ACHIEVEMENTS
ACHIEVEMENTS
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Dr. Glenn Yee Graduate Student Project Award
Chosen through a competitive, merit-based selection process for the Fall 2025 semester. This award provides financial support for special supplies, services, or equipment essential for an innovative Robotics Engineering capstone project.
Make Your Robot Tick Competition
Led the development of an autonomous robot, integrating advanced Machine Learning and Computer Vision to enhance navigation, decision-making, and energy optimization.
Engineered a rapid energy collection system with optimization algorithms, enabling efficient power transfer and surpassing competitors in performance.
Adapted to real-time challenges by making critical hardware and software upgrades, reinforcing 3D-printed terminals with wireframes and refining control algorithms for precision.
Achieved the highest score of 49 points, becoming the only team to successfully complete power delivery to the storage station, a key highlight of the event.
Demonstrated resilience and technical excellence, overcoming setbacks like hardware failures and partial energy transfers, ensuring continuous improvement across rounds to secure victory.
Learning Outcome:
Developed expertise in autonomous robotics, machine learning, and computer vision for enhanced navigation and decision-making. Strengthened skills in optimization algorithms and energy-efficient system design, improving robotic performance.
Team Member- Nilay Jadav
ROBOFEST 3.0
Designed and developed a fully operational autonomous rover, integrating angle-based speed control, intelligent GPS navigation, and PID control, receiving recognition from IIT judges for innovation.
Implemented an advanced obstacle avoidance and path-planning system, utilizing YOLO V8 with 95% accuracy for object detection, leading to a top 17 finish among 150+ teams.
Engineered and 3D-printed compact enclosures for motors using PLA, ensuring structural durability, protection, and optimized performance in demanding environments.
Integrated Ackerman Steering for enhanced maneuverability, demonstrating technical expertise, leadership, and a strong problem-solving approach throughout the competition journey.
Secured funding of ₹50,000 from GUJCOST and ₹25,000 from the university after successfully qualifying through Ideation, PoC, and Prototype rounds, advancing to the next stage with an additional ₹200,000 from GUJCOST and ₹75,000 from the university.
Learning Outcome:
Gained hands-on experience in robotic system development from ideation to prototype, securing significant funding through competitive rounds. Strengthened expertise in autonomous navigation, PID control, 3D-printing and Ackerman steering, while demonstrating innovation, leadership, and technical excellence.
Team Members- Aum Barai, Jaimin Mehta, Jainam Gandhi
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