CN105320134A - Path planning method for robot to independently build indoor map - Google Patents
Path planning method for robot to independently build indoor map Download PDFInfo
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- CN105320134A CN105320134A CN201510701063.4A CN201510701063A CN105320134A CN 105320134 A CN105320134 A CN 105320134A CN 201510701063 A CN201510701063 A CN 201510701063A CN 105320134 A CN105320134 A CN 105320134A
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Abstract
The invention discloses a path planning method for a robot to independently build an indoor map, comprising: step 1, initialization; step 2, employing a laser radar to collect data and perform SLAM; step 3, employing a static boustrophedon mode to decide a next quasi-composition node; step4, after deciding the next quasi-composition node, entering a local dynamic priority mode to determine a next composition node; step 5, deciding the next composition, and then utilizing an A * algorithm to plan the path to the next composition node; step 6, according to a planned path, a robot moving to the next composition point; step 7, utilizing a ''blind alley'' escape strategy to search for an escape node in the composition path; step 8, after finding an escape target, utilizing the A * algorithm to plan an escape path; and step 9, completing composition and finishing path planning. The path planning method is concise and visual, has a changeable resolution, and is easy to create and store.
Description
Technical field
The present invention relates to robotics, particularly relate to a kind of path planning algorithm of robot autonomous structure indoor map.
Background technology
The map describing method that current mobile robot commonly uses has four kinds: grating map, topological map, directly characterization method and geometric properties map, because robot is not too responsive to measured barrier particular location, one need be researched and developed there is succinct, resolution changable, the easily feature such as establishment and storage directly perceived, be applicable to the path planning of the foundation of indoor environment path planning cartographic model.
Summary of the invention
The object of the invention is to the path planning that a kind of robot autonomous structure indoor map is provided for the deficiencies in the prior art, this path planning is directly perceived succinct, resolution changable, easily create and store.
For achieving the above object, the present invention is achieved through the following technical solutions.
A path planning for robot autonomous structure indoor map, comprises the steps:
Step 1: initialization;
Step 2: adopt laser radar image data and SLAM to build map;
Step 3: adopt static ox to plough the next accurate composition node of mode decision;
Step 4: decision-making goes out next accurate composition node, then enter local dynamic station priority mode and determine next composition node;
Step 5: decision-making goes out next composition node, then utilize A* algorithmic rule to go out path to next composition node;
Step 6: according to the path cooked up, robot motion is to next composition point;
Step 7: use " blind alley " to flee from tactful searching in composition path and flee from node;
Step 8: after finding and fleeing from target, then utilize A* algorithmic rule to flee from path;
Step 9: composition completes, path planning terminates.
Wherein, described static ox is ploughed the formula of pattern and is
.
Wherein, the formula of described A* algorithm is
, wherein
refer to that start node S moves to the consumption figures of node;
refer to the consumption figures that joint movements is estimated to destination node G;
refer to the estimated value of the minimal cost path arriving destination node from starting point node through node.
Beneficial effect of the present invention is: the path planning of a kind of robot autonomous structure indoor map of the present invention, comprises the steps: step 1: initialization; Step 2: adopt laser radar image data and SLAM to build map; Step 3: adopt static ox to plough the next accurate composition node of mode decision; Step 4: decision-making goes out next accurate composition node, then enter local dynamic station priority mode and determine next composition node; Step 5: decision-making goes out next composition node, then utilize A* algorithmic rule to go out path to next composition node; Step 6: according to the path cooked up, robot motion is to next composition point; Step 7: use " blind alley " to flee from tactful searching in composition path and flee from node; Step 8: after finding and fleeing from target, then utilize A* algorithmic rule to flee from path; Step 9: composition completes, path planning terminates, and the present invention has succinct, resolution changable, the easy advantage creating and store directly perceived.
Accompanying drawing explanation
Utilize accompanying drawing to be further detailed the present invention below, but the embodiment in accompanying drawing does not form any limitation of the invention.
Fig. 1 is path planning algorithm flow process of the present invention.
Embodiment
Below in conjunction with concrete embodiment, the present invention will be described.
