CATALYST Research Project 2024

2024 Project: Disaster Response Robots

Lead Faculty: Sanjiban Choudhury
Department: Computer Science, Cornell Bower CIS

Project Description

The 2024 CATALYST Scholars will explore the field of robotics and AI through a practical, engaging, and socially relevant project that integrates aspects of engineering, coding, and critical problem-solving. The central theme revolves around a simulated search and rescue operation in a disaster zone, where students will get hands-on experience with building, programming, and deploying a robotic car using Vex Robotics kits. This project will introduce students to fundamental concepts in robotics and AI, culminating in a competition where each team’s robot attempts to rescue the most survivors in the least amount of time.

Key Learning Objectives

  1. Robotics and AI Fundamentals: Understand the core components of robotics and AI, such as perception and decision-making.
  2. Programming Skills: Gain basic proficiency in coding to control robots.
  3. Algorithmic Problem Solving: Develop strategies for effective search and rescue operations in a grid-based setup, focusing on algorithmic thinking and efficient decision-making.
  4. Collaborative Engineering: Enhance teamwork skills which are crucial for the design, construction, and iterative refinement of robotic solutions.
  5. Social Impact Awareness: Cultivate an understanding of how robotics can play a significant role in humanitarian efforts, particularly in disaster relief scenarios.

Hands-On Activities

  1. Robot Assembly: Begin with the mechanical assembly and electronics for the robot.
  2. Programming: Learn the basics of coding to control movement, and explore loops, functions, and conditional logic.
  3. Sensor Integration: Learn how to use sensors to detect simulated survivors.
  4. Search Algorithm Development: Design and implement algorithms for efficient navigation and rescue within the grid.
  5. Trial Missions: Conduct simulated rescue operations to iteratively test and improve robot performance.
  6. Final Challenge: Compete in a timed rescue mission, demonstrating the culmination of skills learned and teamwork achieved.



Faculty Lead Bio:


Sanjiban Choudhury is an Assistant Professor in the Department of Computer Science at Cornell University and a Research Scientist at Aurora Innovation. He leads the Portal group at Cornell to build everyday robots for everyday users. To this end, his research focuses on imitation learning, decision making and human-robot interaction. He did his Ph.D. in Robotics from Carnegie Mellon University and was a Postdoctoral fellow at the University of Washington. His research has received best paper awards at ICAPS 2019, AHS 2014, finalist for IJRR 2018, and winner of the 2018 Howard Hughes award. He is a Siebel Scholar, class of 2013.


Previous Projects

Information about projects from previous years can be found below: