CN106272411A - Multirobot based on gravitation source collaborative carrying hatch cargo method - Google Patents

Multirobot based on gravitation source collaborative carrying hatch cargo method Download PDF

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Publication number
CN106272411A
CN106272411A CN201610719450.5A CN201610719450A CN106272411A CN 106272411 A CN106272411 A CN 106272411A CN 201610719450 A CN201610719450 A CN 201610719450A CN 106272411 A CN106272411 A CN 106272411A
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China
Prior art keywords
goods
robot
gravitation
gravitation source
source
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CN201610719450.5A
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CN106272411B (en
Inventor
陈自强
王炀
葛云龙
庞超飞
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Shanghai Jiaotong University
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Shanghai Jiaotong University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1679—Programme controls characterised by the tasks executed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
    • B25J9/1666—Avoiding collision or forbidden zones

Abstract

A kind of multirobot based on gravitation source collaborative carrying hatch cargo method, by setting up the two-dimensional map of cabin, arranges robot respectively since initial specified point sets out, moves along path planning and detect goods；When after arbitrary robot probe to goods with goods for gravitation source, all robots are set and move towards cargo location；When robot completes to load after goods, robot is set using middle section as gravitation source, and moves to it, and return specified point after middle section completes to unload goods reaching；Re-start detection goods process until the carrying of all goods terminates, the present invention uses sonac to detect environmental information, with low cost, specific geometric properties map is built for cabin environment, need not the algorithm real-time matching of complexity, the method working in coordination with collision prevention carrying by four robots, work efficiency is higher.

