KR20220161919A - Driving characteristics modeling method of logistics robot for virtual simulation - Google Patents

Driving characteristics modeling method of logistics robot for virtual simulation Download PDF

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KR20220161919A
KR20220161919A KR1020210070246A KR20210070246A KR20220161919A KR 20220161919 A KR20220161919 A KR 20220161919A KR 1020210070246 A KR1020210070246 A KR 1020210070246A KR 20210070246 A KR20210070246 A KR 20210070246A KR 20220161919 A KR20220161919 A KR 20220161919A
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target
logistics
driving
transport robot
logistics transport
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KR102560143B1 (en
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나성권
유승우
이명복
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한성대학교 산학협력단
주식회사 지에스아이
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • 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
    • G05D1/0212—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
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/41885—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by modeling, simulation of the manufacturing system
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/4189—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the transport system
    • G05B19/41895—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the transport system using automatic guided vehicles [AGV]

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Abstract

The purpose is to provide a virtual driving modeling system to simulate the movement of a logistics transport robot in accordance with a given logistics transport scenario. The virtual driving modeling system for a logistics transport robot according to the present invention comprises: a traveling wheel control unit (100) that receives a rotation speed of wheels of the logistics transport robot to output the rotation angle of the wheels; a position estimation unit (200) that calculates the current position of the logistics transport robot from the rotation angle of the wheels; a target path generation unit (300) that generates a target speed path based on the time and distance from the current position to a target position of the logistics transport robot, and converts the same into the target position of the logistics transport robot on a two-dimensional plane; and a travel control unit (400) that calculates the target rotation speed at which the rotating wheels should rotate in accordance with the difference between the current position and the target position of the logistics transport robot.

Description

물류이송로봇의 가상 시뮬레이션을 위한 주행특성 가상모델링 방법{DRIVING CHARACTERISTICS MODELING METHOD OF　LOGISTICS ROBOT FOR VIRTUAL SIMULATION}Virtual modeling method of driving characteristics for virtual simulation of logistics transfer robots

본 발명은 물류이송로봇의 움직임을 가상으로 모델링하고, 주어진 물류이송 시나리오에 맞춰, 물류이송로봇의 이동을 시뮬레이션하기 위한 가상주행 모델링 시스템에 관한 것이다.The present invention relates to a virtual driving modeling system for virtually modeling the movement of a logistics transport robot and simulating the movement of a logistics transport robot according to a given logistics transport scenario.

제조공정용 물류이송로봇은 제품의 생산과 자동화를 위하여 원재료, 반제품, 부품, 상품 등의 이송, 이적재를 담당하는 자동화 기기이다. 특히 다품종 복합생산을 가능케 하며, 유연한 생산체계를 가지므로, 스마트 공장에 필수적으로 사용된다.Logistics transport robot for manufacturing process is an automation device that is in charge of transporting and loading raw materials, semi-finished products, parts, and products for production and automation of products. In particular, it enables multi-product complex production and has a flexible production system, so it is essential for smart factories.

물류이송로봇은, 무인자동차와 같이 지상을 주행하는 AGV(Automated Guied Vehicle), 기차와 같이 지상에 설치된 레일을 주행하는 RGV(Rail Guied Vehicle), 상공에 설치된 레일을 주행하는 OHV(Overhead Vehicle) 등 다양한 형태가 있다.Logistics transport robots include AGV (Automated Guided Vehicle) that runs on the ground like an unmanned car, RGV (Rail Guided Vehicle) that runs on rails installed on the ground like a train, and OHV (Overhead Vehicle) that runs on rails installed in the sky. There are various forms.

한편, 물류이송로봇을 제조현장에 설치할 경우에, 최적의 운행 방안을 찾기 위하여 많은 시간과 노력이 요구된다. 이러한 시간과 노력을 절감하기 위하여, 공정설비에서 물류로봇의 동작을 가상 시물레이션하여 추정해 볼 수 있다.On the other hand, when a logistics transfer robot is installed at a manufacturing site, a lot of time and effort are required to find an optimal operation method. In order to save such time and effort, it is possible to estimate the operation of a logistics robot in a process facility by virtual simulation.

