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             1D CNN, resulting in state-of-the-art 99\% accuracy while limiting false positives. I also looked into signal processing 
             within my FTC robotics team, realizing that IMU data could be used to improve odometry and localization. I implemented a 
             custom Kalman filter to fuse IMU data with wheel encoder reading, significantly reducing drift during autonomous navigation 
-            and reducing error buildup over time. }
+            and reducing error buildup over time. 
+            My second major interest has been in the field of Robotics, springing from a lucky acceptance into my 
+            Middle School's robotics team in 6th grade. Due to COVID-19, out team had to start from scratch, and as a 
+            completely inexperienced 7th grader, it took me 7 months to simply learn to spin a motor. The same fascination 
+            I had with computers was now being applied to physical hardware, and I have been a loyal participant in 
+            the First Tech Challenge (FTC) robotics competition. As the software lead of my globally ranked team,
+            Technical Turbulence FTC, I have learned a lot about the algorithms that empower robots during the 
+            30-second autonomous period of the competition. Today, I am intrigued by two major research questions within 
+            the field of autonomous motion planning. First, I wonder how multiple autonomous agents can effectively
+            coordinate in real-time to achieve a common goal while avoiding collisions. This question fascinates me
+            because it combines elements of path planning, communication protocols, and decision-making under uncertainty.
+            Secondly, I am fascinated by the question of whether autonomous robots and vehicles can learn optimal paths from 
+            experience rather than relying on pre-programmed maps. This idea of reinforcement learning for motion planning 
+            excites me because it provides a pathway for devices to improve performance over time in dynamic environments.
+            My experience with robotics has provided me with a strong foundation to tackle these questions, as I have 
+            designed and implemented a custom pathing algorithm for my FTC robot. The motion profiling algorithm I developed 
+            uses cubic and quintic splines to generate smooth trajectories between points, using inverse kinematics and a PID 
+            controller to accurate follow the path. By prioritizing endpoint accuracy over time and path accuracy, our robot's 
+            pathing is extermely precise, resulting in a top-30 autonomous ranking globally. Outside FTC, I worked on a passion 
+            project to allow for pathing of two vaccuum robots in a shared environment. Using A* for initial pathfinding and
+            a custom potential fields algorithm for real-time obstacle avoidance, I made a software system that allowed 
+            for efficient cleaning of a dynamic space.}