Description

Multirobot based on gravitation source collaborative carrying hatch cargo method
Technical field
The present invention relates to the technology of a kind of robot control field, a kind of multirobot based on gravitation source Collaborative carrying hatch cargo method.
Background technology
At present, in cabin, handling and the carrying work of goods are typically all and are completed by artificial fork truck.Work in cabin Bad environments, carrying work is uninteresting, heavy and from multiple, causes handling efficiency relatively low.Utilize robot to the goods carrying in cabin Thing, then be beneficial to improve work efficiency, but it carry track complex effects efficiency.
Summary of the invention
The present invention is directed to prior art many employings laser range finder position with speedometer, equipment cost is higher；It is led There is substantial amounts of filtering and data matching in boat algorithm, amount of calculation is bigger；Frequently use grating map constructing environment and then cause essence Spend the defects such as relatively low, propose a kind of multirobot based on gravitation source collaborative carrying hatch cargo method.
The present invention is achieved by the following technical solutions:
The present invention, by setting up the two-dimensional map of cabin, arranges robot respectively since initial specified point sets out, along planning Path is moved and detects goods；When after arbitrary robot probe to goods with goods for gravitation source, arrange all robots towards Cargo location moves；When robot completes to load after goods, robot is set using middle section as gravitation source, and moves to it Dynamic, and reaching return specified point after middle section completes to unload goods；Re-start detection goods process until all goods Carrying terminates.
Described two-dimensional map is the two dimension that whole cabin plane is divided into four pieces of regions using middle section as center Plane map.
Described specified point is farthest, distance middle section center in every piece of region.
Described path planning is the reciprocating motion paths cooked up according to Niu Gengfa and Artificial Potential Field Method.
Described machine artificial four AGV (Automated Guided Vehicle) dolly, lays respectively at two-dimensional map Four pieces of regions in.
Described robot is furnished with sonac.
Described robot forms a ultrasonic ring for detection centered by self, and ultrasonic ring is for artificially to justify with machine The heart be divided into 16 fan-shaped circles.
Other goods, towards in middle section moving process, is evaded by described robot as repulsion source.
Technique effect
Compared with prior art, the present invention uses sonac to detect environmental information, with low cost, for cabin environment Build specific geometric properties map, it is not necessary to complicated algorithm real-time matching, work in coordination with collision prevention carrying by four robots Method, work efficiency is higher.
Accompanying drawing explanation
Fig. 1 is flow chart of the present invention；
Fig. 2 is the two-dimensional map of cabin；
Fig. 3 is path planning schematic diagram；
Fig. 4 is ultrasonic ring schematic diagram；
Fig. 5 is goods handling process schematic diagram.
Detailed description of the invention
Elaborating embodiments of the invention below, the present embodiment is carried out under premised on technical solution of the present invention Implement, give detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following enforcement Example.
Embodiment 1
As it is shown in figure 1, the present embodiment is realized by following steps:
1) as in figure 2 it is shown, set up cabin two-dimensional map, the specified point of four robot initials is set.
Described is according to cabin environment geometric properties, and environment is divided into middle section and surrounding region to be covered, and will Region to be covered is divided into the two dimensional surface map in four pieces of regions.Two dimensional surface map size is 40 × 40 unit ares.Machine People's per unit move distance is a unit length, and goods to be handled is 1 × 1 unit are.Artificial four of described machine AGV (Automated Guided Vehicle) dolly, lays respectively in four pieces of regions of two-dimensional map.Each robot is two Radius length in dimension map is 0.5 unit length.Four pieces of regions in two-dimensional map are similar with rectangular coordinate plane, respectively For first quartile, the second quadrant, third quadrant and fourth quadrant.
Described specified point is farthest, distance middle section center in every piece of region.
As it is shown on figure 3, described path planning is the one combining Niu Gengfa and Artificial Potential Field Method proposition is suitable for cabin The path planning algorithm of carrying, i.e. uses reciprocal Motion to realize all standing, uses the side by the analog physical field of force Formula realizes detection goods and the collision prevention of robot.
As shown in Figure 4, described AGV dolly is furnished with sonac.AGV dolly forms one centered by self and is used for The ultrasonic ring of detection, ultrasonic ring is to be divided into 16 fan-shaped circles with the artificial center of circle of machine, and its radius is sonac Effective scope of detection.AGV dolly leads to sonac to detect surrounding objects, when goods being detected, triggers multiple sensing Device, the information beamed back according to these sensors determines the position of goods, and makes the decision-making of next step motion of robot.
2) as it is shown in figure 5, AGV dolly is from specified point, move along path planning, detect goods.
3) detecting after goods with goods for gravitation source, AGV dolly moves towards gravitation source.
Described robot is first according to preset path planning and moves, and now robot is unloaded, if at ultrasonic ring internal memory At goods to be handled, being then regarded as simulating the gravitation source in the field of force, the size random device people of gravitation subtracts with the spacing of impact point Little and reduce.Definition gravitation potential fieldIn formula: k is the gravitational field constant more than zero, XgFor impact point position Put.The negative gradient of gravitation potential field is the size of gravitation, Fa(X)=-grad (Ua(X))=k (Xg-X)。
4) AGV dolly loads goods, and moves towards the middle section as gravitation source.
Other goods, towards in middle section moving process, is evaded by described AGV dolly as repulsion source.Ultrasonic There is goods to be carried or other barriers in ring, be then regarded as simulating the repulsion source in the field of force, the size random device people of repulsive force Reduce with the spacing of barrier or goods to be carried and increase.Repulsion potential fieldWherein: m is big In the repulsion field constant of zero, XoFor Obstacle Position, ρ is the investigative range of robot.Repulsion is the negative gradient of repulsion potential field
F r ( X ) = - g r a d ( U r ( X ) ) = m ( 1 X - X o - 1 ρ ) 1 ( X - X o ) 2 ∂ ( X - X o ) ∂ X 0 .
Robot motion direction is exactly the resultant direction of repulsive force and gravitation, i.e. F (X)=Fa(X)+Fr(X) direction.
5) AGV dolly returns specified point after middle section unloading goods.
6) if goods all loads complete, terminate, otherwise return to step 1).
Compared with prior art, the present invention utilizes multirobot to work in coordination with carrying and decreases manpower, it is achieved that carry efficiently Goods, and system is made without numerous and diverse data and processes, thus improve the handling efficiency of goods in cabin, decrease into This.Transport goods compared to current cabin and use more artificial carrying fork truck method, under completing equal carrying work, become This is original less than 1/3rd.

Claims (8)

1. multirobot based on a gravitation source collaborative carrying hatch cargo method, it is characterised in that by setting up cabin Two-dimensional map, arranges robot respectively since initial specified point sets out, moves along path planning and detect goods；When arbitrary machine People detects after goods with goods for gravitation source, arranges all robots and moves towards cargo location；When robot completes to load After goods, robot is set using middle section as gravitation source, and moves to it, and complete to unload goods reaching middle section Rear return specified point；Re-start detection goods process until the carrying of all goods terminates.
Multirobot based on gravitation source the most according to claim 1 collaborative carrying hatch cargo method, is characterized in that, institute The two-dimensional map stated is the two dimensional surface map that whole cabin plane is divided into four pieces of regions using middle section as center.
Multirobot based on gravitation source the most according to claim 2 collaborative carrying hatch cargo method, is characterized in that, institute The specified point stated is farthest, distance middle section center in every piece of region.
Multirobot based on gravitation source the most according to claim 1 collaborative carrying hatch cargo method, is characterized in that, institute The path planning stated is the reciprocating motion paths cooked up according to Niu Gengfa and Artificial Potential Field Method.
Multirobot based on gravitation source the most according to claim 1 collaborative carrying hatch cargo method, is characterized in that, institute Artificial four the AGV dollies of machine stated, lay respectively in four pieces of regions of two-dimensional map.
Multirobot based on gravitation source the most according to claim 5 collaborative carrying hatch cargo method, is characterized in that, institute The robot stated is furnished with sonac.
Multirobot based on gravitation source the most according to claim 6 collaborative carrying hatch cargo method, is characterized in that, institute The robot stated forms a ultrasonic ring for detection centered by self, and ultrasonic ring is halved with the artificial center of circle of machine It is 16 fan-shaped circles.
Multirobot based on gravitation source the most according to claim 1 collaborative carrying hatch cargo method, is characterized in that, institute Other goods, towards in middle section moving process, is evaded by the robot stated as repulsion source.
CN201610719450.5A 2016-08-24 2016-08-24 Multirobot based on gravitation source cooperates with carry vessel hold cargo object space method Active CN106272411B (en)