통상적으로 물류이송로봇은 사다리꼴 속도궤적을 명령으로 인가하여 이를 추정하면서 주행하기는 하지만, 실제의 주행은 사다리꼴 속도궤적을 정확하게 그대로 추종하면서 이루어지지는 않는다. 이의 원인은, 노면의 상태에 따라 바퀴와 노면간의 미끄러짐의 정도가 달라진다는 점, 주행용 서보드라이버의 게인값 튜닝상태에 따라 모터제어기의 회전속도 추종정도가 달라진다는 점 등을 들 수 있다. 따라서, 실제의 물류이송 로봇은 동일한 거리를 여러 회 주행할 경우, 주행할 때마다 주행에 소요되는 시각이 달라지게 된다.In general, logistics transfer robots apply a trapezoidal speed trajectory as a command and run while estimating it, but actual driving does not follow the trapezoidal speed trajectory exactly as it is. This can be caused by the fact that the degree of slip between the wheels and the road surface varies depending on the condition of the road surface, and that the rotational speed tracking degree of the motor controller varies according to the tuning state of the gain value of the driving servo driver. Therefore, when an actual logistics transport robot travels the same distance several times, the time required for travel is different each time it travels.

등록특허공보 제10-1337868호, 반도체 제조용 클러스터 툴의 웨이퍼 이송로봇 테스트 시뮬레이션 시스템Registered Patent Publication No. 10-1337868, wafer transfer robot test simulation system of cluster tool for semiconductor manufacturing 공개특허공보 제10-2020-0137110호, 인라인 생산 시스템을 위한 인라인 시뮬레이션 시스템Publication No. 10-2020-0137110, inline simulation system for inline production system 등록특허공보 제10-1993476호, 물류 토큰과 공정 중심 모델링 방법을 이용한 조선소 블록 물류 시뮬레이션 모델링 방법Registered Patent Publication No. 10-1993476, Shipyard block logistics simulation modeling method using logistics token and process-oriented modeling method 등록특허공보 제10-1568644호, 이벤트 기반 생산-물류 통합 시뮬레이션 시스템 및 시뮬레이션 방법Registered Patent Publication No. 10-1568644, event-based production-logistics integrated simulation system and simulation method

본 발명은 물류이송로봇의 움직임을 가상으로 모델링하고, 주어진 물류이송 시나리오(상위 서버에서 내려오는 물류이송 명령들)에 맞춰, 물류이송로봇의 이동을 시뮬레이션하기 위한 가상주행 모델링 시스템을 제공하려는 데 그 목적이 있다.The present invention is intended to provide a virtual driving modeling system for virtually modeling the movement of the logistics transport robot and simulating the movement of the logistics transport robot according to a given logistics transport scenario (logistics transport commands coming down from the upper server). There is a purpose.

또한 본 발명은 실제 물류이송로봇의 주행시에 생기는 시간오차를 확률적으로 모델링하여 가상의 물류이송 로봇에 적용하고, 시뮬레이션을 통해 실제의 주행특성을 확인하기 위한 가상주행 모델링 시스템을 제공하려는 데 그 목적이 있다.In addition, the present invention is to provide a virtual driving modeling system for probabilistically modeling the time error that occurs during the driving of an actual logistics transport robot, applying it to a virtual logistics transport robot, and confirming actual driving characteristics through simulation. there is

본 발명의 해결하고자 하는 과제는 언급한 과제로 제한되지 않는다. 언급하지 않은 다른 기술적 과제들은 이하의 기재로부터 본 발명이 속하는 기술분야에서 통상의 지식을 가진 자에게 명확하게 이해될 수 있을 것이다.The problem to be solved by the present invention is not limited to the above-mentioned problem. Other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

