TWM606382U - Robotic manipulator system for real-time correction of clamping coordinate - Google Patents

Robotic manipulator system for real-time correction of clamping coordinate Download PDF

Info

Publication number
TWM606382U
TWM606382U TW109209918U TW109209918U TWM606382U TW M606382 U TWM606382 U TW M606382U TW 109209918 U TW109209918 U TW 109209918U TW 109209918 U TW109209918 U TW 109209918U TW M606382 U TWM606382 U TW M606382U
Authority
TW
Taiwan
Prior art keywords
coordinates
clamping
depth
gripper
calculation unit
Prior art date
Application number
TW109209918U
Other languages
Chinese (zh)
Inventor
楊詠傑
謝宜芳
胡念祖
楊景翔
葉晴尹
施政瀚
莊介慈
劉上瑋
許凱勛
何素華
Original Assignee
創璟應用整合有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 創璟應用整合有限公司 filed Critical 創璟應用整合有限公司
Priority to TW109209918U priority Critical patent/TWM606382U/en
Publication of TWM606382U publication Critical patent/TWM606382U/en

Links

Images

Landscapes

  • Manipulator (AREA)

Abstract

一種即時校正夾持座標之機械手臂系統,包括:一輸送平台、一機械手臂及一景深相機,該景深相機於起始座標處對物件拍攝影像畫面,透過該演算單元分析影像畫面得知物件位置、中心座標與尺寸比例,再依據物件該中心座標演算得知夾持座標,以及該起始座標至夾持座標之間的位移路徑,該演算單元於位移路徑上產生有校正座標,當該夾爪位移至該校正座標時,再次對物件拍攝影像畫面,分析與判斷夾持座標是否一致,藉此讓該夾爪精準定位的移動至夾持座標,即能利用該景深相機於該夾爪處的無遮蔽影像畫面與景深測距功能,即時對該夾爪進行微調校正。 A mechanical arm system for real-time correction of clamping coordinates, comprising: a conveying platform, a mechanical arm, and a depth-of-field camera. The depth-of-field camera shoots an image frame of an object at the initial coordinate, and the position of the object is obtained by analyzing the image frame by the calculation unit , The center coordinates and the size ratio, and then calculate the clamping coordinates according to the center coordinates of the object, and the displacement path from the starting coordinates to the clamping coordinates. The calculation unit generates correction coordinates on the displacement path. When the claw is displaced to the calibration coordinates, take another image of the object to analyze and determine whether the clamping coordinates are consistent, so that the clamping claw can be accurately positioned to move to the clamping coordinates, that is, the depth of field camera can be used at the clamping claw The unobstructed image screen and the depth-of-field ranging function can make fine adjustments and corrections to the gripper in real time.

Description

即時校正夾持座標之機械手臂系統 Robotic arm system for real-time correction of clamping coordinates

本創作係有關於一種機械手臂控制系統,尤指一種應用景深相機而達到精準控制夾物位置之即時校正夾持座標之機械手臂系統。 This creation is related to a robotic arm control system, especially a robotic arm system that uses a depth-of-field camera to accurately control the position of the object and correct the clamping coordinates in real time.

按,習知工廠為了降低製造成本,通常都會朝向自動化製造方向發展,而自動化的製造方式主要是透過機械手臂來實現,現有的機械手臂在運作時,通常會依據實際的製程選擇適當的夾爪等取物機構,且該機械手臂只能對單一種類的物件執行重覆的動作,而為了降低夾持失誤率,該物件的位置與角度必須嚴格的受到限制,當物件大小非一致或未摸列整齊時,一般運行固定夾持程序之機械手臂即不適用,故習知另提供一種結合影像分析之機械手臂,其係藉由於機械手臂作業區域內設置有固定式攝影裝置,以藉由攝影裝置拍攝物件影像,透過影像特徵控制機械手臂產生對應的調整,但詳觀上述習知結構不難發覺其尚存有些許不足之處,主要原因係歸如下:該攝影裝置為固定位置狀態,無法透過不同遠近或角度去多次驗證物件的影像特徵,當所拍攝 的影像誤差導致無法正確夾持物件時,機械手臂必須退回原位,使機械手臂不會阻擋該攝影裝置對物件的拍攝,該無法即時校正的作業流程存在有耗時與夾持精準度低之缺點,又在部分難以夾持之事件中,該單一影像判斷物件方式在夾持失敗後,不論後續重新夾持幾次,其結果將仍是無法成功夾持物件,綜上所述皆為本創作所欲改善之技術問題點。 By the way, in order to reduce manufacturing costs, conventional factories usually develop in the direction of automated manufacturing, and automated manufacturing methods are mainly realized through robotic arms. When existing robotic arms are operating, they usually choose appropriate grippers based on the actual manufacturing process. Wait for the retrieval mechanism, and the robotic arm can only perform repeated actions on a single type of object. In order to reduce the clamping error rate, the position and angle of the object must be strictly restricted. When the size of the object is not consistent or not touched When the rows are neatly arranged, the general mechanical arm that runs the fixed clamping program is not suitable. Therefore, the conventional art provides a mechanical arm combined with image analysis. This is because a fixed photographing device is installed in the working area of the mechanical arm. The device shoots an image of an object, and uses the image feature to control the robotic arm to produce corresponding adjustments. However, it is not difficult to find that there are still some shortcomings in the above-mentioned conventional structure. The main reasons are as follows: the camera is in a fixed position and cannot Through different distances or angles to verify the image characteristics of the object multiple times, when the shot When the object cannot be clamped correctly due to the image error, the robotic arm must be returned to the original position so that the robotic arm will not block the photographing device from shooting the object. The operation process that cannot be corrected in real time has time-consuming and low clamping accuracy. Disadvantages. In some cases that are difficult to clamp, the single-image method of judging an object after clamping fails, no matter how many subsequent re-clamping, the result will still be unable to successfully clamp the object. In summary The technical problems that the creation wants to improve.

