ERVII_Image_Processing

Introduction

The main idea of this file is to present the analysis, design, problems and implementation of a c++ program instance that could control the ERVII (ER7) arm in order to detect several different objects and manipulate them in such a way that could be staffed in a pyramid ordered by size.

To see it in action (YouTube video), click here.

Goal

This project's main goal is stated as: Given a set of randomly picked objects, you need to locate these objects through a given camera and pick and place these objects as a stack. With this idea in mind, the logic of the processes needed to solve this were stated as

1. Obtain images from camera.
2. Work on camera calibration.
3. Work on the inverse kinematics (when solvable)
4. Design and implement a c++ program to communicate with the ER7 arm via ACL.

Camera software and calibration

In order to use the camera's images and make an analysis of the objects captured by it, we used openCV libraries that already have several different image processing characteristics inside their methods.

Datastructure

The main() clause in our c++ implementation is stated as follows:

int main(){
    hCom = rs232_open("COM1");
    if(hCom == 0)
        exit(-1);
    //Initialize arm
    initializeArm();
    //Make camera calibration and obtain objects in obtainObjectsAndNumbers()
    er7Actions(obtainObjectsAndNumbers());
    return 0;
}

The camera administration is made under the obtainObjectsAndNumbers() method, which is a customized object structure called objectsAndNumbers, where both the structures involved and the abstract constructor are stated as follow:

struct object{
    //properties
    double area;
    double phi;
    double gyrumAngle;
    double principalAngle;
    Point2f centroid;
};

struct objectsAndNumbers{
    //properties
    vector<object> vectorObject;
    int numberOfObjects;
    //Constructor
    objectsAndNumbers(vector<object> vectorObjectInput,int numberOfObjectsInput): 
         vectorObject(vectorObjectInput), numberOfObjects(numberOfObjectsInput){ }
};

and the interface stated as

objectsAndNumbers obtainObjectsAndNumbers();

The obtainObjectsAndNumbers() returns an abstract object made of two objects, a

vector<object> vectorObject

which is the list of the already analyzed objects, and a int numberOfObjects which contains the number of objects obtained.

Note

From the above code, we can see that all the necessary characteristics are inside the objectsAndNumbers abstract structure. In order to access the properties of the n-th object, the path that is needed is just

&obtainObjectsAndNumbers().vectorObject[n].area;
&obtainObjectsAndNumbers().vectorObject[n].phi;
&obtainObjectsAndNumbers().vectorObject[n].gyrumAngle;
&obtainObjectsAndNumbers().vectorObject[n].principalAngle;
&obtainObjectsAndNumbers().vectorObject[n].centroid;

and to access the number of objects is just needed

&obtainObjectsAndNumbers().numberOfObjects;

Because the vectorObject[n] requires an specific number to be accessed, is was easier to carry with the number of objects from the previous method and add it as an object in the structure than calculating from the vectorObject[] itself.

These abstract objects were necessary to be created in order to save and use in a more order way the objects' analysis results obtained from the camera analysis.

openCV methods

After capturing the image from the camera, several processes are needed to be performed before the contours can be calculated (As well as the barycenters and inertial axis of the objects). We have then the code

Mat resultRealWorldImage;
resultRealWorldImage = realWorldImage.clone();
//Apply blur, binarization and dilatation
blur(resultRealWorldImage, resultRealWorldImage, Size(6,6));
threshold(resultRealWorldImage, resultRealWorldImage, 80, 255, CV_THRESH_BINARY);
erode(resultRealWorldImage,resultRealWorldImage, Mat(6,6,0));
dilate(resultRealWorldImage,resultRealWorldImage, Mat(6,6,0));
//Finding contours process begins
//Objects for managing obtained information of contours
vector<vector<Point> > foundContours;
vector<Vec4i> outputArrayHierarchy;
//Finding contour methods
Canny(resultRealWorldImage, resultRealWorldImage, 100, 255, 3);
//Applies Canny edge detector and produces the edge map.
findContours(resultRealWorldImage, foundContours, outputArrayHierarchy, CV_RETR_TREE, 
       CV_CHAIN_APPROX_SIMPLE, Point(0,0));

The methods from the openCV libraries that were used are, specifically, blur, threshold, erode, dilate, canny and findcontours. After this transformations, aspects like the inertial axis, barycenters and areas can be calculated from the objects.

Inverse kinematics

In order to find the general movement equations that could describe the system, the inverse kinematics were developed from the system described in Figure 1.