본 발명에 따른 물류이송로봇의 가상주행 모델링 시스템은, 물류이송로봇의 바퀴의 회전속도를 입력받아, 바퀴의 회전각을 출력하는 주행바퀴 제어부(100)와, 상기 바퀴의 회전각으로부터 물류이송로봇의 현재위치를 계산하는 위치 추정부(200)와, 상기 물류이송로봇의 현재위치와 목표위치까지의 거리 및 시간의 경과에 따른 목표 속도궤적을 생성하고, 2차원 평면상에 위치한 물류이송로봇의 목표위치로 변환하는 목표궤적 생성부(300)와, 물류이송로봇의 현재위치와 목표위치의 차이를 0으로 하기 위해, 회전바퀴가 회전해야 하는 목표 회전속도를 계산하는 주행 제어부(400)을 포함한다.The virtual driving modeling system of the logistics transfer robot according to the present invention includes a driving wheel control unit 100 that receives the rotational speed of the wheels of the logistics transfer robot and outputs the rotational angle of the wheels, and the logistics transfer robot from the rotational angle of the wheels. A position estimator 200 that calculates the current position of the logistic transfer robot, the distance between the current position and the target position of the logistic transfer robot and a target speed trajectory according to the lapse of time, and the logistic transfer robot located on a two-dimensional plane. Includes a target trajectory generating unit 300 that converts to a target position and a driving control unit 400 that calculates a target rotational speed at which the rotating wheel should rotate in order to make the difference between the current position and the target position of the logistics transfer robot zero. do.

상기 주행 제어부(400)는, 가속구간, 등속구간, 감속구간, 서행구간이 연속적으로 주행하도록 제어될 수 있다.The driving control unit 400 may be controlled to continuously drive in an acceleration section, a constant speed section, a deceleration section, and a slow speed section.

상기 물류이송로봇의 현재 위치에 따른 주행바퀴의 목표속도는 아래 〈수학식 1〉에 따라 결정된다.The target speed of the driving wheels according to the current position of the logistics transfer robot is determined according to Equation 1 below.

〈수학식 1〉<Equation 1>

Figure pat00001
Figure pat00001

여기서,

Figure pat00002
과
Figure pat00003
은, 각각
Figure pat00004
과
Figure pat00005
시간에서의 주행바퀴의 현재위치를 의미하고,
Figure pat00006
은 k시간에서 바퀴의 목표속도이다.here,
Figure pat00002
class
Figure pat00003
silver, respectively
Figure pat00004
class
Figure pat00005
Means the current position of the driving wheel in time,
Figure pat00006
is the target speed of the wheel at time k.

상기 수학식 1에서, 가우시안 노이즈 함수

Figure pat00007
의 평균(
Figure pat00008
)과 표준편차(
Figure pat00009
)는, 물류이송로봇이 일정 목표거리를 가지는 경로를 반복해서 주행하여, 도착할 때까지 걸리는 주행 데이터를 기록한 후, 상기 주행 데이터로부터 물류이송로봇이 등속기간에서 소요한 시간을 측정한 다음, 목표속도와 시간을 곱하여 등속구간에서의 주행거리를 획득하여 주행거리의 평균과 표준편차를 계산된다.In Equation 1 above, the Gaussian noise function
Figure pat00007
mean of (
Figure pat00008
) and standard deviation (
Figure pat00009
), the logistics transport robot repeatedly travels a path with a certain target distance, records the travel data it takes to arrive, measures the time the logistics transport robot spends in a constant speed period from the travel data, and then targets the target speed The distance traveled in the constant speed section is obtained by multiplying by the time and the average and standard deviation of the distance traveled are calculated.

상기 현재위치와 목표위치의 차이는 아래 〈수학식 7〉에 따라 결정될 수 있다.The difference between the current position and the target position may be determined according to Equation 7 below.

〈수학식 7〉<Equation 7>

Figure pat00010
Figure pat00010

본 발명에 따르면, 실제 물류이송 로봇의 주행시에 생기는 시간오차를 확률적으로 모델링하여 가상의 물류이송 로봇에 적용함으로써, 가상의 시뮬레이션을 통해 실제의 물류이송을 최적화할 수 있다.According to the present invention, by probabilistically modeling a time error generated during driving of an actual logistics transport robot and applying it to a virtual logistics transport robot, actual logistics transport can be optimized through virtual simulation.

도 1은 본 발명의 일 실시예에 따른 물류이송 로봇의 가상주행 모델링 시스템을 나타낸 것이다.
도 2는 본 발명의 일 실시예에 따른 물류이송로봇의 가상주행을 나타낸 것이다.1 shows a virtual driving modeling system of a logistics transport robot according to an embodiment of the present invention.
2 shows virtual driving of a logistics transport robot according to an embodiment of the present invention.

이하, 본 발명의 실시예를 첨부된 도면을 참조하여 상세히 설명한다. Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

도 1은 본 발명의 일 실시예에 따른 물류이송로봇의 가상주행 모델링 시스템을 나타낸 것이다.1 shows a virtual driving modeling system of a logistics transfer robot according to an embodiment of the present invention.