有鑑於此,本創作人於多年從事相關產品之製造開發與設計經驗,針對上述之目標,詳加設計與審慎評估後,終得一確具實用性之本創作。 In view of this, the creator has been engaged in the manufacturing, development and design of related products for many years, and after detailed design and careful evaluation of the above goals, he finally got a practical creation.

本創作所欲解決之技術問題在於針對現有技術存在的上述缺失,提供一種即時校正夾持座標之機械手臂系統。 The technical problem to be solved by this creation is to provide a mechanical arm system for real-time correction of the clamping coordinates in response to the above-mentioned deficiencies in the prior art.

一輸送平台用於連續輸送物件至指定位置,一機械手臂設置於該輸送平台一側,且該機械手臂末端設置有可三維座標移動的一夾爪,又該機械手臂內建有即時判斷該夾爪座標之一控制單元,且該夾爪於該輸送平台上方的固定位置定義為起始座標,一景深相機固定於該機械手臂之該夾爪上,且該景深相機之鏡頭正面對準於該夾爪朝向,又該景深相機與該控制單元連線有一演算單元,該景深相機於起始座標處對物件拍攝影像畫面,透過該演算單元分析影像畫面得知物件位置,且基於起始座標與景深距離就能運算得知物件 的一中心座標與尺寸比例。 A conveying platform is used to continuously convey objects to a specified position. A mechanical arm is arranged on one side of the conveying platform, and the end of the mechanical arm is provided with a gripper that can move in three-dimensional coordinates, and the mechanical arm is built in for real-time judgment. A control unit of the jaw coordinates, and the fixed position of the jaw above the conveying platform is defined as the starting coordinate. A depth camera is fixed on the jaw of the robotic arm, and the front of the lens of the depth camera is aligned with the The gripper is oriented, and there is a calculation unit connected to the depth camera and the control unit. The depth camera shoots an image frame of the object at the start coordinate, and the position of the object is obtained by analyzing the image frame through the calculation unit, and is based on the start coordinate and Depth of field distance can calculate the object A center coordinate and size ratio of.

其中該景深相機包括有一主鏡頭與一副鏡頭,該副鏡頭用於感測距離,使該主鏡頭所拍攝影像畫面具有景深效果。 The depth-of-field camera includes a main lens and a pair of lenses, and the auxiliary lens is used for sensing distance, so that the image captured by the main lens has a depth effect.

其中該演算單元連接有一雲端伺服器,該雲端伺服器儲存有提供辨視物件使用之影像畫面及對應物件之相關資料,讓該演算單元深度學習該雲端伺服器之影像畫面,藉此提高對物件的判斷精準度。 The calculation unit is connected to a cloud server, and the cloud server stores the image screen used to identify the object and related data of the corresponding object, so that the calculation unit can deeply learn the image screen of the cloud server, thereby improving the objectivity. The accuracy of judgment.

其中該景深相機於執行拍攝指令時,該演算單元能記錄全部物件之影像畫面,並於該雲端伺服器建立影像專案資料夾,使該景深相機後續所拍攝的影像畫面能直接比對影像專案資料夾內之影像畫面,藉此提高該演算單元之運算速度與判斷精準度。 When the depth-of-field camera executes the shooting command, the arithmetic unit can record the image frames of all objects, and create an image project folder on the cloud server, so that the subsequent images taken by the depth-of-field camera can directly compare the image project data The image frames in the folder can improve the calculation speed and judgment accuracy of the calculation unit.

其中該夾爪沿著位移路徑執行位移動作時,該演算單元能記錄全部位移路徑與是否到達指定的校正座標或夾持座標,並於該雲端伺服器建立路徑專案資料夾,透過數據分析判斷相同或相近之位移路徑皆無法讓夾爪到達指定位置時,該演算單元後續將排除不良的位移路徑,透過繞路方式提高定位精準度。 When the gripper performs a displacement action along the displacement path, the calculation unit can record all the displacement paths and whether they reach the specified calibration coordinates or clamping coordinates, and create a path project folder on the cloud server, and judge the same through data analysis When neither of the similar displacement paths allows the gripper to reach the specified position, the calculation unit will subsequently eliminate the bad displacement path and improve the positioning accuracy by detouring.

其中該演算單元利用已知的該起始座標與影像畫面之景深進行運算,使影像畫面能繪制圍設該物件的一平面邊界框,且該平面邊界框於一端角落定義為一邊界座標, 又該演算單元以該平面邊界框運算得知物件之中心座標與尺寸比例。 The calculation unit uses the known starting coordinates and the depth of field of the image frame to perform calculations so that the image frame can draw a plane bounding box surrounding the object, and the plane bounding box is defined as a boundary coordinate at one end corner, In addition, the calculation unit uses the plane bounding box to calculate the center coordinates and the size ratio of the object.

其中該平面邊界框的長寬比設定為(w,h),該邊界座標設定為(Xi,Yi),該演算單元以該平面邊界框運算得知該中心座標為((Xi-w/2),(Yi-h/2)),又該起始座標設定為(X0,Y0),且該物件尺寸比例設定為Z,即能獲得對應物件之X點移動向量為-((Xi-w/2)-X0)/Z,以及對應物件之Y點移動向量為-((Yi-h/2)-Y0)/Z。 The aspect ratio of the plane bounding box is set to (w, h), the boundary coordinates are set to (Xi, Yi), and the calculation unit uses the plane bounding box to calculate that the center coordinates are ((Xi-w/2 ),(Yi-h/2)), and the starting coordinates are set to (X 0 ,Y 0 ), and the size ratio of the object is set to Z, the X point movement vector of the corresponding object can be obtained as -((Xi -w/2)-X 0 )/Z, and the Y point movement vector of the corresponding object is -((Yi-h/2)-Y 0 )/Z.

