CN111142542A - Omnidirectional mobile robot autonomous navigation system based on VFH local path planning method - Google Patents
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- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- 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
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- 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
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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- G05D1/02—Control of position or course in two dimensions
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- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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Abstract
The invention provides an omnidirectional mobile robot autonomous navigation system based on a VFH local path planning method. The method comprises the steps of firstly constructing a grid map of an environment by using a laser radar installed on a mobile robot, then drawing a global path from the current position of the mobile robot to a desired target position by a global path planning method, and finally selecting a local target point from the global path to plan a local path. The local path planning method improves a VFH + obstacle avoidance method, so that the mobile robot can select the optimal obstacle avoidance direction, and meanwhile, the condition that the VFH + can select the non-optimal obstacle avoidance direction under special conditions is eliminated by combining the idea of A route planning, so that the planned local path is as short as possible under any conditions. After the local path is planned, the mobile robot is controlled to move along the direction of the local path, and meanwhile, the local path is updated at a certain frequency, so that the mobile robot can autonomously navigate in a scene with a complex and changeable environment.
Description
Technical Field
The invention relates to an omnidirectional mobile robot autonomous navigation system based on a VFH local path planning method, and belongs to the technical field of mobile robot autonomous navigation.
Background
With the development of the robot technology, more and more robots, especially mobile robots, are widely used in various aspects of people's daily life, such as logistics storage robots, inspection robots, home service robots, and the like. Among mobile robots, an omni-directional mobile robot is popular because it can move in any one direction. The key to mobile robotics is its autonomous navigation capability in moving from a current position to a target position. The autonomous navigation technology of the mobile robot relates to environment perception, precise positioning, decision and planning, control and execution. On the basis of environment perception and accurate positioning, the quality of decision and planning directly determines the performance of autonomous navigation. The decision and planning is mainly to perform path planning, which can be divided into global path planning and local path planning according to the known degree of the surrounding environment. In the case of completely sensing the surrounding environment, an optimal global path may be drawn by using a global planning algorithm such as a ×, however, when the surrounding environment changes (for example, a dynamic obstacle exists), the robot may not move safely to the target position along the existing global path. At present, some existing methods applied to local path planning of a mobile robot, such as a Dynamic Window Analysis (DWA), have many parameters, are not easy to adjust, and sometimes cause a navigation failure, specifically, the method is always rotated at a non-target position.
Furthermore, chinese patent No.: CN100491084C, name: a mobile robot local path planning method based on binary environment information is disclosed. The invention discloses a non-omnidirectional mobile robot local path planning method based on binary information. But the method greatly simplifies the environment, has higher requirements on the working environment and is not easy to popularize.
Chinese patent No.: CN104407616A, name: a mobile robot dynamic path planning method based on immune network algorithm. The invention discloses a mobile robot local path planning method based on an immune network algorithm. According to the method, the obstacles of the working environment are represented by rectangular boxes, then visual processing is carried out, and finally the path of the mobile robot is obtained through iteration based on an immune network algorithm. However, the immune network algorithm generates the initial antibody (path) population in a random manner, and adds the randomness of high-frequency variation and new antibody (path) addition, so that the evolution algebra and complexity required for solving the optimal path in each planning are uncertain.
Chinese patent No.: CN108549385A, name: a robot dynamic path planning method combining an A-star algorithm and a VFH obstacle avoidance algorithm. The invention discloses a dynamic path planning method combining an A-x algorithm and a VFH obstacle avoidance algorithm, which is used for local path planning when a robot meets an obstacle in the motion process. The method comprises the steps of firstly representing the environment around the robot as a grid map, then planning an initial global path from a starting point to a target point by applying an A-x algorithm, dividing the initial global path into a plurality of equidistant path sections by using a stage target point, then enabling the robot to move to the stage target point along the initial path, and if an obstacle is encountered, avoiding the obstacle by using a VFH (vacuum pulse height) until the robot moves to a final target point. However, the VFH obstacle avoidance algorithm does not explicitly consider the geometric dimensions of the robot, but compensates according to experience, and obviously, it cannot be completely ensured that the robot can avoid the obstacles encountered in the moving process, and there are two obstacle avoidance directions with the minimum cost in the VFH algorithm, in this case, the robot may select a non-optimal obstacle avoidance direction, and thus the robot cannot move to the target point in the shortest path.