본 발명의 일 실시예에 따른 물류이송로봇의 가상주행 모델링 시스템은, 주행바퀴 제어부(100), 위치 추정부(200), 목표궤적 생성부(300), 및 주행 제어부(400)를 포함한다.A virtual driving modeling system of a logistics transfer robot according to an embodiment of the present invention includes a driving wheel control unit 100, a position estimation unit 200, a target trajectory generator 300, and a driving control unit 400.

상기 바퀴 제어부(100)는 실제 물류이송로봇에서 바퀴를 구동하는 서보 드라이버의 제어로직을 간략화 또는 근사화하고, 주행 제어부(400)로부터 바퀴의 목표 회전속도(

Figure pat00011
, Desired Velocity)를 입력받아 주행 제어부(400)의 결과값인 바퀴의 회전각(
Figure pat00012
, Actual Position)을 출력한다. The wheel control unit 100 simplifies or approximates the control logic of the servo driver that drives the wheels in the actual logistics transport robot, and the target rotation speed of the wheel from the driving control unit 400 (
Figure pat00011
, Desired Velocity) and the rotation angle of the wheel, which is the result of the driving control unit 400 (
Figure pat00012
, Actual Position) is output.

상기 위치 추정부(200)는 바퀴 제어부(100)로부터 바퀴의 회전각(

Figure pat00013
)을 입력받아 물류이송로봇의 현재위치(
Figure pat00014
)를 계산한다. 물류이송로봇의 현재위치 데이터는 2차원 평면상의 위치인 x좌표(
Figure pat00015
), y좌표(
Figure pat00016
)와 회전각(
Figure pat00017
)으로 이루어진다. 상기 현재위치 데이터는 주행제어부 및 목표궤적 생성부로 출력된다.The position estimating unit 200 determines the rotation angle of the wheel from the wheel control unit 100 (
Figure pat00013
) and the current location of the logistics transport robot (
Figure pat00014
) is calculated. The current position data of the logistics transfer robot is the x-coordinate, which is a position on a two-dimensional plane (
Figure pat00015
), y coordinate (
Figure pat00016
) and rotation angle (
Figure pat00017
) is made up of The current location data is output to the driving control unit and the target trajectory generating unit.

상기 목표궤적 생성부(300)는 현재위치 데이터에 기초하여, 물류이송로봇의 현재위치와 목표위치까지의 거리 및 시간의 경과에 따른 목표 속도궤적을 생성하고 이를 2차원 평면상에 위치한 물류이송로봇의 목표위치(

Figure pat00018
)로 변환한다. The target trajectory generation unit 300 generates a target speed trajectory based on the current location data, the distance from the current location of the logistics transfer robot to the target location, and the lapse of time, and stores the trajectory of the logistics transport robot on a two-dimensional plane. target position of (
Figure pat00018
) is converted to

상기 주행 제어부(400)는 현재위치 및 목표위치 데이터에 기초하여, 물류이송로봇의 현재위치(

Figure pat00019
)와 목표위치(
Figure pat00020
)의 차이(
Figure pat00021
)를 계산하고, 그 차이를 0으로 만들기 위해 주행바퀴가 회전해야 하는 속도(
Figure pat00022
, 목표 회전속도)를 계산한다.The driving control unit 400 is based on the current position and target position data, the current position of the logistics transfer robot (
Figure pat00019
) and target position (
Figure pat00020
) of the difference (
Figure pat00021
) and the speed at which the driving wheel must rotate to make the difference zero (
Figure pat00022
, the target rotational speed) is calculated.

본 발명에 따른 소프트웨어에 의한 가상주행 모델링 시스템에서, 시간 0에서 시간

Figure pat00023
까지 진행된다고 하면, 소프트웨어에서 시간은 연속적으로 흐르지 않으므로, 사전에 설정된 단위시간(
Figure pat00024
)마다 주행 알고리즘 연산을 수행한다. 이때
Figure pat00025
의 관계가 성립한다. (이때,
Figure pat00026
은 양의 정수)In the virtual driving modeling system by software according to the present invention, from time 0 to time
Figure pat00023
If it goes up to , time does not flow continuously in the software, so it is a preset unit time (
Figure pat00024
), the driving algorithm operation is performed. At this time
Figure pat00025
relationship is established (At this time,
Figure pat00026
is a positive integer)

물류이송로봇의 현재 위치에 따른 주행바퀴의 목표속도는 아래와 같다.The target speed of the driving wheel according to the current position of the logistics transfer robot is as follows.

