Conclusion

Team Four created a functional robot capable of modeling a pitching wedge impacting a golf ball. Scaling the model to impact a ping pong ball, the team used a triple crank Watt's mechanism to provide a "pause" and "flicking" motion onto the ball. The team faced challenges when adapting the mechanism design to ensure ground linkages didn't conflict with other joints, creating an optimized end effector, and analyzing a six-bar mechanism. Ultimately, the final prototype was successful. We accomplished our goal of modeling the velocity profile of a human swing, while also imparting an inclined velocity to the ball. All lessons learned, future work and tips for future teams are outlined below.

Lessons Learned

1. 2D designs of the mechanism do not illustrate the many required planes of motion for the links. When we first started planning out the mechanism by looking at YouTube videos and MotionGen, we initially did not foresee the many challenges associated with transforming a 2D design into a 3D design. Some of these challenges include joint collisions, positioning of grounds, and play between the links. Moving forward, it is important to consider the multiple planes of motion involved in a 2D design and use low-cost, quick iterations to diagnose issues before proceeding with a complete prototype.
2. 3D Prints have significant wear and tear throughout repeated use. In our case, replacing bearings in the 3D prints and repeated use led to weathering of the mounts, ultimately increasing play within the mechanism. 
3. Using tolerancing test cuts for laser-cut components saves time and cost. While cutting our links, we needed the press-fit holes to have tight tolerances. Repeatedly cutting the links until the press fit was appropriate was a waste of time and material. Instead, it is more efficient to cut out a "test piece," with many holes of incrementally different sizes. Use this to determine the appropriate dimension for press-fit components.

Future Work

Although the team was successful in completing the required scope of the project, improvements can be made if another team were to take this project on in the future. 

1. Creating a button capable of running the motor for a single revolution. This would make it easier to place the ball and shoot consistently. Along the same line, calibrating different speeds for different distance shots would be advantageous for adding complexity to this project.
2. To scale the model for a real golf ball, adaptations would need to be made to the motor torque or the size of the mechanism as a whole. Doing so would enable the mechanism to launch the mass of a golf ball instead of a ping-pong ball. We could also adapt the end effector to resemble golf clubs closer or have more end-effector iterations. 
3. Creating better fits for the bearings or using higher-quality bearings or d-shafts would help keep the ground joints from sliding. This would improve the amount of play in the system and help constrain the model to a true 1 DOF system.
4. The kinematic analysis could also be fully debugged to show the accurate depiction of our physical prototype, and we could further the analysis by analyzing the acceleration and mechanical advantage of our end effector point. 

Tips for Future Teams

1. Scope out the idea fully before beginning the design process and understand all underlying tasks and complexities. Team 4 initially set out to create a soccer "corner kick" robot, but through the design process it was hard to replicate the "spin" imparted onto the ball. Luckily, the team was able to pivot to a golf model, but if a future team's mechanism is too niche, it may be difficult to pivot. We found golf to be a great area to narrow the scope of the project since we had many options for adding complexity to the project like calibration, aiming for a ball height, or playing around with the coupler motion. 
2. A six-bar mechanism may be fun to explore, but it proved time-consuming and difficult for the analysis team. If a future undergraduate group is considering a six-bar mechanism, strong programming and a good base in numerical methods are key skills expected from the analysis team.

Acknowledgments

The team would like to thank the teaching team for this class - Dr. Meredith Symmank and TA's Connor Hennig & Aayush Parikh. Team 4 also extends immense gratitude towards the Texas InventionWorks Staff for their guidance in the manufacturing process and off-hour facilities. Additionally, the team expresses a warm thanks to the previous teams for this class as it provided many references and points of inspiration for the context of this project.