Autonomous Navigation for Small UAV in Indoor GPS-denied Environments

With the evolution of unmanned aerial vehicles (UAVs) in recent years, more and more researchers are setting their sights on the application research of the indoor environment. Indoor applications include industrial facility inspection, warehouse inventory management, health sector, search, and rescue, among others. However, the use of UAVs in these applications requires continuous high-accuracy positioning and pose information and the consequent efficient obstacle avoidance algorithm. To address the above problem, we want to design an algorithm that can:
1. Perceive the surrounding environment.
2. Control attitude and position of UAVs.
3. Navigate UAV through obstacles.
4. Account for the changes in the dynamic environment and remain stable.

Faculty Supervisor:

Igor Gilitschenski

Student:

Partner:

SOTI Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Toronto

Program: