Drone swarm interaction
Recent advancements in technology have made it feasible to deploy multiple flying drones that can be controlled in swarms by a single operator. This innovative approach to drone management opens up new possibilities for applications ranging from surveillance to emergency response. In collaboration with scientists from the University of Oslo (UiO) who specialize in drone swarm deployment, this project aims to tackle the unique challenges associated with controlling drone swarms.
The essence of this project is to develop new interaction models for both planning and executing operations involving drone swarms. The focus will be on a design case linked to an upcoming research project, where swarms of smaller drones are employed to aid emergency search missions. These drones, equipped with sensors, will have the capability to swiftly cover large areas and remotely detect the pulse and breathing of disaster victims, providing crucial information to rescue teams.
This project will let you design of control systems for such drone swarms, considering both onsite and remote operation setups. The primary goals will include:
- Researching current methods and technologies in drone swarm control to identify potential improvements and innovations.
- Conducting user research to understand the specific needs, challenges, and preferences of operators controlling drone swarms, especially in high-pressure situations like emergency search missions.
- Developing and prototyping new interaction models that can enhance the efficiency and effectiveness of swarm control, making it more intuitive and responsive.
- Conducting user testing to refine the control models based on real-world feedback, ensuring they are practical and meet the demands of emergency response scenarios.
This project presents a unique opportunity to contribute to the evolving field of drone technology, particularly in enhancing the capabilities and applications of drone swarms. By designing innovative control systems, you will play a crucial role in supporting emergency search missions, potentially saving lives and making emergency responses more efficient.
