Optimized Task Allocation on Drones for Survey and Rescue in Disaster-Stricken Areas
Optimized Task Allocation on Drones for Survey and Rescue in Disaster-Stricken Areas
The eYantra Robotics Competition is a prestigious six-month event requiring teamwork, technical expertise, and innovative problem-solving. As part of a four-member team, our theme was Survey and Rescue, where we developed a pre-emptive scheduling algorithm for a drone to aid individuals affected by natural disasters.
The eYantra Robotics Competition is a prestigious six-month event requiring teamwork, technical expertise, and innovative problem-solving. As part of a four-member team, our theme was Survey and Rescue, where we developed a pre-emptive scheduling algorithm for a drone to aid individuals affected by natural disasters.
Category
May 15, 2024
Aerial Robotics
Aerial Robotics
Purpose
May 15, 2024
Competition
Competition
Affiliation
May 15, 2024
Gujarat Technological University
Gujarat Technological University
Year
May 15, 2024
2019
2019
Task 1.1 :
Implemented position hold for the drone at a specific point [2, 2, 20] using a PID control algorithm in simulation.
Task 1.2 :
Programming waypoint navigation for the drone to traverse a set of 3D coordinates using the PID controller. Waypoints are in the form (x, y, z).
After completing simulations, we transitioned to physical hardware, where we integrated an overhead camera, an RGB LED as a beacon, and a WayCon Marker for drone localization after camera calibration.
In the final task, we tackled dynamic challenges involving three priority-based services:
Red (Rescue) - Highest priority, requiring the drone to return to the homing position after service.
Blue (Medicine) - Medium priority.
Green (Food) - Lowest priority.
To succeed, we fine-tuned the PID algorithm for the physical drone and developed a pre-emptive scheduling algorithm to manage tasks effectively.
Despite unforeseen challenges—such as losing half of our team midway through the competition—we persevered and secured 6th place nationwide. This project provided my first comprehensive experience with ROS, taught me resilience under pressure, and reinforced the value of teamwork. I remain deeply grateful to eYantra and Prof. Kavi Arya for this incredible learning opportunity.
Task 1.1 :
Implemented position hold for the drone at a specific point [2, 2, 20] using a PID control algorithm in simulation.
Task 1.2 :
Programming waypoint navigation for the drone to traverse a set of 3D coordinates using the PID controller. Waypoints are in the form (x, y, z).
After completing simulations, we transitioned to physical hardware, where we integrated an overhead camera, an RGB LED as a beacon, and a WayCon Marker for drone localization after camera calibration.
In the final task, we tackled dynamic challenges involving three priority-based services:
Red (Rescue) - Highest priority, requiring the drone to return to the homing position after service.
Blue (Medicine) - Medium priority.
Green (Food) - Lowest priority.
To succeed, we fine-tuned the PID algorithm for the physical drone and developed a pre-emptive scheduling algorithm to manage tasks effectively.
Despite unforeseen challenges—such as losing half of our team midway through the competition—we persevered and secured 6th place nationwide. This project provided my first comprehensive experience with ROS, taught me resilience under pressure, and reinforced the value of teamwork. I remain deeply grateful to eYantra and Prof. Kavi Arya for this incredible learning opportunity.
Task 1.1 :
Implemented position hold for the drone at a specific point [2, 2, 20] using a PID control algorithm in simulation.
Task 1.2 :
Programming waypoint navigation for the drone to traverse a set of 3D coordinates using the PID controller. Waypoints are in the form (x, y, z).
After completing simulations, we transitioned to physical hardware, where we integrated an overhead camera, an RGB LED as a beacon, and a WayCon Marker for drone localization after camera calibration.
In the final task, we tackled dynamic challenges involving three priority-based services:
Red (Rescue) - Highest priority, requiring the drone to return to the homing position after service.
Blue (Medicine) - Medium priority.
Green (Food) - Lowest priority.
To succeed, we fine-tuned the PID algorithm for the physical drone and developed a pre-emptive scheduling algorithm to manage tasks effectively.
Despite unforeseen challenges—such as losing half of our team midway through the competition—we persevered and secured 6th place nationwide. This project provided my first comprehensive experience with ROS, taught me resilience under pressure, and reinforced the value of teamwork. I remain deeply grateful to eYantra and Prof. Kavi Arya for this incredible learning opportunity.
