | |
| CN113156970B (en) | Path fusion planning method for traffic area, robot and chip | |
| CN111938513B (en) | Robot obstacle-crossing edgewise path selection method, chip and robot | |
| CN110231824B (en) | Intelligent agent path planning method based on straight line deviation method | |
| WO2023155371A1 (en) | Stable movement global path planning method for indoor mobile robot | |
| CN108444490B (en) | Robot path planning method based on depth fusion of visible view and A-x algorithm | |
| WO2022000960A1 (en) | Obstacle-crossing termination determination method, obstacle-crossing control method, chip, and robot | |
| CN111174798A (en) | Foot type robot path planning method | |
| CN113219975A (en) | Route optimization method, route planning method, chip and robot | |
| CN111949017B (en) | Robot obstacle crossing edge path planning method, chip and robot | |
| CN112306067B (en) | Global path planning method and system | |
| CN113485369A (en) | Indoor mobile robot path planning and path optimization method for improving A-x algorithm | |
| CN113190010A (en) | Edge obstacle-detouring path planning method, chip and robot | |
| US20220203534A1 (en) | Path planning method and biped robot using the same | |
| CN114281084B (en) | Intelligent vehicle global path planning method based on improved A-algorithm | |
| CN113110497A (en) | Navigation path-based edge obstacle-detouring path selection method, chip and robot | |
| CN113110499A (en) | Judging method of passing area, route searching method, robot and chip | |
| CN117075607A (en) | Unmanned vehicle path planning method suitable for improving JPS in complex environment | |
| CN113238549A (en) | Path planning method and chip for robot based on direct nodes and robot | |
| CN115685982A (en) | Navigation path planning method based on connected graph and iterative search | |
| CN110849385B (en) | Track planning method and system based on double-layer heuristic search conjugate gradient descent | |
| CN116429138A (en) | Path planning method, path planning device, vehicle and storage medium | |
| CN114353814B (en) | JPS path optimization method based on Angle-Propagation Theta algorithm improvement | |
| CN114924565A (en) | Welding robot path planning method, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 519000 2706, No. 3000, Huandao East Road, Hengqin new area, Zhuhai, Guangdong Applicant after: Zhuhai Yiwei Semiconductor Co.,Ltd. Applicant after: WUHAN University OF SCIENCE AND TECHNOLOGY Address before: Room 105-514, No.6 Baohua Road, Hengqin New District, Zhuhai City, Guangdong Province Applicant before: AMICRO SEMICONDUCTOR Co.,Ltd. Applicant before: WUHAN University OF SCIENCE AND TECHNOLOGY |