Figure pat00027
Figure pat00027

Figure pat00028
Figure pat00028

Figure pat00029
Figure pat00029

여기서,

Figure pat00030
과
Figure pat00031
은, 각각
Figure pat00032
과
Figure pat00033
시간에서의 주행바퀴의 현재위치를 의미하고,
Figure pat00034
은 k시간에서 바퀴의 목표속도를 의미한다. here,
Figure pat00030
class
Figure pat00031
silver, respectively
Figure pat00032
class
Figure pat00033
Means the current position of the driving wheel in time,
Figure pat00034
is the target speed of the wheel at time k.

만일, 물류이송로봇의 기구부가 좌우에 바퀴가 있는 차륜구동(Differential Drive) 방식인 경우에는 주행바퀴의 현재위치는 좌, 우 바퀴 각각의 회전각으로 표기할 수 있다.If the mechanical part of the logistics transfer robot is a differential drive method with wheels on the left and right, the current position of the driving wheel can be indicated by the rotation angle of each of the left and right wheels.

수학식 2에서, ρ는 주행바퀴의 회전각, ρl,k는 k 시간에서의 왼쪽 바퀴의 회전각, ρr,k는 k시간에서의 오른쪽 바퀴의 회전각을 의미한다. 예컨대, 최초 위치에서 ρ는 zero이고, 한바퀴 회전한 후에는 2pi 라디안(360도), 두 바퀴 회전한 후에는 4pi라디안(720도)이 된다.In Equation 2, ρ is the rotation angle of the driving wheel, ρ l,k is the rotation angle of the left wheel at time k, and ρ r,k is the rotation angle of the right wheel at time k. For example, at the initial position, ρ is zero, after one rotation it becomes 2pi radians (360 degrees), and after two rotations it becomes 4pi radians (720 degrees).

수학식 3에서,

Figure pat00035
는 실제의 서보 드라이버 로직을 간략화하는 대신에, 바퀴와 바닥간의 미끄러짐을 반영하고 실제와 이상적인 상황에서의 주행 차이를 보정하기 위하여 추가되는 가우시안 노이즈 함수(Gaussian Noise Function) 이다. 위 식에서 물류이송로봇이 주행할 때 걸리는 이상적인 소요시간이
Figure pat00036
라고 할 때,
Figure pat00037
은
Figure pat00038
를 단위시간
Figure pat00039
로 나눈 값이다. (
Figure pat00040
)In Equation 3,
Figure pat00035
Instead of simplifying the actual servo driver logic, is a Gaussian noise function added to reflect the slip between the wheel and the floor and compensate for the driving difference between real and ideal conditions. In the above equation, the ideal time required for the logistics transport robot to travel is
Figure pat00036
When you say
Figure pat00037
silver
Figure pat00038
unit time
Figure pat00039
is the value divided by (
Figure pat00040
)

상기 가우시안 노이즈 함수의 평균(

Figure pat00041
)과 표준편차(
Figure pat00042
)는 실제 물류이송로봇의 주행데이터를 통해 얻을 수 있다. 그 절차는 아래와 같다The average of the Gaussian noise function (
Figure pat00041
) and standard deviation (
Figure pat00042
) can be obtained through the driving data of the actual logistics transport robot. The procedure is as follows

① 물류이송로봇이 일정 목표거리(

Figure pat00043
)를 가지는 경로를 반복(
Figure pat00044
회)해서 주행하도록 하고, 도착할때까지 걸리는 주행데이터(시간별 물류이송로봇의 속도)를 기록한다.① The logistics transfer robot has a certain target distance (
Figure pat00043
) iterate over the path with (
Figure pat00044
times), and record the travel data (speed of the logistics transport robot by time) until it arrives.

② 주행데이터로부터, 물류이송로봇이 등속구간(목표속도

Figure pat00045
)에서 소요한 시간(
Figure pat00046
)을 측정한다.② From the driving data, the logistics transport robot is in the constant speed section (target speed
Figure pat00045
) time spent in (
Figure pat00046
) is measured.

