Team Status Report for 10/3/2026

For the week of September 27th – October 3rd, our team made significant progress toward finalizing the Iteration 1 design of our 6-DOF robotic arm. Our main focus was completing the mechanical design, validating the robot through simulation and torque analysis, finalizing the hardware parts list, and preparing for physical implementation when our ordered parts begin arriving.

A major area of progress was remodeling our robot around the dimensions and geometry of the UR3e model from last week. We used the UR3e’s dimensions as a reference for our own kinematic model, allowing us to use a proven robot configuration while adapting the design to our 3D-printed links and selected smart bus servos. The updated SolidWorks assembly now contains modeled representations of the purchased smart bus serial servos, power supply, shafts, and other components. The end effector was also modified to support a pen for our intended testing.

We also performed several simulations to validate the updated design. FEA stress testing was used to identify and strengthen weak areas of the printed components, while MuJoCo was used to visualize the robot and verify its motion and geometry with the SolidWorks assembly. Simultaneously, Python kinematic and torque analysis tools were used to evaluate loads at every robot joint and confirm that the purchased servos can support the weight of the robot arm. The results of these showed that the shoulder and elbow joints are near the practical limits of our selected servos at the full UR3e dimensions. To address this, the current design uses two servos at each of these joints, along with a reduction mechanism and counterbalance spring to reduce the load and side forces on the servos.

On the software side, we continued developing our ROS2 environment on the Jetson and established the project’s GitHub repository and initial software structure. We also determined that OpenCV AprilTag detection is a better fit for our vision system than using a YOLO26 model, since AprilTags can be detected directly (using the apriltags OpenCV library) without training an object detection model. This should provide a simpler and more efficient solution for our Jetson Orin Nano and Intel RealSense D455 camera setup.

Finally, we worked together to finalize the Iteration 1 master parts list and identify remaining hardware such as bearings, screws, shafts, tubing, and additional filament. With the mechanical design and simulations largely complete, our primary risk is now transitioning successfully into fabrication and assembly. The first print runs are expected to require approximately 35 hours and 900 g of filament, so we will need to carefully prioritize the initial parts and quickly iterate on any components that require redesign.

Our project is slightly behind the original schedule since the CAD design and subsequent validation took more time than anticipated. Therefore, we have had to push back most of our schedule by about a week, so printing and assembly will commence this following week.

For next week, our team plans to:

  • Begin printing the finalized Iteration 1 components, starting with the base.
  • Measure and test initial prints before committing to the full build.
  • Order any remaining hardware and additional filament required for assembly.
  • Begin assembling the printed components and servos as parts become available.
  • Continue developing the ROS2 framework, including the URDF and tf2 structure.
  • Begin prototyping AprilTag tracking using the Jetson and RealSense camera.

Team Status Report for 9/26/26

Team Status Report

For the week of September 20th–26th, we worked on bringing up the embedded software platform, grounding the mechanical design in a reputable six-axis reference model, refining the Iteration 1 parts list, and preparing the CAD and presentation materials needed for the next stage of the project.

Project Risks & Management Strategies

The biggest risk was figuring out the structural requirements of our manually inferred dimensions on our previous CAD model, as we didn’t have a good basis to figure out if the links would sustain the weight of the joints.

We are managing this risk by comparing our measurements now against Universal Robots’ UR3e, and we aim to calculate the joint torques using the selected components’ estimated masses, and prepare some comprehensive SolidWorks motion and load simulations before printing the final links for this iteration.

Another risk we’ve identified is the integration between the CAD model, ROS2 coordinates, computer vision, and the physical arm. We are attempting to reduce that risk through developing the Jetson software environment early; this week, we’ve already set it up and ran it, and we’re collaborating on defining the CAD workspace and joint constraints before we print the pieces.

System Design Changes

We chose to use the UR3e as reference for dimensions and kinematics, instead of deriving all link lengths and joint placements from scratch which would require continuous testing, and this mechanical specs can get a bit complicated when isn’t the primary expertise or focus of our group. We imported the UR3e STEP model into SolidWorks and recorded its links, joint placement, proportions, and reachable workspace.

We also set up and installed the OS on our NVIDIA Jetson Orin Nano with JetPack 7 Ubuntu and ROS2. This would give us a physical development platform for testing ROS2 nodes and preparing the coordinate-frame and motion-planning architecture before we assemble the complete arm, so we could allow time extra time for adapting the reference links and joints and configuring the Jetson.

Project Schedule Status

The project remains mostly on schedule. The Jetson environment, initial ROS2 publisher/subscriber test, UR3e reference-model import, early test printing, and preliminary CAD work were completed this week. The Iteration 1 CAD, joint-limit definition, surface modeling, and torque/workspace analysis are scheduled through October 3rd and remain in progress. The parts list and the remaining calculations need to be finalized promptly so that the team can place the hardware order and begin manufacturing without consuming the integration buffer later in the semester.