其中該夾爪位移至夾持座標,使該夾爪旋轉角度對準物件之中心座標,該夾爪夾持物件不足或超過指定寬度之容許值時,該演算單元判斷夾持失敗,由該控制單元將該夾爪位移至上一步驟之校正座標,再次由該景深相機進行拍攝,且由該演算單元重新計算新的夾持座標,重新進行夾持動作。 The clamping jaws are displaced to the clamping coordinates so that the rotation angle of the clamping jaws is aligned with the center coordinates of the object. When the clamping jaws are insufficient or exceed the allowable value of the specified width, the calculation unit determines that the clamping has failed, and the control is The unit displaces the clamping jaws to the correction coordinates of the previous step, and takes the shot again with the depth-of-field camera, and the calculation unit recalculates the new clamping coordinates and performs the clamping operation again.

其中該機械手臂於該夾爪處裝設有一荷重單元,於操作該夾爪進行夾持動作後,該荷重單元未偵測到該夾爪保持有重量的增加,該演算單元即能判斷夾持失敗,由該控制單元將該夾爪位移至上一步驟之校正座標,再次由該景深相機進行拍攝,且由該演算單元重新計算新的夾持座標,重新進行夾持動作。 The mechanical arm is equipped with a load unit at the clamping jaw. After the clamping jaw is operated to perform a clamping action, the load unit does not detect that the clamping jaw maintains an increase in weight, and the calculation unit can judge the clamping If it fails, the control unit displaces the clamping jaw to the calibration coordinates of the previous step, and then takes the shot again by the depth camera, and the calculation unit recalculates the new clamping coordinates and performs the clamping action again.

其中該夾爪於自行設定次數下仍未成功夾持物件時,由該控制單元操作該夾爪沿著該輸送平台的垂直軸旋 轉90度,藉此夾持物件的不同位置,或傾斜該夾爪使該景深相機額外拍攝物件的側邊影像畫面,藉此就物件高度分析重心位置而提供新的夾持座標。 When the clamping jaw fails to clamp the object for the number of times set by itself, the control unit operates the clamping jaw to rotate along the vertical axis of the conveying platform Rotate 90 degrees to clamp different positions of the object, or tilt the clamping jaws to allow the depth-of-field camera to additionally capture the side image of the object, thereby providing new clamping coordinates by analyzing the position of the center of gravity of the object.

本創作的主要目的在於,該景深相機於起始座標處對物件拍攝影像畫面,透過該演算單元分析影像畫面得知物件位置、中心座標與尺寸比例,再依據物件該中心座標演算得知夾持座標,以及該起始座標至夾持座標之間的位移路徑,該演算單元於位移路徑上產生有校正座標,當該夾爪位移至該校正座標時,再次對物件拍攝影像畫面,分析與判斷夾持座標是否一致,藉此讓該夾爪精準定位的移動至夾持座標,即能利用該景深相機於該夾爪處的無遮蔽影像畫面與景深測距功能,即時對該夾爪進行微調校正。 The main purpose of this creation is that the depth-of-field camera shoots an image frame of the object at the starting coordinates, analyzes the image frame through the arithmetic unit to obtain the object position, center coordinates and size ratio, and then calculates the clamping according to the center coordinates of the object The coordinates and the displacement path from the starting coordinates to the clamping coordinates. The calculation unit generates correction coordinates on the displacement path. When the clamping jaws are displaced to the correction coordinates, an image of the object is taken again for analysis and judgment Whether the gripping coordinates are consistent, so that the gripper can be accurately positioned to move to the gripping coordinate, that is, the unobstructed image of the depth-of-field camera at the gripper and the depth-of-field ranging function can be used to fine-tune the gripper in real time Correction.

其他目的、優點和本創作的新穎特性將從以下詳細的描述與相關的附圖更加顯明。 Other purposes, advantages, and novel features of this creation will be more apparent from the following detailed description and related drawings.

〔本創作〕 [This creation]

10:輸送平台 10: Conveying platform

20:機械手臂 20: Robotic arm

21:夾爪 21: Gripper

22:控制單元 22: control unit

23:荷重單元 23: Load cell

30:景深相機 30: Depth of Field Camera

31:演算單元 31: Calculation unit

32:主鏡頭 32: main lens

33:副鏡頭 33: Secondary lens

34:平面邊界框 34: plane bounding box

341:邊界座標 341: boundary coordinates

35:雲端伺服器 35: Cloud server

A:中心座標 A: Center coordinates

〔第1圖〕係本創作之立體圖。 [Picture 1] is a three-dimensional view of this creation.

〔第2圖〕係本創作景深相機之鏡頭示意圖。 [Picture 2] is the lens diagram of the creative depth-of-field camera.

〔第3圖〕係本創作之影像畫面分析示意圖。 [Picture 3] is a schematic diagram of the image analysis of this creation.

〔第4圖〕係本創作之元件關係之方塊圖。 [Figure 4] is a block diagram of the relationship between the components of this creation.

〔第5圖〕係本創作之作動步驟之流程方塊圖。 [Picture 5] is the flow block diagram of the action steps of this creation.