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Cited By (9)

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CN106737696A (en) * 2017-03-11 2017-05-31 杭州极木科技有限公司 A kind of multirobot cooperates with transportation resources
CN107169611A (en) * 2017-06-09 2017-09-15 金陵科技学院 A kind of patterned way planning AGV travel regions and the method for monitoring its operation
CN108693879A (en) * 2018-04-28 2018-10-23 上海理工大学 Method for planning path for mobile robot based on modified embedded-atom method
WO2019061616A1 (en) * 2017-09-29 2019-04-04 Huawei Technologies Co., Ltd. Impedance-based motion control for autonomous vehicles
CN110162103A (en) * 2019-06-13 2019-08-23 河南宙合网络科技有限公司 A kind of unmanned plane independently cooperates with transportation system and method with intelligent vehicle group
CN110471427A (en) * 2019-09-06 2019-11-19 大连海事大学 A kind of ship formation intelligent Collision Avoidance method based on path planning and Artificial Potential Field Method
CN110796208A (en) * 2018-08-02 2020-02-14 菜鸟智能物流控股有限公司 Detection method, device and system
CN113342004A (en) * 2021-07-29 2021-09-03 山东华力机电有限公司 Multi-AGV (automatic guided vehicle) scheduling method and system based on artificial intelligence and visual perception
WO2022032442A1 (en) * 2020-08-10 2022-02-17 深圳技术大学 Method and system for cooperatively transporting object by multiple intelligent agents, and computer readable storage medium

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CN104390648A (en) * 2014-12-22 2015-03-04 中国矿业大学 Coal mine rescue robot path planning method based on artificial potential field
CN105182973A (en) * 2015-09-08 2015-12-23 郑州大学 Self-adaptive hunting device using multiple robot pursuers to hunt single moving target and method
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CN104317291A (en) * 2014-09-16 2015-01-28 哈尔滨恒誉名翔科技有限公司 Artificial-potential-field-based robot collision preventation path planning method
WO2016045615A1 (en) * 2014-09-25 2016-03-31 科沃斯机器人有限公司 Robot static path planning method
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Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106737696A (en) * 2017-03-11 2017-05-31 杭州极木科技有限公司 A kind of multirobot cooperates with transportation resources
CN107169611A (en) * 2017-06-09 2017-09-15 金陵科技学院 A kind of patterned way planning AGV travel regions and the method for monitoring its operation
WO2019061616A1 (en) * 2017-09-29 2019-04-04 Huawei Technologies Co., Ltd. Impedance-based motion control for autonomous vehicles
US10928832B2 (en) 2017-09-29 2021-02-23 Huawei Technologies Co., Ltd. Impedance-based motion control for autonomous vehicles
CN108693879A (en) * 2018-04-28 2018-10-23 上海理工大学 Method for planning path for mobile robot based on modified embedded-atom method
CN108693879B (en) * 2018-04-28 2021-07-13 上海理工大学 Mobile robot path planning method based on improved artificial potential field method
CN110796208A (en) * 2018-08-02 2020-02-14 菜鸟智能物流控股有限公司 Detection method, device and system
CN110796208B (en) * 2018-08-02 2023-05-05 菜鸟智能物流控股有限公司 Detection method, device and system
CN110162103A (en) * 2019-06-13 2019-08-23 河南宙合网络科技有限公司 A kind of unmanned plane independently cooperates with transportation system and method with intelligent vehicle group
CN110471427A (en) * 2019-09-06 2019-11-19 大连海事大学 A kind of ship formation intelligent Collision Avoidance method based on path planning and Artificial Potential Field Method
WO2022032442A1 (en) * 2020-08-10 2022-02-17 深圳技术大学 Method and system for cooperatively transporting object by multiple intelligent agents, and computer readable storage medium
CN113342004A (en) * 2021-07-29 2021-09-03 山东华力机电有限公司 Multi-AGV (automatic guided vehicle) scheduling method and system based on artificial intelligence and visual perception
CN113342004B (en) * 2021-07-29 2021-10-29 山东华力机电有限公司 Multi-AGV (automatic guided vehicle) scheduling method and system based on artificial intelligence and visual perception

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