③ 목표속도와 시간을 곱하여 등속구간에서의 주행거리(=

Figure pat00047
)를
Figure pat00048
회 기록하고, 여기에서 주행거리의 평균과 표준편차를 계산한다. 이 평균과 표준편차가 가우시안 노이즈 함수에 적용되는 평균(
Figure pat00049
)과 표준편차(
Figure pat00050
)를 의미한다.③ Multiply the target speed and time to travel distance in the constant speed section (=
Figure pat00047
)cast
Figure pat00048
Record the number of times, and calculate the average and standard deviation of the distance traveled. This average and standard deviation are applied to the Gaussian noise function,
Figure pat00049
) and standard deviation (
Figure pat00050
) means

이와 같은 절차를 거쳐서, 실제 물류이송로봇의 주행특성이 가상의 물류이송로봇의 주행특성에 반영된다.Through this procedure, the driving characteristics of the actual logistics transport robot are reflected in the driving characteristics of the virtual logistics transport robot.

이하, 현재위치 및 목표위치 데이터를 획득하는 것을 설명한다.Hereinafter, obtaining current location and target location data will be described.

물류이송로봇의 시각 k에서의 실제 위치 벡터를

Figure pat00051
, 시각
Figure pat00052
에서 물류이송로봇의 목표위치 벡터를
Figure pat00053
라 하면, 아래와 같다.The actual position vector at the time k of the logistics transfer robot
Figure pat00051
, Time
Figure pat00052
The target position vector of the logistics transfer robot in
Figure pat00053
If so, the following

Figure pat00054
Figure pat00054

Figure pat00055
Figure pat00055

여기서,

Figure pat00056
,
Figure pat00057
,
Figure pat00058
는 각각 시각
Figure pat00059
에서 물류이송로봇의 현재위치의 x좌표, y좌표, 회전각을 의미하고,
Figure pat00060
,
Figure pat00061
,
Figure pat00062
는 각각 시각
Figure pat00063
에서 물류이송로봇이 추종해야 하는 목표 위치의 x좌표, y좌표, 회전각을 의미한다.here,
Figure pat00056
,
Figure pat00057
,
Figure pat00058
are each time
Figure pat00059
means the x-coordinate, y-coordinate, and rotation angle of the current position of the logistics transfer robot in
Figure pat00060
,
Figure pat00061
,
Figure pat00062
are each time
Figure pat00063
It means the x-coordinate, y-coordinate, and rotation angle of the target position that the logistics transfer robot should follow in .

참고로, 수학식 4에서, 좌측식은 위치 추정부에 획득한 현재위치 데이터이고, 우측식은 목표궤적 생성부에서 획득한 목표위치 데이터이다.For reference, in Equation 4, the equation on the left is the current position data obtained by the position estimation unit, and the equation on the right is the target position data obtained by the target trajectory generator.

여기에,

Figure pat00064
에 오일러 적분을 적용하면 아래와 같이
Figure pat00065
로부터
Figure pat00066
을 구할 수 있다.Here,
Figure pat00064
Applying the Euler integral to
Figure pat00065
from
Figure pat00066
can be obtained.

수학식 5에서,

Figure pat00067
는 물류이송로봇의 선속도(Linear Velocity)이고,
Figure pat00068
는 물류이송로봇의 각속도(Angular Velocity)를 의미하며, 예를 들어 물류이송로봇의 기구부가 좌우에 바퀴가 있는 차륜구동(Differential Drive) 방식인 경우에는 아래 수학식 6과 같이 계산할 수 있다.In Equation 5,
Figure pat00067
is the linear velocity of the logistics transfer robot,
Figure pat00068
Means the angular velocity of the logistics transfer robot. For example, when the mechanical part of the logistics transfer robot is a differential drive type with wheels on the left and right, it can be calculated as shown in Equation 6 below.

Figure pat00069
Figure pat00069

수학식 6에서,

Figure pat00070
은 바퀴의 반지름,
Figure pat00071
는 바퀴사이의 거리를 의미한다.In Equation 6,
Figure pat00070
the radius of the silver wheel,
Figure pat00071
is the distance between the wheels.

