CN113295167B - Obstacle avoidance method for indoor robot - Google Patents
Obstacle avoidance method for indoor robot Download PDFInfo
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- CN113295167B CN113295167B CN202110526378.5A CN202110526378A CN113295167B CN 113295167 B CN113295167 B CN 113295167B CN 202110526378 A CN202110526378 A CN 202110526378A CN 113295167 B CN113295167 B CN 113295167B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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Abstract
The invention provides an indoor robot obstacle avoidance method which is mainly used for an indoor robot and can effectively avoid the phenomenon that the robot cannot pass through the range of an area where a moving obstacle passes due to the obstruction of a dynamic obstacle and is not intelligent enough when a far path is selected in the traveling process of the robot. The algorithm is based on a move _ base navigation framework of an ROS system, and a decision-making behavior for obstacle avoidance based on costmap is optimized emphatically. The invention improves the algorithm for updating the barrier data, can process the moving barrier and can not avoid the pedestrian who has already walked around; when the barrier is processed to be updated, redundant barrier data can be effectively and timely removed; the obstacle data are added or deleted only when being dynamically updated, and if the traveling route is not influenced during normal walking, the obstacle data are updated without wasting the calculation power, so that the calculation power can be saved.
Description
Technical Field
The invention relates to an indoor robot obstacle avoidance method, and belongs to the technical field of automatic driving.
Background
The ROS community is a mature and practical robot operating system in the field of the existing robot, and the ROS community maintains bottom hardware and upper software of the robot through the rosmaser, drives complex sensors, has a positioning function, a navigation decision and path planning function and controls the bottom layer to be packaged into a node which is easy to maintain and based on the rosmaser. However, the current navigation decision-making part has the problems of low efficiency and low accuracy, the existing barrier data cannot be updated and deleted in time, and only when no feasible path capable of reaching the target position exists in the map with the added barriers, the decision-making layer can clear all data and then perform a new decision-making process.
Disclosure of Invention
The invention aims to provide an indoor robot obstacle avoidance method, which can effectively avoid the left-right swinging and in-situ rotation of the robot among pedestrians and can make correct decisions in flowing pedestrians in time.
In order to achieve the purpose, the invention is realized by the following technical scheme:
step 1, adding costmap data into a global path by the robot according to barrier data obtained by a sensor, wherein the hierarchy is an obstacle layer and is used for providing data for path planning barriers;
step 2, newly adding a costmap layer and a dynamic layer, wherein the hierarchy is used for acquiring real-time data of the obstacle in real time;
step 3, the robot updates the obstacle layer data, global planning is carried out, if the global planning passes through the obstacle layer data points, the step 4 is carried out, and if not, the step 5 is carried out;
step 4, if the obstacle layer changes, processing the data in the obstacle layer and the dynamic layer, and then carrying out global planning again; if the obstacle layer is not changed, performing step 3;
step 5, local planning is carried out, and if the local planning does not pass through the barrier data point, a corresponding speed control command is sent according to the robot motion model; if the local plan passes through the obstacle data point, then go to step 3;
preferably, the specific steps for processing the obsacle layer and the dynamic layer in the step 4 are as follows: acquiring obstacle data of an obstacle layer in real time, if the data is updated, adding obstacle data points in the layer, then acquiring dynamic layer data updated according to the obstacle data and comparing the updated dynamic layer data with the originally added obstacle layer, if certain coordinate point data is repeated, retaining obstacle layer data, if certain coordinate point data is dynamic layer and has no obstacle layer, clearing all data, acquiring sensor data again, then adding the sensor data to the obstacle layer, and if certain coordinate point data is obstacle layer and has no dynamic layer, deleting the obstacle layer data of the point.
The invention has the advantages that:
1. the algorithm for updating the barrier data is improved, the moving barrier can be processed, and pedestrians who have already walked cannot be avoided by winding the barrier;
2. when the barrier is processed to be updated, redundant barrier data can be effectively and timely removed;
3. the obstacle data are added or deleted only when being dynamically updated, and if the traveling route is not influenced during normal walking, the obstacle data are updated without wasting the calculation power, so that the calculation power can be saved.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
When an existing robot uses move _ base navigation, firstly, a cost map is created based on a created map, the cost map is divided into different cost values according to an algorithm, the location of an obstacle is usually the highest and is 100, a passable area is usually 1, and when the robot is used, the robot has a certain volume and is usually divided into 100-1 cost intervals with stepwise decrement within a certain range around the obstacle in order to avoid the robot being too close to the obstacle. Then, global path planning (similar to the navigation of the high-level map) is carried out by using an A or D algorithm, then, obstacle data are updated in real time according to different sensors (laser radar, a camera, ultrasonic waves and the like), and then, local path planning is updated in real time according to the obstacle data. However, the existing obstacle data cannot be updated and deleted in time, and only when no feasible path for reaching the target position exists in the map to which the obstacle is added, the decision layer will clear all the data, and then a new round of decision process is performed.
The invention relates to an indoor robot obstacle avoidance method, when a mobile robot carries out self-pilot navigation, global planning (similar to Gaode map navigation) is firstly carried out on a created map, then obstacle data near the robot is obtained through a sensor and is added to an obstacle layer of costmap, however, the obstacle data may appear on a globally planned route, obstacle layer data needs to be added in real time, when the obstacle layer data is updated again, the obstacle data is obtained through adding a dynamic layer (only used for obtaining the information of the sensor and not added to the map to influence obstacle avoidance), then the dynamic layer data and the obstacle layer are compared, if certain coordinate point data is repeated, the obstacle layer data is kept, if certain coordinate data is existed and obstacle layer data is not existed, all data are cleared, and the sensor data is obtained again, and then adding the position data to an obsaclelayer layer, if the obsaclle layer at a certain coordinate point has data and the dynamic layer does not have data, deleting the obsacle layer data at the point, and then performing global planning again, wherein the generated new path can bypass the obstacle and cannot be influenced by the moving obstacle.
Claims (1)
1. An indoor robot obstacle avoidance method is characterized by comprising the following steps:
step 1, adding costmap data into a global path by the robot according to barrier data obtained by a sensor, wherein the hierarchy is an obstacle layer and is used for providing data for path planning barriers;
step 2, a costmap layer and a dynamic layer are added, and the hierarchy is used for acquiring real-time data of the obstacles in real time;
step 3, the robot updates the obsacle layer data to perform global planning, if the global planning passes through the obsacle layer data points, the step 4 is performed, otherwise, the step 5 is performed;
step 4, if the obstacle layer changes, processing the data in the obstacle layer and the dynamic layer, and then carrying out global planning again; if the obstacle layer is not changed, performing step 3; the method comprises the following specific steps:
acquiring obstacle data of an obstacle layer in real time, if the data is updated, adding obstacle data points in the obstacle layer, then acquiring dynamic layer data updated according to the obstacle data and comparing the updated dynamic layer data with the originally added obstacle layer, if certain coordinate point data are repeated, retaining the obstacle layer data, if certain coordinate point data are available in the dynamic layer and not available in the obstacle layer, clearing all data, reacquiring sensor data, then adding the sensor data to the obstacle layer, and if certain coordinate point data are available in the obstacle layer and not available in the dynamic layer, deleting the obstacle layer data of the certain coordinate point;
step 5, local planning is carried out, and if the local planning does not pass through the barrier data point, a corresponding speed control command is sent according to the robot motion model; if the local plan passes the obstacle data points, step 3 is performed.
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