為使貴審查委員對本創作之目的、特徵及功效能夠有更進一步之瞭解與認識,以下茲請配合【圖式簡單說明】詳述如後: In order to enable your reviewer to have a further understanding and understanding of the purpose, features and effects of this creation, please cooperate with the following [Schematic Description] as detailed below:

先請由第1圖、第2圖與第4圖所示觀之,一種即時校正夾持座標之機械手臂系統,包括:一輸送平台10、一機械手臂20及一景深相機30,一輸送平台10用於連續輸送物件至指定位置,一機械手臂20設置於該輸送平台10一側,且該機械手臂20末端設置有可三維座標移動的一夾爪21,又該機械手臂20內建有即時判斷該夾爪21座標之一控制單元22,且該夾爪21於該輸送平台10上方的固定位置定義為起始座標,一景深相機30固定於該機械手臂20之該夾爪21上,且該景深相機30之鏡頭正面對準於該夾爪21朝向,又該景深相機30與該控制單元22連線有一演算單元31,又該景深相機30包括有一主鏡頭32與一副鏡頭33,該副鏡頭33用於感測距離,使該主鏡頭32所拍攝影像畫面具有景深效果。 First, please observe from the first, second and fourth figures, a robotic arm system for real-time correction of clamping coordinates, including: a conveying platform 10, a robotic arm 20, a depth camera 30, and a conveying platform 10 is used to continuously convey objects to a designated position. A robotic arm 20 is arranged on the side of the conveying platform 10, and the end of the robotic arm 20 is provided with a gripper 21 that can move in three-dimensional coordinates. A control unit 22 determines the coordinates of the gripper 21, and the fixed position of the gripper 21 above the conveying platform 10 is defined as the starting coordinate, a depth camera 30 is fixed on the gripper 21 of the robotic arm 20, and The front of the depth-of-field camera 30 is aligned with the jaw 21, and the depth-of-field camera 30 is connected to the control unit 22 with an arithmetic unit 31. The depth-of-field camera 30 includes a main lens 32 and a secondary lens 33. The secondary lens 33 is used for sensing distance, so that the image captured by the main lens 32 has a depth effect.

其實際使用之情況,再請由第4、5圖配合第1圖所示觀之,當物件被該輸送平台10輸送至該機械手臂20對應處時,該景深相機30於起始座標處對物件拍攝影像畫面,若未拍攝到任何物件或拍到的物件不完整時,將會於短暫間隔後再重覆拍攝,若有拍攝到物件時,透過該演算單元31分析影像畫面得知物件位置,且基於起始座標與景深距離就能運算得知物件的一中心座標A與尺寸比例,再依據物件該中心座 標A演算得知夾持座標,夾持座標即為物件的上方適當處,使夾爪21能對物件的重心處進行夾合,再進一步規劃該起始座標至夾持座標之間的位移路徑,基本上讓夾爪21沿著位移路徑進行向量移動,再者,該演算單元31於位移路徑上自動產生有至少一個校正座標,校正座標為位移路徑上的任意點,得依據路徑長度或路徑時間分割多段的校正座標,讓夾爪21於移動過程中能不斷的自主修正座標位置,當控制單元22移動該夾爪21位移至該校正座標時,能先由該控制單元22判斷該夾爪21所在座標,於校正座標與實際位置座標之間的誤差過大時,該控制單元22將該夾爪21移動回到起始座標,重新開始,如僅存在微小誤差時,該控制單元22能直接移動該夾爪21至正確的校正座標,讓該景深相機30再次對物件拍攝影像畫面,透過該演算單元31分析影像畫面並比對與前次判斷的夾持座標是否一致,如有一致則將該夾爪21移動至下一個校正座標或夾持座標,藉此讓該夾爪21精準定位的移動至夾持座標,再基於物件的尺寸比例夾合該夾爪21至指定寬度,即能利用該景深相機30於該夾爪21處的無遮蔽影像畫面與景深測距功能,即時對該夾爪21進行微調校正,俾以達到穩定夾持物件之功效。 In actual use, please refer to Figures 4 and 5 in conjunction with Figure 1. When the object is conveyed by the conveying platform 10 to the corresponding position of the robotic arm 20, the depth-of-field camera 30 is aligned at the starting coordinates. Object shooting image screen. If no object is captured or the captured object is incomplete, the shooting will be repeated after a short interval. If an object is captured, the calculation unit 31 analyzes the image screen to know the location of the object , And based on the starting coordinates and the depth of field distance, you can calculate a center coordinate A and the size ratio of the object, and then according to the center of the object The standard A calculation knows the clamping coordinates. The clamping coordinates are the appropriate places above the object, so that the gripper 21 can clamp the center of gravity of the object, and then further plan the displacement path from the starting coordinates to the clamping coordinates , Basically let the gripper 21 move vectorially along the displacement path. Moreover, the calculation unit 31 automatically generates at least one correction coordinate on the displacement path. The correction coordinate is any point on the displacement path, which depends on the path length or path. Time-divided multi-segment correction coordinates, so that the gripper 21 can continuously and autonomously correct the coordinate position during the movement. When the control unit 22 moves the gripper 21 to the correction coordinate, the control unit 22 can first determine the gripper 21. When the error between the calibration coordinates and the actual position coordinates is too large, the control unit 22 moves the gripper 21 back to the starting coordinates and restarts. If there is only a slight error, the control unit 22 can directly Move the gripper 21 to the correct calibration coordinates, and let the depth-of-field camera 30 take an image of the object again, analyze the image through the arithmetic unit 31 and compare whether it is consistent with the previously determined gripping coordinates. The clamping jaw 21 moves to the next calibration coordinate or clamping coordinate, so that the clamping jaw 21 is accurately positioned and moved to the clamping coordinate, and then the clamping jaw 21 is clamped to a specified width based on the size ratio of the object, which can be used The unobstructed image of the depth-of-field camera 30 at the gripper 21 and the depth-of-field distance measurement function can perform fine adjustment and correction on the gripper 21 in real time, so as to achieve the effect of stably gripping objects.