The VFH + obstacle avoidance method explicitly considers the geometric size of the robot on the basis of the VFH obstacle avoidance method, and ensures the safety of the robot in obstacle avoidance, but it still fails to avoid the possibility that the robot may select a non-optimal obstacle avoidance direction under special circumstances. In summary, the invention provides an omnidirectional mobile robot autonomous navigation system based on a VFH local path planning method by expanding the VFH + in combination with the concept of a path planning.
Disclosure of Invention
The invention relates to an omnidirectional mobile robot autonomous navigation system based on a VFH local path planning method, which aims to: the omnidirectional mobile robot can carry out autonomous navigation in a dynamic environment in a simple, safe and reliable mode.
1. The invention builds the autonomous navigation frame of the omnidirectional mobile robot. The method specifically comprises the following steps: firstly, constructing a static grid map of the running environment of the omnidirectional mobile robot; then, a global path from the current position of the mobile robot to the target position is planned on a map according to the given target position; and finally mapping the dynamic environment information detected by the sensor to a constructed map, and then realizing the autonomous navigation of the mobile robot by repeatedly calling a local path planning method.
2. The invention improves the VFH + local obstacle avoidance method. The method specifically comprises the following steps: firstly, constructing a vector field histogram of the obstacle according to the distance between the obstacle and the mobile robot; then determining which directions in the histogram are accessible to the mobile robot according to the diameter of the circumscribed circle of the mobile robot; and finally, selecting candidate obstacle avoidance directions according to the current direction of the mobile robot and the direction of the target position relative to the mobile robot.
3. The invention combines the concept of A path planning to expand the improved VFH +. And expanding the local path by using the VFH + local obstacle avoidance direction again within a certain distance in the candidate obstacle avoidance direction until a local target point is reached or the length of the planned path reaches an expected value.
The invention has the advantages that:
1. according to the invention, the navigation is carried out by repeatedly calling the local path planning method, so that the mobile robot can well carry out autonomous navigation in a complex dynamic environment.
2. The original VFH + local obstacle avoidance method is improved, the obstacle avoidance condition of the mobile robot is considered more comprehensively, and the mobile robot can select the obstacle avoidance direction as optimal as possible.
3. The invention expands the improved VFH + method by combining the concept of A-path planning, and avoids the situation that when the VFH + is used, a non-optimal obstacle avoidance direction is selected under the condition that two obstacle avoidance directions with the minimum cost exist, thereby ensuring that the planned local path is as short as possible.
4. When the environment of the robot is free of dynamic obstacles, the method can optimize the existing global path, because the global path planned by the grid-based global planning method is only optimal for a grid map (discrete), and the actual environment is continuous. For example, when the global path planned by a has an included angle, two sides of the included angle are not shortest, at least a curve tangent to the two sides is shorter, and when the VFH local path planning method is repeatedly invoked, the path of the motion of the omnidirectional mobile robot is better than the path planned by a.
Drawings
FIG. 1 is a flow chart of autonomous navigation of an omnidirectional mobile robot according to the present invention
FIG. 2 is a flow chart of the local path planning of the present invention
FIG. 3 is an exemplary diagram of determining an obstacle avoidance direction by the VFH + obstacle avoidance method
FIG. 4 is a diagram illustrating an exemplary method for planning a local path according to the present invention
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings so that the objects, technical solutions and advantages of the present invention will be more apparent. It should be noted that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the embodiment, an autonomous navigation system of the omnidirectional mobile robot based on the VFH local path planning method is realized, 4 Mecanum wheels capable of moving in an omnidirectional manner and 1 laser radar with higher precision are installed on the omnidirectional mobile robot, so that the mobile robot can move in an omnidirectional manner, sense the surrounding environment and construct and update a grid map.
Fig. 1 is a flow chart of autonomous navigation of a mobile robot. Firstly, a grid map of a mobile robot running environment is constructed by using a laser radar installed on a mobile robot platform, and obstacles in the grid map expand according to the radius of a circumscribed circle of the mobile robot, so that the mobile robot can be regarded as mass points, the safety of the mobile robot in obstacle avoidance is easily ensured, and then a global path planning and calculating rule is used for drawing a global path based on the grid map. And finally, selecting a local target point from the global path, and realizing autonomous navigation by repeatedly calling a local path planning method and controlling the mobile robot to move along the local path.
