add image to readme

README.md

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 # handeye-4dof: Handeye Calibration for 4DOF Manipulators
 
+<p align="center">
+<img src="images/scara.png" alt>
+<br>
+<em> Figure 1. Handeye calibration for 4DOF SCARA arms [1]. Left is eye-on-base and right is eye-on-hand. </em>
+</p>
+
 This package provides eye-on-hand handeye calibration for 4DOF robot manipulators using dual quaternions. This is an implementation of [1] which extended dual quaternion handeye calibration techniques [2] to 4DOF robots. Handeye calibration through dual quaternions is favorable as it allows for us to solve for translation and rotation simultaneously, thus avoiding any compounding error resultant from solving these separately.
 ## Background
 
-Robot handeye calibration is an important and well studied problem that allows us to obtain the unknown static transformation between the end effector and camera (*in eye-on-hand case*) or the robot base and camera (*in eye-on-base case*). This is done by sampling several transformations between the base and end effector (*through forward kinematics*) and camera to marker (*through marker detection methods*) which allows us to formulate the famous [**AX = XB**](https://en.wikipedia.org/wiki/Hand_eye_calibration_problem) problem where **X** is our desired static transform.
+Robot handeye calibration is an important and well studied problem that allows us to obtain the unknown static transformation between the end effector and camera (*in eye-on-hand case*) or the robot base and camera (*in eye-on-base case*). This is done by sampling several transformations between the base and end effector (*through forward kinematics*) and camera to marker (*through marker detection methods*) which allows us to formulate the [**AX = XB**](https://en.wikipedia.org/wiki/Hand_eye_calibration_problem) problem where **X** is our unknown desired static transform.
 
 Several methods exist to solve for **X** but a vast majority of these methods assume that the robot is well articulated (i.e. has 6DOF). For 4DOF robots such as SCARAs (x, y, z, yaw), conventional calibration methods are infeasible and are incapable of producing valid results. This method circumvents this problem by reducing [2] to 4DOF robots. See [1] for further details. For an introduction to dual quaternions, see [3].
 
@@ -28,6 +34,7 @@ Several methods exist to solve for **X** but a vast majority of these methods as
 ## TODO
 - Expand documentation in README
 - Add ROS capabilities.
+- Add command line interface.
 - Add post nonlinear refinement.
 - Add singular value checking.
 - Add pose selection based off of dual quaternion scalar score.