再進一步說明其演算方法,請由第3、4圖所示觀之,該演算單元31利用已知的該起始座標與影像畫面之景深進行運算,使影像畫面能繪制圍設該物件的一平面邊界框 34,且該平面邊界框34於一端角落定義為一邊界座標341,又該演算單元31以該平面邊界框34運算得知物件之中心座標A與尺寸比例,又該平面邊界框34的長寬比設定為(w,h),該邊界座標341設定為(Xi,Yi),該演算單元31以該平面邊界框34運算得知該中心座標A為((Xi-w/2),(Yi-h/2)),又該起始座標設定為(X0,Y0),且該物件尺寸比例設定為Z,即能獲得對應物件之X點移動向量為-((Xi-w/2)-X0)/Z,以及對應物件之Y點移動向量為-((Yi-h/2)-Y0)/Z,其中,X點與Y點之移動向量採用負數表示,主要是位移方向與向量的對應關係,並不局限於採用正數或負數,另X點與Y點之移動向量亦能乘除單位換算值,使移動向量的數值能放大而被控制單元22直接讀取與應用,透過上述演算過程將影像畫面之座標點轉換為實際座標點,再進一步計算實際移動向量並發送給該機械手臂20之該控制單元22,俾以達到驅動該機械手臂20之使用目的。 To further explain its calculation method, please observe it from Figures 3 and 4. The calculation unit 31 uses the known starting coordinates and the depth of field of the image frame to perform calculations, so that the image frame can draw an image surrounding the object. A plane bounding box 34, and the plane bounding box 34 is defined as a boundary coordinate 341 at one end corner, and the calculation unit 31 uses the plane bounding box 34 to calculate the center coordinate A and the size ratio of the object, and the plane bounding box 34 The aspect ratio of is set to (w, h), the boundary coordinate 341 is set to (Xi, Yi), the calculation unit 31 uses the plane boundary box 34 to calculate that the center coordinate A is ((Xi-w/2) ,(Yi-h/2)), and the starting coordinates are set to (X 0 ,Y 0 ), and the size ratio of the object is set to Z, the X point movement vector of the corresponding object can be obtained as -((Xi- w/2)-X 0 )/Z, and the Y point movement vector of the corresponding object is -((Yi-h/2)-Y 0 )/Z, where the movement vector between X point and Y point is represented by a negative number, It is mainly the correspondence relationship between the displacement direction and the vector. It is not limited to the use of positive or negative numbers. In addition, the movement vector of point X and Y can also be multiplied and divided by the unit conversion value, so that the value of the movement vector can be amplified and read directly by the control unit 22 And application, the coordinate points of the image frame are converted into actual coordinate points through the above calculation process, and then the actual movement vector is further calculated and sent to the control unit 22 of the robotic arm 20 to achieve the purpose of driving the robotic arm 20.

再進一步說明該夾爪21的夾持作動機制,續請由第4、5圖所示,該夾爪21位移至夾持座標後,使該夾爪21旋轉角度對準物件之中心座標A,並由該控制單元22驅動該夾爪21進行夾持動作,於該夾爪21夾持物件不足或超過指定寬度之容許值時,該演算單元31判斷夾持失敗,由該控制單元22將該夾爪21位移至上一步驟之校正座標,再次由該景深相機30進行拍攝,且由該演算單元31重新計算新的夾持座標,重新進行夾持動作。另一實施方式,該機械手臂20於該夾爪21處 裝設有一荷重單元23,於操作該夾爪21進行夾持動作後,該荷重單元23未偵測到該夾爪21保持有重量的增加,該演算單元31即能判斷夾持失敗,由該控制單元22將該夾爪21位移至上一步驟之校正座標,再次由該景深相機30進行拍攝,且由該演算單元31重新計算新的夾持座標,重新進行夾持動作。若由上述兩種方式皆未能成功夾持物件時,或該夾爪21於自行設定次數下仍未成功夾持物件時,由該控制單元22操作該夾爪21沿著該輸送平台10的垂直軸旋轉90度,藉此夾持物件的不同位置,或傾斜該夾爪21使該景深相機30額外拍攝物件的側邊影像畫面,藉此就物件高度分析重心位置而提供新的夾持座標,又當順利夾持物件後,該控制單元22控制該夾爪21回復至起始座標位置,並待候下個物件進入該機械手臂20的活動範圍內。 Further explain the clamping action mechanism of the clamping jaw 21. As shown in Figures 4 and 5, after the clamping jaw 21 is displaced to the clamping coordinate, the rotation angle of the clamping jaw 21 is aligned with the center coordinate A of the object. And the control unit 22 drives the clamping jaw 21 to perform a clamping action. When the clamping jaw 21 is not enough or exceeds the allowable value of the specified width, the calculation unit 31 determines that the clamping fails, and the control unit 22 The clamping jaw 21 is displaced to the calibration coordinates of the previous step, and the depth camera 30 is used for shooting again, and the calculation unit 31 recalculates the new clamping coordinates and performs the clamping operation again. In another embodiment, the robotic arm 20 is positioned at the jaw 21 A loading unit 23 is installed. After the clamping jaw 21 is operated to perform a clamping action, the loading unit 23 does not detect that the clamping jaw 21 maintains an increase in weight. The calculation unit 31 can then determine that the clamping has failed. The control unit 22 displaces the clamping jaw 21 to the correction coordinates of the previous step, and the depth camera 30 takes pictures again, and the calculation unit 31 recalculates the new clamping coordinates and performs the clamping operation again. If the object is not successfully clamped by the above two methods, or the clamping jaw 21 fails to clamp the object for the number of times set by itself, the control unit 22 operates the clamping jaw 21 along the conveying platform 10 The vertical axis rotates 90 degrees to clamp different positions of the object, or tilt the clamping jaw 21 to make the depth-of-field camera 30 additionally capture the side image of the object, thereby providing new clamping coordinates for the object height analysis of the center of gravity position After the object is successfully clamped, the control unit 22 controls the clamping jaw 21 to return to the initial coordinate position, and waits for the next object to enter the movable range of the robotic arm 20.