Fig. 2 is a flow chart of the local path planning of the present invention, and is a specific implementation manner of the VFH in fig. 1 for planning the local path. Fig. 3 is an exemplary diagram of determining an obstacle avoidance direction by using a VFH + obstacle avoidance method, which is a basic step of a VFH local path planning method, and a VFH planned path is obtained by expanding the VFH local path planning method by using the a principle. Fig. 4 shows an example of planning a local path by using a VFH local path planning method, which includes the following steps:
step 1: and determining a local target point on the planned global path. If the distance between the robot and the target point is smaller than the expected value of the length of the local path to be planned (2 m in this embodiment, which is 2-3 times the diameter of the circumscribed circle of the mobile robot in this embodiment), the target point is set as the local target point, otherwise, the point on the global path, which is 2m away from the current position of the robot, is set as the local target point.
Step 2: the example process of fig. 3 is utilized to determine candidate obstacle avoidance directions for the mobile robot at the current time position. The circular area is a sensing area of the mobile robot at the current position, the sensing radius is the diameter (0.75 m) of a circumscribed circle of the mobile robot, and the candidate obstacle avoidance directions are 2-3 directions relatively close to the target direction in the passable directions of the mobile robot.
And step 3: giving each obstacle avoidance direction a cost value, i.e. a cost value, depending on the direction of the mobile robot and the direction of the target relative to the mobile robot
Wherein
Representing the angle between the two directions,
is a candidate obstacle avoidance direction, is the current direction of the mobile robot,
is the direction of the target relative to the mobile robot.
And 4, step 4: and determining projection points in the obstacle avoidance direction. If the local target point is less than 0.4m in the obstacle avoidance direction, directly regarding the local target point as a projection point, otherwise, assuming that the robot moves 0.4m in the obstacle avoidance direction (the value should be smaller than the perception radius), regarding a point which is 0.4m away from the current position of the robot in the obstacle avoidance direction as a projection point of the robot in the obstacle avoidance direction.
And 5: and endowing each projection point with a cost value according to the principle of A. Has a cost value of
I.e. the cost value comprises two parts, the first part
The accumulated cost representing the movement of the mobile robot from the initial position to the projection point along the obstacle avoidance direction (the cost value in which obstacle avoidance direction is accumulated along which obstacle avoidance direction is moved), and the other part
Representing the expected cost of the robot moving from the proxel to the target position.
Step 6: selecting a projection point with the minimum cost from all projection points, judging whether the point is the local target point selected in the step 1, if so, judging whether the path from the mobile robot to the projection point is a planned local path, finishing the planning, if not, judging whether the length of the path from the mobile robot to the projection point is an expected value of the length of the local path, if so, judging that the path is also the planned local path, finishing the planning, if not, regarding the projection point as the current position of the robot, and returning to the step 2.
The planned local path, although not necessarily a path from the current position of the mobile robot to the selected local target point, is necessarily an excellent path for guiding the mobile robot to move from the current position to the local target point at the current time. Because the omnidirectional mobile robot can move along any direction, after the local path is planned, the omnidirectional mobile robot can track the local path only by giving the movement speed for controlling the mobile robot along the tangential direction of the local path. In the moving process of the omnidirectional mobile robot, a grid map constructed before is updated according to obstacle information detected by a laser radar, if a global path planned before is blocked by an obstacle on the updated grid map, an automatic navigation module calls a global path planning method to update the global path (although the situation is less), and then calls the method of the invention to update a local path at a frequency of 3Hz (which is longer than the time required for planning the local path), so that the mobile robot can avoid the obstacle according to the latest grid map, and therefore the mobile robot cannot completely move along the planned local path. Finally, the track obtained by the actual motion of the mobile robot is a smooth curve.