Because our system only counts with one camera, the depth of the objects was obtained by hand, getting an approx of 4 cms of thickness on the objects. In order to make the pile, the high of it must be saved in a variable and carried on along the overall run.

Calculation of object positions and arm movement

Before the object position calculations are made, is necessary to manipulate the picture before hand in order to get an accurate number for our actual system. We obtain a picture like the following after all the camera transformations and the findContours method have been applied.

After each object's information is calculated, is displayed on console, so the user can get the information of it.

The main() has a

er7Actions(obtainObjectsAndNumbers());

where obtainObjectsAndNumbers() is an objectsAndNumbers class method, which returns the objects already analyzed by the camera and the number of objects as well. In order to calculate the height, place of movement and height of the pyramid to the ER7 arm, the SETPVC and MOVE instructions were used as follow

cout << "[Object inside working area" << endl;
z+=390;
sendInstructionToER7("SETPVC TMP",numerOfObjects ," z ", z);
sendInstructionToER7("MOVE TMP");
Sleep(1000);
z-=390;
sendInstructionToER7("SETPVC TMP",numerOfObjects ," z ", z);
sendInstructionToER7("MOVE TMP");
Sleep(1000);
sendInstructionToER7("CLOSE");
Sleep(1000);
z+=390*(heightOfObject+1);
rollOfObject=-201+((-1)*objectsAndNumbersInput.vectorObject[baseObjectIndex].phi-objectsAndNumbersInput.vectorObject[baseObjectIndex].gyrumAngle)/pi*(180*10);
sendInstructionToER7("SETPVC TMP",numerOfObjects," z ", z);
sendInstructionToER7("SETPVC TMP",numerOfObjects," r ", rollOfObject);
sendInstructionToER7("MOVE TMP%d",numerOfObjects);
Sleep(1000);
gotoPointNew(objectsAndNumbersInput.vectorObject[baseObjectIndex].centroid.x,
          objectsAndNumbersInput.vectorObject[baseObjectIndex].centroid.y, z, -900, rollOfObject);
Sleep(1000);
z-=385;
sendInstructionToER7("SETPVC TMP",numerOfObjects," z ", z);
sendInstructionToER7("MOVE TMP%d",numerOfObjects);
Sleep(1000);
sendInstructionToER7("OPEN");
Sleep(1000);
z+=500;
sendInstructionToER7("SETPVC TMP",numerOfObjects," z ", z);
sendInstructionToER7("MOVE TMP%d",numerOfObjects);
Sleep(1000);
sendInstructionToER7("MOVE ORIG");
heightOfObject++;

From the last code section, we need to mention:

1. The sendInstructionToER7(x,y,z) function was created in order to solve some of the problems found when programming.
2. After every movement (Picking an object and place it in the pyramid), the arm comes back to the H0 position.
3. After some measures, the z value moved for the object when appalling was of 390, in order to have 1mm of error margin when stacking the objects.
4. Before this set of instructions is performed, the program checks if the object is reachable or not by:
   1. Using an overrided sendReceiveInstructionToER7 function described as follow

   void sendReceiveInstructionToER7(int i1, char* s1){
   	char buf[50];
   	sprintf(buf, "%d", i1);
   	rs232_sendCmd(hCom, buf, s1);
   }

   2. The previous overrided function is used in the following code

   sendReceiveInstructionToER7("TEACH TMP",objectNumber,bufReply[0]);
   sendReceiveInstructionToER7(x,bufReply[1]);
   sendReceiveInstructionToER7(y,bufReply[2]);
   sendReceiveInstructionToER7(z,bufReply[3]);
   sendReceiveInstructionToER7(p,bufReply[4]);
   sendReceiveInstructionToER7(r,bufReply[5]); //GOT FINAL ANSWER FOR R
   //If final answer is BAD POINT COORDINATES, means that the object is out of working space
   char *finalAnswer=strstr(bufReply[5],"Bad");
   if(finalAnswer==NULL){
   	return true;
   }
   //TRY to confirm if 'BAD POINT COORDINATES' is gotten
   memcpy(verifyPointer,finalAnswer,9);
   verifyPointer[9]='\0';
   if(strcmp(verifyPointer,"Bad point")==0){
   	return false;
   }
   return true;

Results

The provided code is able to successfully control an ERVII arm, make image processing of the objects it needs to grab, and create a pyramid (sorted by size) of those objects.

To see it in action (YouTube video), click here.