As shown in Figure 1, a kind of path planning of robot autonomous structure indoor map, comprises the steps:
Step 1: initialization;
Step 2: adopt laser radar image data and SLAM to build map;
Step 3: adopt static ox to plough the next accurate composition node of mode decision;
Step 4: decision-making goes out next accurate composition node, then enter local dynamic station priority mode and determine next composition node;
Step 5: decision-making goes out next composition node, then utilize A* algorithmic rule to go out path to next composition node;
Step 6: according to the path cooked up, robot motion is to next composition point;
Step 7: use " blind alley " to flee from tactful searching in composition path and flee from node;
Step 8: after finding and fleeing from target, then utilize A* algorithmic rule to flee from path;
Step 9: composition completes, path planning terminates.
Further, described static ox is ploughed the formula of pattern and is
.
Further, the formula of described A* algorithm is
, wherein
refer to that start node S moves to the consumption figures of node;
refer to the consumption figures that joint movements is estimated to destination node G;
refer to the estimated value of the minimal cost path arriving destination node from starting point node through node.
Need further explain, the present invention adopts Grid Method to describe, and there are eight working direction in robot, assuming that the distance walking direct bearing is
, then the distance walking oblique orientation is
, getting approximate value is 14, being then expressed as follows of cost function:
,
; In formula,
represent the consumption figures of father node to destination node S of node;
represent that node is to its father node consumption figures;
method of estimation have a lot, be that manhatton distance is estimated, Euclidean distance is estimated in the method that grating map is conventional, used herein is that manhatton distance is estimated, have ignored diagonal distance, is specifically expressed as follows:
, wherein:
with
the coordinate of representation node,
with
represent the coordinate of destination node G; " blind alley " flees from strategy: robot is when composition path planning, can with the data structure storage composition node path of storehouse, when robot enters " blind alley ", grid beyond composition node rolling window can be searched for one by one with the strategy of " first-in last-out ", find out the node that can flee from.
Above content is only preferred embodiment of the present invention, and for those of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, this description should not be construed as limitation of the present invention.
Claims (3)
1. a path planning for robot autonomous structure indoor map, is characterized in that, comprise the steps:
Step 1: initialization;
Step 2: adopt laser radar image data and SLAM to build map;
Step 3: adopt static ox to plough the next accurate composition node of mode decision;
Step 4: decision-making goes out next accurate composition node, then enter local dynamic station priority mode and determine next composition node;
Step 5: decision-making goes out next composition node, then utilize A* algorithmic rule to go out path to next composition node;
Step 6: according to the path cooked up, robot motion is to next composition point;
Step 7: use " blind alley " to flee from tactful searching in composition path and flee from node;
Step 8: after finding and fleeing from target, then utilize A* algorithmic rule to flee from path;
Step 9: composition completes, path planning terminates.
2. the path planning of a kind of robot autonomous structure indoor map according to claim 1, is characterized in that: the formula that described static ox ploughs pattern is
.
3. the path planning of a kind of robot autonomous structure indoor map according to claim 1, is characterized in that: the formula of described A* algorithm is
, wherein
refer to that start node S moves to the consumption figures of node;
refer to the consumption figures that joint movements is estimated to destination node G;
refer to the estimated value of the minimal cost path arriving destination node from starting point node through node.