Team Progress & Highlights

The team successfully configured the Jetson Orin Nano from scratch, installed JetPack 7 Ubuntu and ROS2, and verified the environment with ROS2 publisher and subscriber nodes running simultaneously. We also established an initial 3D-printing environment and completed some basic test prints to estimate manufacturing time and evaluate print settings.

Week-Specific Considerations

Part A: Public Health, Safety, and Welfare
Written by Bryan Hong

When it comes to public health, safety, and welfare, our project may not appear at first glance to directly impact any of the three. However, by placing the means of production into the hands of the artist, we have helped the latter avoid employing the services of a third-party manufacturing company that may rely on unethical labor practices and/or unsafe working conditions. By enabling artists and creators to reproduce their work in-house, our system reduces the reliance on these morally-questionable third party manufacturers, and thus indirectly improves global health, safety, and welfare, ensuring that the physical manifestation of art does not come at the cost of others’ health.

Part B: Social Factors
Written by Aaron Tang

Our robot arm is intended to be used primarily by digital artists, students, and researchers who want to transform a digital line drawing into a physical drawing on curved surfaces.

In order to make this design accessible for social and educational settings, our 1. web interface shouldn’t require experience with robotics, CAD, or any sort of electrical/software engineering. Users should be able to submit a drawing on our interface, select a marker color, and follow the robot’s status and receive clear feedback.

This would make the system valuable for classroom demonstrations and creative environments where artists who don’t have engineering backgrounds can safely and easily reproduce their art. It would also take into consideration people who have difficulty drawing manually on large, elevated, or unusually positioned surfaces.

We have also considered some concerns that robotic drawing tools could replace human creativity. Our goal is to create a tool to assist artists, not replace them: the user should ultimately still be responsible for their own artwork and creative decisions, while the robot simply transfers that work exactly stroke by stroke to a physical surface. The system should also respect ownership and consent by reproducing only artwork that artists consent to, and keeping submitted drawings under the user’s control.

Part C: Economic Factors
Written by Jonathan Waller

Our 6DOF drawing robot addresses economic factors in production and consumption by providing a low-cost, accessible alternative to expensive industrial machinery. By utilizing standard off-the-shelf smart servos, 3D-printed structural components, and open-source software, our design significantly reduces the bill of materials. This allows the 6DOF arm to be affordable relative to its capabilities. The system was designed with independent creators and digital artists in mind, allowing them to produce small batches of custom physical works directly from their digital art. Instead of relying on costly third-party manufacturing services or full-scale assembly lines, artists can preserve their preferred digital workflow, fine-tune their designs locally, and economically handle low-volume production without a heavy financial investment.

Team Status Report for 9/19/26

Team Status Report

For this week, our team focused on defining the master project timeline, evaluating key system risks, and refining our initial mechanical and electrical hardware architectures.

Project Risks & Management Strategies

Our team identified three primary technical risks that could jeopardize project success and established corresponding management strategies. First, structural deflection in our 3D-printed links under joint motor loads could degrade drawing accuracy. We are running SolidWorks stress and torque simulations on Iteration 1 link geometries prior to printing, with a contingency plan to insert internal aluminum reinforcement rods or increase print wall thickness if excessive flex occurs. Second, dynamic surface geometries could push the arm past its physical reach or into joint singularities. We defined a strict 0.4m *0.4m * 0.4m target workspace and designed our path planner to bound trajectories, utilizing an adjustable mounting base to reposition targets as needed. Finally, subsystem integration between ROS2, microcontrollers, vision tracking, and physical hardware presents a late-stage bottleneck, so we proactively restructured our timeline to include dedicated integration buffer weeks.

System Design Changes

We updated our system block diagram this week to replace traditional stepper motors with smart serial bus servo motors for primary joint actuation. Smart servos provide built-in position feedback controllers and support daisy-chain communication, which drastically reduces physical wire runs and bulk throughout the 6DOF arm structure. While smart servos carry a slightly higher unit cost than bare steppers, they eliminate the need to purchase separate motor driver breakout boards for each joint and significantly reduce wire harness assembly time, keeping overall project costs and risks on track.

Project Schedule Status

The team completed a comprehensive review and revamp of our master schedule this week. We explicitly incorporated dedicated buffer space for system integration and physical hardware debugging toward the end of the term. With these adjustments in place, our overall project progress remains on schedule relative to our updated roadmap.

Team Progress & Highlights

On the design front, the team held a design review forum to critique our preliminary Iteration 1 SolidWorks draft, successfully identifying key structural constraints around shoulder torque distribution, arm reach, and 3D printing clearances. Additionally, we designed a universal object target mounting base equipped with AprilTags. This mounting base allows dynamic target surfaces—such as cups, curved plates, or flat planes—to be secured firmly in the workspace while providing a clear coordinate frame for the vision system to detect relative to the robot base.

Initial team sketches for helping the robot identify the base and object with AprilTags
1. Initial team sketches for helping the robot identify the base and object with AprilTags

  1. Iteration 1 SolidWorks CAD draft overview showing initial joint and enclosure layout
  2. AprilTag object target mounting base design diagram