이하, 본 발명에 따른 목표궤적 생성부(300) 및 주행 제어부(400)에 대하여 설명한다.Hereinafter, the target trajectory generation unit 300 and the driving control unit 400 according to the present invention will be described.

도 2는 본 발명의 일 실시예에 따른 물류이송로봇의 가상주행을 나타낸 것이다.2 shows virtual driving of a logistics transport robot according to an embodiment of the present invention.

물류이송로봇의 아래 그림과 같이, A지점에서 B지점으로 직선경로를 따라 주행하는 경우, 이 직선경로는 가속구간, 등속구간, 감속구간, 서행구간으로 구성되고, 이 4가지 구간은 사전에 설정된 가속도, 등속 속도, 감속도, 서행속도, 서행거리에 따라 정해진다.As shown in the figure below of the logistics transfer robot, when driving along a straight path from point A to point B, this straight path consists of an acceleration section, a constant speed section, a deceleration section, and a slow speed section, and these four sections are set in advance. It is determined by acceleration, constant velocity, deceleration, slow speed, and slow distance.

도 2에서, A B 지점의 2차원 평면상의 좌표는 사전이 알려져 있고, 시각을

Figure pat00072
라 할 때
Figure pat00073
에서 물류이송로봇은 A지점에 있다. In FIG. 2, the coordinates of the point AB on the two-dimensional plane are known in advance, and the time
Figure pat00072
when
Figure pat00073
In , the logistics transfer robot is at point A.

물류이송로봇의 현재위치

Figure pat00074
와 목표위치
Figure pat00075
값으로부터 아래와 같이 에러
Figure pat00076
를 계산할 수 있다.The current position of the logistics transfer robot
Figure pat00074
and target position
Figure pat00075
Error as below from value
Figure pat00076
can be calculated.

Figure pat00077
Figure pat00077

이때, 주행바퀴의 목표 회전속도

Figure pat00078
는 아래와 같이 에러
Figure pat00079
, 현재 위치
Figure pat00080
, 목표 위치
Figure pat00081
의 함수로 표현할 수 있다. 상기 수학식 7에서, 벡터e는 현재위치와 목표위치와의 차이를 말하는데, e1은 현재위치의 x좌표값과 목표위치의 x좌표값의 차이, e2는 현재위치의 y좌표값과 목표위치의 y좌표값의 차이, e3는 현재위치의 회전각과 목표위치의 회전값의 차이를 말한다.At this time, the target rotational speed of the driving wheel
Figure pat00078
error as below
Figure pat00079
, Current location
Figure pat00080
, target position
Figure pat00081
can be expressed as a function of In Equation 7, vector e refers to the difference between the current position and the target position, e 1 is the difference between the x-coordinate value of the current position and the x-coordinate value of the target position, e 2 is the y-coordinate value of the current position and the target The difference between the y-coordinate value of the position, e 3 means the difference between the rotation angle of the current position and the rotation value of the target position.

본 발명에 따른 목표 회전속도는 하기 〈수학식 8〉에 따라 계산된다.The target rotational speed according to the present invention is calculated according to Equation 8 below.

Figure pat00082
Figure pat00082

상기 목표 회전속도 함수는 물류이송로봇의 기구 특성에 따라 달라질 수도 있다. The target rotational speed function may vary according to mechanical characteristics of the logistics transfer robot.

이상, 본 발명을 구체적인 실시예를 통하여 상세하게 설명하였으나, 본 발명은 상기 실시예에 한정되지 않고, 본 발명의 기술적 사상의 범위내에서 통상의 지식을 가진 자에 의하여 여러 가지 변형이 가능하다.In the above, the present invention has been described in detail through specific embodiments, but the present invention is not limited to the above embodiments, and various modifications are possible by those skilled in the art within the scope of the technical idea of the present invention.