本創作之又一實施例,再請由第4、5圖所示觀之,該演算單元31連接有一雲端伺服器35,該雲端伺服器35儲存有提供辨視物件使用之影像畫面及對應物件之相關資料,讓該演算單元31深度學習該雲端伺服器35之影像畫面,藉此提高對物件的判斷精準度。另一方面,該景深相機30於執行拍攝指令時,該演算單元31能記錄全部物件之影像畫面,並於該雲端伺服器35建立影像專案資料夾,使該景深相機30後續所拍攝的影像畫面能直接比對影像專案資料夾內之影像畫面,透過大量的自我深度學習過程,藉此提高該演算 單元31之運算速度與判斷精準度。再者,該夾爪21沿著位移路徑執行位移動作時,該演算單元31能記錄全部位移路徑與是否到達指定的校正座標或夾持座標,並於該雲端伺服器35建立路徑專案資料夾,透過數據分析判斷相同或相近之位移路徑皆無法讓夾爪21到達指定位置時,很可能為該機械手臂20長期存在的機構缺陷,導致該夾爪21每次移動至固定座標位置時就會脫離位移路徑,此時該演算單元31後續將排除不良的位移路徑,當新產生的位移路徑重疊已排除之不良位移路徑時,重新於該段路徑一側建立新路徑,即透過繞路方式提高定位精準度,俾以提高該機械手臂20之位移效率。 Another embodiment of this creation, please look at it as shown in Figures 4 and 5. The calculation unit 31 is connected to a cloud server 35, and the cloud server 35 stores image frames and corresponding objects used to identify objects. The relevant data allows the calculation unit 31 to deeply learn the image frame of the cloud server 35, thereby improving the accuracy of determining the object. On the other hand, when the depth-of-field camera 30 executes a shooting command, the arithmetic unit 31 can record the image frames of all objects, and create an image project folder on the cloud server 35 to enable the depth-of-field camera 30 to subsequently capture the image frames Can directly compare the images in the image project folder, and improve the calculation through a large amount of self-deep learning process The calculation speed and judgment accuracy of the unit 31. Furthermore, when the gripper 21 performs a displacement action along the displacement path, the arithmetic unit 31 can record all the displacement paths and whether the specified calibration coordinates or clamping coordinates are reached, and create a path project folder on the cloud server 35, When it is judged through data analysis that the same or similar displacement paths cannot allow the gripper 21 to reach the specified position, it is likely to be a long-standing mechanical defect of the mechanical arm 20, which causes the gripper 21 to detach every time it moves to a fixed coordinate position. Displacement path. At this time, the calculation unit 31 will subsequently eliminate the bad displacement path. When the newly generated displacement path overlaps the excluded bad displacement path, a new path is re-established on the side of the path, that is, the positioning is improved by detouring The accuracy is to improve the displacement efficiency of the robot arm 20.

綜上所述,本創作確實已達突破性之結構設計,而具有改良之新型內容,同時又能夠達到產業上之利用性與進步性,且本創作未見於任何刊物,亦具新穎性,當符合專利法相關法條之規定,爰依法提出新型專利申請,懇請 鈞局審查委員授予合法專利權,至為感禱。 To sum up, this creation has indeed achieved a breakthrough structural design, and has improved new content, while at the same time it can achieve industrial utilization and progress. Moreover, this creation has not been seen in any publications, and it is also novel. In accordance with the relevant provisions of the Patent Law, Yan filed a new patent application in accordance with the law, and I implore the Jun Bureau review committee to grant legal patent rights. I really pray.

唯以上所述者,僅為本創作之一較佳實施例而已,當不能以之限定本創作實施之範圍;即大凡依本新型申請專利範圍所作之均等變化與修飾,皆應仍屬本新型專利涵蓋之範圍內。 Only the above is only one of the preferred embodiments of this creation, and should not be used to limit the scope of implementation of this creation; that is, all equal changes and modifications made in accordance with the scope of the patent application for this new model should still belong to this new model Covered by the patent.

10:輸送平台 10: Conveying platform

20:機械手臂 20: Robotic arm

21:夾爪 21: Gripper

30:景深相機 30: Depth of Field Camera

Claims (10)

