Class Activity 1: Introducing the PincherX 100 Robot Arm and Vision Kit - madibabaiasl/kinematics-robotic-arms-modern-approach GitHub Wiki

• Identify the key hardware components of the PincherX 100 robot arm and the Vision Kit, including their roles in sensing, actuation, and communication.
• Understand how the robot interfaces with the ROS2 Humble framework and Python-ROS API for control and programming.
• Explain the mechanical structure of the PincherX 100 (its links, joints, and actuators) in terms of kinematic design.
• Recognize how smart servos, encoders, and depth cameras contribute to feedback and control in robotic systems.
• Develop practical familiarity with hardware assembly, safe operation, and setup procedures for ROS-based robot control.

By the end of this lesson, you will be able to:

• Assemble, mount, and power up the PincherX 100 robot arm and its vision kit safely and correctly.
• Use the robot’s joint limits to define safe operating conditions and avoid hardware damage.
• Annotate and label the robot’s links and joints, demonstrating understanding of its serial manipulator structure.
• Distinguish between proprioceptive (encoder) and exteroceptive (camera) sensors in the system and explain their functions.
• Describe how USB-to-TTL/RS-485 communication enables control of Dynamixel servos from a computer.
• Analyze how a depth camera compensates for the limitations of monocular vision using stereo imaging.
• Produce a well-structured technical report that includes setup documentation, annotated photos, and thoughtful reflection on the assembly and operation process.

This activity bridges theory and practice: it transforms abstract concepts from Lesson 1 (sensors, actuators, and kinematics) into a tangible, hands-on understanding. By setting up and examining the PincherX 100, you move from knowing about robots to interacting with them. This foundation is essential before diving into ROS2 programming and motion control, because understanding how data and power move through a real robot makes future software design both safer and smarter.

https://youtu.be/8Q3oiBn_P7U

For most of the projects in this class, we will use the serial robot arm, the PincherX 100, from Trossen Robotics with the vision kit for vision-based control. This robot arm is controlled by Robot Operating System (ROS), and we will use ROS2 Humble, which is the eighth release of ROS, and it is a long-term support (LTS) release, meaning that it will be updated and the bugs will be fixed until May 2027. We will use RViz as the visualization tool to visualize the state of the robot, including its position, orientation, and sensor data. Python is the preferred language, and we will use the Python-ROS API, which sits above ROS, so that even if you are not proficient with ROS, you can still control and program the robot arm.

The robot should be fastened to an 18"x24" wooden board for stability during operation. Here are the steps to do:

• Unbox the robot arm and the vision kit
• The robot arm comes pre-installed, and all you have to do is attach the gripper (note that you can always 3D print your own gripper for the specific needs of a task). Follow the instructions in the following video to do so:

How.to.install.the.gipper.mp4

How to install the gipper. Video credit: Trossen Robotics

• Make sure to take into account the joint limits when turning the robot arm, because if you turn it beyond the joint limits, you will damage it (take this into account when programming the robot as well). The joint limits for the PincherX 100 robot arm to ensure a safe range of operation are:

• Now assemble the vision kit according to the box instructions, which are straightforward. The only place that you may need help is installing the AprilTag, which is a visual fiducial (artificial feature) system. Targets can be created from an ordinary printer, while the AprilTag detection software calculates accurate 3D position, orientation, and identity of the tags in relation to the camera. Learn more about the AprilTag at the link below:

https://april.eecs.umich.edu/software/apriltag

Follow the video below to install the AprilTag (make sure that the orientation of the tag is like the video):

install.the.AprilTag.mp4

• The template for the hole layout is shown below:

pincherx100-mounting template.pdf

Then use a set of M4 PEM nuts and thumb screws or 3/4” #8 Rounded Pan Head Wood Screws to fasten the robot arm to the wooden board.

• Now it's time to power on the robot and connect it to the computer.

Warning: While the robot is powered on, exercise caution to avoid touching any cables, connectors, boards, or other electrical components onboard, as this could lead to the risk of electrical shock injury.

Our arm is now ready for ROS installation in the next class activity.

Question 1: Based on what we have learned in lesson 1, in terms of the kinematics design, what kind of robot is the PincherX 100? Explain.

Question 2: Identify the robot's links and joints. Annotate the robot’s links/joints on the real robot (include the picture).

The links of the PincherX 100 robot arm are actuated using the Dynamixel X-Series smart servos by ROBOTIS, where each smart servo has a motor, a control board, a gearbox, and an encoder that can fine-tune smooth joint motions. Learn more about smart servos at the link below:

https://youtu.be/U0v_0ZyX-SI

These servos come with a small-sized USB communication converter (it converts USB that the computer understands to serial communication TTL/RS-485 that servos understand) that enables controlling and operating the DYNAMIXEL with the computer. It has both 3-pin connectors for TTL communication and 4-pin connectors for RS-485 communication (two different methods used for data transmission in electronic systems).

Question 3: What is the communication used in the PincherX 100 and why (note that the type of communication is dependent on the servo model used, but you can see that from the connected pins)?

Photo credit: ROBOTIS

If you need more information about the U2D2 controller, refer to the website below:

https://emanual.robotis.com/docs/en/parts/interface/u2d2/

Now let's talk about the sensors. As mentioned earlier, the smart servos have embedded encoders that provide feedback on the position, velocity, and torque of the motor. This feedback is used to control the motor and to ensure that it operates within its safe operating limits.

Question 4: According to lesson 1, what kind of sensor is this encoder?

The other sensor that we will use in this course is the camera and the vision kit that comes with it. This sensor will allow us to add a computer vision component to our robot setup to perform different tasks that need that extra eye. The camera that we will use is the Intel D415 RealSense Depth Camera, which features 1920x1080 resolution at 30fps with a 65° × 40° field of view and an ideal range of 0.5m to 3m.

Question 5: According to lesson 1, what kind of sensor is this camera?

Question 6: According to lesson 1, what is the main limitation of a single camera and how do you think this camera solves it? Show with a simple diagram.

After completing this activity, each student should write and submit a short report in PDF format to this activity via Canvas. You can use the text editor of your choice to write the report (Word, Google Docs, LateX), but all reports should have the following titles and sections:

• Title, Name (5 points)
• Introduction: Briefly explain the purpose of the activity (15 points).
• Materials and Setup: Make sure to include photos of your setup (20 points).
• Answers to Embedded Questions: Make sure to include photos/diagrams when needed. There are 6 embedded questions that need to be answered (5 points each/30 points total).
• Reflection: A short reflection on any interesting observations, surprises, difficulties, new directions that can be taken and any other feedback you may have (20 points).
• References: Note that utilizing (or not utilizing) AI should be disclosed here. You can use AI tools according to the allowed instances in the Syllabus. Also, 100% AI-generated content is not allowed (10 points).

Note: This activity is eligible for "best report" points in our reward system (see the reward system sheet for the criteria).