My Team
For the past 9 years, I have been a part of the FM493RS Robotics Team. As Team Captain and Build Lead, I led robot design and programming efforts, bringing our team to a top 20 statewide rank across three seasons. Outside of competition, I shared my love of robotics through workshops, classroom sessions, and tournaments across the sacramento area, reaching over 1000 students underrepresented in STEM.
Video Showcase
To automatically detect the image on the cone for parking, the robot uses a machine learning model trained on a variety of images to determine which zone it should park in at the end of the run. To navigate precisely, I extended the navigation algorithm showcased in the Ultimate Goal Auto-Align video. Once the robot gets moving, it deposits the preloaded cone, with which the custom made passive cone deposit shows its strength: simply by moving up and down, the robot can deposit cones. The horizontal extension is similarly quick, with the claw on the end serving as the star of the show. By orienting itself in a precise manner, it can pick up a cone from the stack without unbalancing the rest of it, and quickly reorient the cone to transfer it to the deposit tool. This involved multiple servos, as well as a cross-thread time signaling system to be implemented in the software to enable the retrieval and deposit mechanisms to sync up.
2022-2023: Powerplay
These images detail my contributions to my team, for the Powerplay Robotics Competition, in which the robot had to grab cones off the ground and score them on a variety of vertical poles. To achieve this, I implemented a two way slide system with claw intake and automatic cone deposit. Inspired by the range of motion of a CNC machine, I designed the five axis claw on the end to rotate in multiple dimensions to pick up cones and reorient them for deposit. To increase the range of our intake, I decided to incorporate a horizontal slide system. This would move the claw out horizontally by up to 1.2 meters, enabling it to pick up cones and score them without any robot movement at all. To further minimize time taken when orienting the robot for deposit, I designed an automatic passive cone deposit system. After cones were placed onto the surface, it could simply rise and fall, depositing the cones without need for adjustment.
Video Showcase
The objective of the robot is to pick up rings around the field and shoot them into the target box. To reduce time spent realigning and navigating back to the shoot point, I decided to automate this procedure through a comprehensive navigation system. The first part of this system is for the robot to know where it is, a challenge called localization. This was my first time developing localization software, and since the robot is a ground navigating robot, I decided to implement a 3 wheel odometry system. By tracking the revolution of each wheel (oriented at different angles), it was possible to calculate the exact position and heading of the robot. The next step was rapid navigation. After experimenting to determine the maximum linear and angular accelerations of the robot, I implemented a spline based motion planning algorithm inspired by the dynamical systems course I had taken online earlier.
2020-2021: Ultimate Goal
These were my major contributions to my robotics team for the Ultimate Goal Season of picking up foam rings randomly tossed onto the field and launching them into goals at varying heights. I designed the entire robot in CAD, and optimized the BOM. The first system that I designed was a ground intake. Using two sets of wheels (like a vacuum), the robot could drive over rings and feed along. From there, wheels would push the rings into the shooting system, which had a range of 3 meters thanks to two wheels spinning at 6000 RPM. To keep the rings on target, I used wheels of different sizes to induce spin into the ring when launched (like a frisbee). I also implemented a custom built claw system to pick up and carry a heavy wobble goal deposited onto the field. By orienting the goal appropriately and slightly releasing the claw, the robot led the wobble goal into a piece of C-Channel, leaving the core mechanisms of the robot unobscured.