一種即時校正夾持座標之機械手臂系統,包括: A mechanical arm system for real-time correction of clamping coordinates, including: 一輸送平台,其用於連續輸送物件至指定位置; A conveying platform, which is used to continuously convey objects to a designated position; 一機械手臂,其設置於該輸送平台一側,且該機械手臂末端設置有可三維座標移動的一夾爪,又該機械手臂內建有即時判斷該夾爪座標之一控制單元,且該夾爪於該輸送平台上方的固定位置定義為起始座標; A mechanical arm is arranged on one side of the conveying platform, and the end of the mechanical arm is provided with a gripper that can move in three-dimensional coordinates, and a control unit for real-time judgment of the coordinate of the gripper is built in the mechanical arm, and the gripper The fixed position of the claw above the conveying platform is defined as the starting coordinate; 一景深相機,其固定於該機械手臂之該夾爪上,且該景深相機之鏡頭正面對準於該夾爪朝向,又該景深相機與該控制單元連線有一演算單元; A depth-of-field camera, which is fixed on the gripper of the robotic arm, the front of the lens of the depth-of-field camera is aligned with the direction of the gripper, and the depth-of-field camera is connected to the control unit with an arithmetic unit; 該景深相機於起始座標處對物件拍攝影像畫面,透過該演算單元分析影像畫面得知物件位置,且基於起始座標與景深距離就能運算得知物件的一中心座標與尺寸比例,再依據物件該中心座標演算得知夾持座標,以及該起始座標至夾持座標之間的位移路徑,該演算單元於位移路徑上自動產生有至少一個校正座標,當控制單元移動該夾爪位移至該校正座標時,該景深相機再次對物件拍攝影像畫面,透過該演算單元分析影像畫面並比對與前次判斷的夾持座標是否一致,藉此讓該夾爪精準定位的移動至夾持座標,再基於物件的尺寸比例夾合該夾爪至指定寬度,即能利用該景深相機於該夾爪處的無遮蔽影像畫面與景深測距功能,即時對該夾爪進行微調校正。 The depth-of-field camera shoots an image frame of the object at the starting coordinates, and the calculation unit analyzes the image frame to know the position of the object, and based on the starting coordinates and the depth-of-field distance, it can calculate a center coordinate and size ratio of the object. The center coordinate calculation of the object obtains the clamping coordinates and the displacement path from the starting coordinate to the clamping coordinates. The calculation unit automatically generates at least one correction coordinate on the displacement path. When the control unit moves the clamping jaw to When the coordinates are calibrated, the depth-of-field camera again shoots an image frame of the object, analyzes the image frame through the calculation unit and compares whether it is consistent with the previously determined clamping coordinates, so that the clamping jaw can be accurately positioned and moved to the clamping coordinates , And then clamp the gripper to a specified width based on the size ratio of the object, that is, the unobstructed image frame of the depth-of-field camera at the gripper and the depth-of-field ranging function can be used to fine-tune and correct the gripper instantly. 如請求項1之即時校正夾持座標之機械手臂系統,其中該景深相機包括有一主鏡頭與一副鏡頭,該副鏡頭用於感測距離,使該主鏡頭所拍攝影像畫面具有景深效果。 For example, the robotic arm system for real-time correction of the clamping coordinates of claim 1, wherein the depth-of-field camera includes a main lens and a sub-lens, and the sub-lens is used to sense the distance so that the image captured by the main lens has a depth effect. 如請求項1之即時校正夾持座標之機械手臂系統,其中該演算單元連接有一雲端伺服器,該雲端伺服器儲存有提供辨視物件使用之影像畫面及對應物件之相關資料,讓該演算單元深度學習該雲端伺服器之影像畫面,藉此提高對物件的判斷精準度。 For example, the robotic arm system for real-time calibration of the clamping coordinates of the request item 1, wherein the calculation unit is connected to a cloud server, and the cloud server stores the image screen used to identify the object and the related data of the corresponding object, so that the calculation unit Deeply learn the image of the cloud server to improve the accuracy of the judgment of the object. 如請求項3之即時校正夾持座標之機械手臂系統,其中該景深相機於執行拍攝指令時,該演算單元能記錄全部物件之影像畫面,並於該雲端伺服器建立影像專案資料夾,使該景深相機後續所拍攝的影像畫面能直接比對影像專案資料夾內之影像畫面,藉此提高該演算單元之運算速度與判斷精準度。 For example, the robotic arm system for real-time calibration of the clamping coordinates of claim 3, where the depth-of-field camera executes the shooting command, the arithmetic unit can record the image frames of all objects, and create an image project folder on the cloud server to make the The subsequent image frames captured by the depth-of-field camera can be directly compared with the image frames in the image project folder, thereby improving the calculation speed and accuracy of the calculation unit. 如請求項3之即時校正夾持座標之機械手臂系統,其中該夾爪沿著位移路徑執行位移動作時,該演算單元能記錄全部位移路徑與是否到達指定的校正座標或夾持座標,並於該雲端伺服器建立路徑專案資料夾,透過數據分析判斷相同或相近之位移路徑皆無法讓夾爪到達指定位置時,該演算單元後續將排除不良的位移路徑,透過繞路方式提高定位精準度。 For example, the mechanical arm system for real-time correction of the clamping coordinates of claim 3, wherein when the clamping jaw performs a displacement action along the displacement path, the calculation unit can record all the displacement paths and whether it reaches the designated correction coordinates or the clamping coordinates, and then The cloud server creates a path project folder, and when data analysis determines that the same or similar displacement paths cannot allow the gripper to reach the specified position, the calculation unit will subsequently eliminate the bad displacement path and improve the positioning accuracy by detouring. 如請求項1之即時校正夾持座標之機械手臂系統,其中該演算單元利用已知的該起始座標與影像畫面之景深進行運算,使影像畫面能繪制圍設該物件的一平面邊界框,且該平面邊界框於一端角落定義為一邊界座標,又該演算單元以該平面邊界框運算得知物件之中心座標與尺寸比例。 For example, the mechanical arm system for real-time correction of the clamping coordinates of claim 1, wherein the calculation unit uses the known starting coordinates and the depth of field of the image frame to perform calculations, so that the image frame can draw a plane bounding box surrounding the object, And the plane bounding box is defined as a boundary coordinate at one end corner, and the calculation unit calculates the center coordinate and the size ratio of the object based on the plane bounding box. 如請求項6之即時校正夾持座標之機械手臂系統,其中該平面邊界框的長寬比設定為(w,h),該邊界座標設定為(Xi,Yi),該演算單元以該平面邊界框運算得知該中心座標為((Xi-w/2),(Yi-h/2)),又該起始座標設定為(X0,Y0),且該物件尺寸比例設定為Z,即能獲得對應物件之X點移動向量為-((Xi-w/2)-X0)/Z,以及對應物件之Y點移動向量為-((Yi-h/2)-Y0)/Z。 For example, the robot arm system for real-time correction of the clamping coordinates of claim 6, wherein the aspect ratio of the plane bounding box is set to (w, h), the boundary coordinates are set to (Xi, Yi), and the calculation unit is based on the plane boundary Box operation knows that the center coordinate is ((Xi-w/2),(Yi-h/2)), and the starting coordinate is set to (X 0 ,Y 0 ), and the object size ratio is set to Z, That is, the X point movement vector of the corresponding object is -((Xi-w/2)-X 0 )/Z, and the Y point movement vector of the corresponding object is -((Yi-h/2)-Y 0 )/ Z. 如請求項1之即時校正夾持座標之機械手臂系統,其中該夾爪位移至夾持座標,使該夾爪旋轉角度對準物件之中心座標,該夾爪夾持物件不足或超過指定寬度之容許值時,該演算單元判斷夾持失敗,由該控制單元將該夾爪位移至上一步驟之校正座標,再次由該景深相機進行拍攝,且由該演算單元重新計算新的夾持座標,重新進行夾持動作。 For example, the mechanical arm system for real-time correction of the clamping coordinates of request 1, in which the clamping jaw is displaced to the clamping coordinate, so that the rotation angle of the clamping jaw is aligned with the center coordinate of the object, and the clamping jaw is insufficient or exceeds the specified width When the allowable value is allowed, the arithmetic unit judges that the clamping has failed, the control unit moves the gripper to the calibration coordinates of the previous step, and the depth-of-field camera shoots again, and the arithmetic unit recalculates the new clamping coordinates. Perform clamping action. 如請求項1之即時校正夾持座標之機械手臂系統,其中該機械手臂於該夾爪處裝設有一荷重單元,於操 作該夾爪進行夾持動作後,該荷重單元未偵測到該夾爪保持有重量的增加,該演算單元即能判斷夾持失敗,由該控制單元將該夾爪位移至上一步驟之校正座標,再次由該景深相機進行拍攝,且由該演算單元重新計算新的夾持座標,重新進行夾持動作。 For example, the mechanical arm system for real-time correction of the clamping coordinates of claim 1, wherein the mechanical arm is equipped with a load unit at the gripper, and the operation After the clamping jaw is used for the clamping action, the load unit does not detect that the clamping jaw maintains an increase in weight, the calculation unit can then judge the clamping failure, and the control unit displaces the clamping jaw to the previous step of calibration The coordinates are photographed by the depth-of-field camera again, and new clamping coordinates are recalculated by the calculation unit, and the clamping action is performed again. 如請求項1之即時校正夾持座標之機械手臂系統,其中該夾爪於自行設定次數下仍未成功夾持物件時,由該控制單元操作該夾爪沿著該輸送平台的垂直軸旋轉90度,藉此夾持物件的不同位置,或傾斜該夾爪使該景深相機額外拍攝物件的側邊影像畫面,藉此就物件高度分析重心位置而提供新的夾持座標。 For example, the mechanical arm system for real-time correction of the clamping coordinates of claim 1, where the gripper fails to grip the object for the number of times set by itself, the control unit operates the gripper to rotate 90 along the vertical axis of the conveying platform In this way, different positions of the object can be clamped, or the clamping jaw can be tilted so that the depth-of-field camera additionally captures the side image of the object, thereby providing new clamping coordinates by analyzing the position of the center of gravity of the object.
TW109209918U 2020-07-31 2020-07-31 Robotic manipulator system for real-time correction of clamping coordinate TWM606382U (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
TW109209918U TWM606382U (en) 2020-07-31 2020-07-31 Robotic manipulator system for real-time correction of clamping coordinate