Claims (5)
1. An omnidirectional mobile robot autonomous navigation system based on a VFH local path planning method is characterized in that:
4 Mecanum wheels and 1 laser radar are installed on the mobile robot, so that the mobile robot can realize omnidirectional motion, sense the environment and construct a static grid map of the operating environment;
drawing a global path from an initial position to a desired target position on the constructed static map by using a global path planning rule;
and selecting a local target point from the global path, calling a VFH local path planning method and controlling the mobile robot to move along the tangential direction of the planned local path, and continuously repeating the process in the moving process of the mobile robot to realize the autonomous navigation of the mobile robot.
2. The omnidirectional mobile robot autonomous navigation system of claim 1, wherein: the VFH local path planning method is obtained by expanding an improved VFH + obstacle avoidance method by utilizing the idea of A path planning; the planned local path is not necessarily a path from the current position of the mobile robot to the selected local target point, but is necessarily an excellent path for guiding the mobile robot to move from the current position to the local target point at the current moment.
3. The omnidirectional mobile robot autonomous navigation system of claim 1, wherein: wheels which can enable the mobile robot to realize omnidirectional motion are arranged on the mobile robot of the autonomous navigation system; the laser radar has higher precision, can construct a static grid map and update the map according to the obstacle information detected in real time.
4. The omnidirectional mobile robot autonomous navigation system of claim 2, wherein: in the process of expanding the VFH + obstacle avoidance method by using the A-path planning idea, when a projection point in the obstacle avoidance direction is a selected local target point, or the path length from the projection point to the current position of the mobile robot along the obstacle avoidance direction is the expected length of the local path plan, the path from the projection point to the current position of the mobile robot is the planned local path.
5. The omnidirectional mobile robot autonomous navigation system according to claim 1 or 2, wherein: the mobile robot does not completely move along the local path planned by the VFH local path planning method, and then carries out next planning by calling the VFH, but carries out calling at a fixed frequency under the condition of a small part of movement so as to adapt to a complex and variable environment and ensure that the path actually operated by the mobile robot is a smooth track.
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Cited By (6)
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| CN111665844A (en) * | 2020-06-23 | 2020-09-15 | 北京三快在线科技有限公司 | Path planning method and device |
| CN112882475A (en) * | 2021-01-26 | 2021-06-01 | 大连华冶联自动化有限公司 | Motion control method and device of Mecanum wheel type omnibearing mobile robot |
| CN112947484A (en) * | 2021-03-31 | 2021-06-11 | 哈尔滨工业大学（深圳） | Visual navigation method and device for mobile robot in intensive pedestrian environment |
| CN112987721A (en) * | 2021-02-01 | 2021-06-18 | 哈尔滨工业大学 | Multi-AGV dispatching package and fusion method of global planning and local planning thereof |
| CN115437388A (en) * | 2022-11-09 | 2022-12-06 | 成都朴为科技有限公司 | Method and device for escaping from poverty of omnidirectional mobile robot |
| WO2023124621A1 (en) * | 2021-12-31 | 2023-07-06 | 追觅创新科技(苏州)有限公司 | Path planning method and system based on obstacle marker, and self-moving robot |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111665844A (en) * | 2020-06-23 | 2020-09-15 | 北京三快在线科技有限公司 | Path planning method and device |
| CN111665844B (en) * | 2020-06-23 | 2023-10-24 | 北京三快在线科技有限公司 | Path planning method and device |
| CN112882475A (en) * | 2021-01-26 | 2021-06-01 | 大连华冶联自动化有限公司 | Motion control method and device of Mecanum wheel type omnibearing mobile robot |
| CN112987721A (en) * | 2021-02-01 | 2021-06-18 | 哈尔滨工业大学 | Multi-AGV dispatching package and fusion method of global planning and local planning thereof |
| CN112947484A (en) * | 2021-03-31 | 2021-06-11 | 哈尔滨工业大学（深圳） | Visual navigation method and device for mobile robot in intensive pedestrian environment |
| WO2023124621A1 (en) * | 2021-12-31 | 2023-07-06 | 追觅创新科技(苏州)有限公司 | Path planning method and system based on obstacle marker, and self-moving robot |
| CN115437388A (en) * | 2022-11-09 | 2022-12-06 | 成都朴为科技有限公司 | Method and device for escaping from poverty of omnidirectional mobile robot |
| CN115437388B (en) * | 2022-11-09 | 2023-01-24 | 成都朴为科技有限公司 | Method and device for escaping from poverty of omnidirectional mobile robot |
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