100 : 주행바퀴 제어부
200 : 위치 추정부
300 : 목표궤적 생성부
400 : 주행 제어부100: driving wheel control unit
200: position estimation unit
300: target trajectory generating unit
400: driving control unit

Claims (5)

물류이송로봇의 바퀴의 회전속도를 입력받아, 바퀴의 회전각을 출력하는 주행바퀴 제어부(100)와,
상기 바퀴의 회전각으로부터 물류이송로봇의 현재위치를 계산하는 위치 추정부(200)와,
상기 물류이송로봇의 현재위치와 목표위치까지의 거리 및 시간의 경과에 따른 목표 속도궤적을 생성하고, 2차원 평면상에 위치한 물류이송로봇의 목표위치로 변환하는 목표궤적 생성부(300)와,
물류이송로봇의 현재위치와 목표위치의 차이를 0으로 하기 위해, 회전바퀴가 회전해야 하는 목표 회전속도를 계산하는 주행 제어부(400)을 포함하는 것을 특징으로 하는 물류이송로봇의 가상주행 모델링 시스템.
A driving wheel control unit 100 that receives the rotational speed of the wheel of the logistics transfer robot and outputs the rotational angle of the wheel;
A position estimation unit 200 for calculating the current position of the logistics transfer robot from the rotation angle of the wheel;
A target trajectory generating unit 300 for generating a target speed trajectory according to the lapse of time and the distance between the current position and the target position of the logistics transfer robot and converting it into a target position of the logistics transfer robot located on a two-dimensional plane;
A virtual driving modeling system for a logistics transfer robot comprising a travel control unit 400 for calculating a target rotational speed at which the rotating wheel should rotate in order to set the difference between the current position and the target position of the logistics transfer robot to zero.
 상기 주행 제어부(400)는,
가속구간, 등속구간, 감속구간, 서행구간이 연속적으로 주행하도록 제어되는 것을 특징으로 하는 물류이송로봇의 가상주행 모델링 시스템.
The driving control unit 400,
A virtual driving modeling system for a logistics transport robot, characterized in that the acceleration section, constant speed section, deceleration section, and slow speed section are controlled to continuously drive.
 청구항 1에 있어서,
상기 물류이송로봇의 현재 위치에 따른 주행바퀴의 목표속도는 하기 〈수학식 1〉에 따라 결정되는 것을 특징으로 하는 물류이송로봇의 가상주행 모델링 시스템.
〈수학식 1〉
Figure pat00083

여기서,
Figure pat00084
과
Figure pat00085
은, 각각
Figure pat00086
과
Figure pat00087
시간에서의 주행바퀴의 현재위치를 의미하고,
Figure pat00088
은 k시간에서 바퀴의 목표속도이다.
The method of claim 1,
The virtual driving modeling system of the logistics transport robot, characterized in that the target speed of the driving wheel according to the current position of the logistics transport robot is determined according to Equation 1 below.
<Equation 1>
Figure pat00083

here,
Figure pat00084
class
Figure pat00085
silver, respectively
Figure pat00086
class
Figure pat00087
Means the current position of the driving wheel in time,
Figure pat00088
is the target speed of the wheel at time k.
 청구항 3에 있어서,
가우시안 노이즈 함수
Figure pat00089
의 평균(
Figure pat00090
)과 표준편차(
Figure pat00091
)는,
물류이송로봇이 일정 목표거리를 가지는 경로를 반복해서 주행하여, 도착할 때까지 걸리는 주행 데이터를 기록한 후,
상기 주행 데이터로부터 물류이송로봇이 등속기간에서 소요한 시간을 측정한 다음,
목표속도와 시간을 곱하여 등속구간에서의 주행거리를 획득하여 주행거리의 평균과 표준편차를 계산하는 것을 특징으로 하는 물류이송로봇의 가상주행 모델링 시스템.
The method of claim 3,
Gaussian noise function
Figure pat00089
mean of (
Figure pat00090
) and standard deviation (
Figure pat00091
)Is,
After the logistics transfer robot repeatedly travels a path with a certain target distance and records the driving data it takes to arrive,
After measuring the time spent by the logistics transport robot in the constant speed period from the driving data,
A virtual driving modeling system for a logistics transport robot, characterized in that by multiplying the target speed and time to obtain the driving distance in the constant speed section and calculating the average and standard deviation of the driving distance.
 청구항 1에 있어서,
상기 현재위치와 목표위치의 차이는 아래 〈수학식 7〉에 따라 결정되는 것을 특징으로 하는 물류이송로봇의 가상주행 모델링 시스템.
〈수학식 7〉
Figure pat00092
The method of claim 1,
The virtual driving modeling system of the logistics transport robot, characterized in that the difference between the current position and the target position is determined according to Equation 7 below.
<Equation 7>
Figure pat00092
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