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
TW109209918U TWM606382U (en) 2020-07-31 2020-07-31 Robotic manipulator system for real-time correction of clamping coordinate

Publications (1)

Publication Number Publication Date
TWM606382U true TWM606382U (en) 2021-01-11

Family

ID=75238639

Family Applications (1)

Application Number Title Priority Date Filing Date
TW109209918U TWM606382U (en) 2020-07-31 2020-07-31 Robotic manipulator system for real-time correction of clamping coordinate

Country Status (1)

Country Link
TW (1) TWM606382U (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI739536B (en) * 2020-07-31 2021-09-11 創璟應用整合有限公司 Robotic arm system for real-time correction of clamping coordinates
CN114326477A (en) * 2021-12-02 2022-04-12 四川广目科技有限公司 Control system of intelligent sensing industrial robot based on open source framework

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI739536B (en) * 2020-07-31 2021-09-11 創璟應用整合有限公司 Robotic arm system for real-time correction of clamping coordinates
CN114326477A (en) * 2021-12-02 2022-04-12 四川广目科技有限公司 Control system of intelligent sensing industrial robot based on open source framework

Similar Documents

Publication Publication Date Title
JP5282717B2 (en) Robot system
CN106426161B (en) System and method for correlating machine vision coordinate spaces in a guided assembly environment
TWI670153B (en) Robot and robot system
US9519736B2 (en) Data generation device for vision sensor and detection simulation system
JP5561384B2 (en) Recognition program evaluation apparatus and recognition program evaluation method
TWM606382U (en) Robotic manipulator system for real-time correction of clamping coordinate
CN108748149B (en) Non-calibration mechanical arm grabbing method based on deep learning in complex environment
CN113146172B (en) Multi-vision-based detection and assembly system and method
JP7377627B2 (en) Object detection device, object grasping system, object detection method, and object detection program
CN110378325B (en) Target pose identification method in robot grabbing process
US11625842B2 (en) Image processing apparatus and image processing method
CN110539299B (en) Robot working method, controller and robot system
US20210086366A1 (en) Controller of robot apparatus for adjusting position of member supported by robot
JP7481427B2 (en) Removal system and method
US20190255706A1 (en) Simulation device that simulates operation of robot
CN113689509A (en) Binocular vision-based disordered grabbing method and system and storage medium
WO2022021156A1 (en) Method and apparatus for robot to grab three-dimensional object
Gratal et al. Virtual visual servoing for real-time robot pose estimation
CN111390910A (en) Manipulator target grabbing and positioning method, computer readable storage medium and manipulator
EP2696164A1 (en) Three-dimensional position/posture recognition device, three-dimensional position/posture recognition method, and three-dimensional position/posture recognition program
TWI739536B (en) Robotic arm system for real-time correction of clamping coordinates
WO2021039775A1 (en) Image processing device, image capturing device, robot, and robot system
CN113021391A (en) Integrated vision robot clamping jaw and using method thereof
CN110853102A (en) Novel robot vision calibration and guide method, device and computer equipment
WO2022257550A1 (en) Docking method for self-moving forklift, and self-moving forklift