2D Inverse Kinematics Implementation

Question

Hi

I am trying to implement Inverse Kinematics on a 2D arm(made up of three sticks with joints). I am able to rotate the lowest arm to the desired position. Now, I have some questions:

1. How can I make the upper arm move alongwith the third so the end point of the arm reaches the desired point. Do I need to use the rotation matrices for both and if yes can someone give me some example or an help and is there any other possibl;e way to do this without rotation matrices???

2. The lowest arm only moves in one direction. I tried google it, they are saying that cross product of two vectors give the direction for the arm but this is for 3D. I am using 2D and cross product of two 2D vectors give a scalar. So, how can I determine its direction???

Plz guys any help would be appreciated....

Thanks in advance Vikram

Answer 1

I'll give it a shot, but since my Robotics are two decades in the past, take it with a grain of salt.

The way I learned it, every joint was described by its own rotation matrix, defined relative to its current position and orientation. The coordinate of the whole arm's endpoint was then calculated by combining the rotation matrices together.

This achieved exactly the effect you are looking for: you could move only one joint (change its orientation), and all the other joints followed automatically.

You won't have much chance in getting around matrices here - in fact, if you use homogeneous coordinates, all joint calculations (rotations as well as translations) can be modeled with matrix multiplications. The advantage is that the full arm position can then be described with a single matrix (plus the arm's origin).

With this transformation matrix, you can tackle the inverse kinematic problem: since the transformation matrix' elements will depend on the angles of the joints, you can treat the whole calculation 'endpoint = startpoint x transformation' as a system of equations, and with startpoint and endpoint known, you can solve this system to determine the unknown angles. The difficulty herein lies that the equation may not be solvable, or that there are multiple solutions.

I don't quite understand your second question, though - what are you looking for?

Answer 2

Hi, Thanks for the reply. if I am correct you are suggesting me to use jacobians right? Actually I was using Cyclic Coordinate Descent(CCD) technique. I could not understand Jacobian well. Can you give me some links where i can have aclear picture of that.

And in 2nd question, I am saying that the lowest stick moves only onright side not on right. Google suggests to find cross product to find direction but I am not sure how cross product of 2D vectors can give the direction

Thanks Vikram

Answer 3

In robotics we most often use DH parameters for the forward and reverse kinematics. Wikipedia has a nice introduction.

Answer 4

The DH (Denavit-Hartenberg) notation is part of the solution. It helps you collect a succinct set of values that describe the mechanics of your robot such as link length and joint type.

From there it becomes easier to calculate forward kinematics. The first think you have to understand is how to translate a coordinate frame from one place to another coordinate frame. For example, given your robot (or the DH table of it), what is the set of rotations and translations you have to apply to one coordinate frame (the world for example) to know the location of a point (or vector) in the robot's wrist coordinate frame.

As you may already know, homogeneous transform matrices are very useful for such transformations. They are 4x4 matrices that encapsulate rotation and translation. Another very useful property of those matrices is that if you have two coordinate frames linked and defined by some rotation and translation, if you multiply the two matrices together, then you just need to multiply your transformation target by the product of that multiplication.

So the DH table will help you build that matrix.

Inverse kinematics is a bit more complicated though and depends on your application. The complication arises from having multiple solutions for the same problem. The greater the number of DOF, the greater the number of solutions.

Think about your arm. Pinch something solid around you. You can move your arm to several locations in the space and still keep your pinching vector unchanged. Solving the inverse kinematics problem involves deciding which solution to choose as well.