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| CN106197421A (en) * | 2016-06-24 | 2016-12-07 | 北京工业大学 | A kind of forward position impact point for moving robot autonomous exploration generates method |
| CN106647769A (en) * | 2017-01-19 | 2017-05-10 | 厦门大学 | AGV path tracking and obstacle avoiding coordination method based on A* extraction guide point |
| CN107247463A (en) * | 2017-06-08 | 2017-10-13 | 广东容祺智能科技有限公司 | A kind of unmanned aerial vehicle station system for supporting self-defined map to access |
| CN108469814A (en) * | 2018-02-08 | 2018-08-31 | 广东雷洋智能科技股份有限公司 | Path cruise method applied to home-services robot |
| CN108663063A (en) * | 2018-05-09 | 2018-10-16 | 宁波拓邦智能控制有限公司 | Overlay path planing method, device, equipment, computer installation and storage medium |
| CN108709562A (en) * | 2018-04-28 | 2018-10-26 | 北京机械设备研究所 | A kind of mobile robot rolling grating map construction method |
| 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 |
| CN109085836A (en) * | 2018-08-29 | 2018-12-25 | 深圳市浦硕科技有限公司 | A kind of method that sweeping robot returns designated position minimal path |
| CN109947114A (en) * | 2019-04-12 | 2019-06-28 | 南京华捷艾米软件科技有限公司 | Robot complete coverage path planning method, device and equipment based on grating map |
| CN112486182A (en) * | 2020-12-08 | 2021-03-12 | 南通大学 | Sweeping robot for realizing construction of unknown environment map and path planning and use method thereof |
| CN113534820A (en) * | 2021-09-14 | 2021-10-22 | 深圳市元鼎智能创新有限公司 | Method and device for motion obstacle avoidance and route control of sweeping robot and sweeping robot |
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106197421B (en) * | 2016-06-24 | 2019-03-22 | 北京工业大学 | A kind of forward position target point generation method independently explored for mobile robot |
| CN106197421A (en) * | 2016-06-24 | 2016-12-07 | 北京工业大学 | A kind of forward position impact point for moving robot autonomous exploration generates method |
| CN106647769A (en) * | 2017-01-19 | 2017-05-10 | 厦门大学 | AGV path tracking and obstacle avoiding coordination method based on A* extraction guide point |
| CN106647769B (en) * | 2017-01-19 | 2019-05-24 | 厦门大学 | Based on A*Extract AGV path trace and the avoidance coordination approach of pilot point |
| CN107247463A (en) * | 2017-06-08 | 2017-10-13 | 广东容祺智能科技有限公司 | A kind of unmanned aerial vehicle station system for supporting self-defined map to access |
| CN108469814A (en) * | 2018-02-08 | 2018-08-31 | 广东雷洋智能科技股份有限公司 | Path cruise method applied to home-services robot |
| CN108709562B (en) * | 2018-04-28 | 2020-07-03 | 北京机械设备研究所 | Method for constructing rolling grid map of mobile robot |
| CN108709562A (en) * | 2018-04-28 | 2018-10-26 | 北京机械设备研究所 | A kind of mobile robot rolling grating map construction method |
| CN108663063A (en) * | 2018-05-09 | 2018-10-16 | 宁波拓邦智能控制有限公司 | Overlay path planing method, device, equipment, computer installation and storage medium |
| CN108663063B (en) * | 2018-05-09 | 2021-11-16 | 宁波拓邦智能控制有限公司 | Overlay path planning method, device, equipment, computer device and storage medium |
| 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 |
| CN108981710B (en) * | 2018-08-07 | 2019-10-11 | 北京邮电大学 | A kind of complete coverage path planning method of mobile robot |
| CN109085836A (en) * | 2018-08-29 | 2018-12-25 | 深圳市浦硕科技有限公司 | A kind of method that sweeping robot returns designated position minimal path |
| CN109947114A (en) * | 2019-04-12 | 2019-06-28 | 南京华捷艾米软件科技有限公司 | Robot complete coverage path planning method, device and equipment based on grating map |
| CN109947114B (en) * | 2019-04-12 | 2022-03-15 | 南京华捷艾米软件科技有限公司 | Robot full-coverage path planning method, device and equipment based on grid map |
| CN112486182A (en) * | 2020-12-08 | 2021-03-12 | 南通大学 | Sweeping robot for realizing construction of unknown environment map and path planning and use method thereof |
| CN112486182B (en) * | 2020-12-08 | 2022-12-02 | 南通大学 | Sweeping robot for realizing unknown environment map construction and path planning and use method thereof |
| CN113534820A (en) * | 2021-09-14 | 2021-10-22 | 深圳市元鼎智能创新有限公司 | Method and device for motion obstacle avoidance and route control of sweeping robot and sweeping robot |
| CN113534820B (en) * | 2021-09-14 | 2021-12-14 | 深圳市元鼎智能创新有限公司 | Method and device for motion obstacle avoidance and route control of sweeping robot and sweeping robot |
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