Obstacle detection and collision avoidance for multi-rotor UAV
Position - Senior Engineer – State Estimation and Control at Technology Innovation Hub for IoT and IoE (TIH-IoT), IIT-Bombay
Technical skills - Python, Robot operating system (ROS), MAVROS, SITL (Ardupilot + Gazebo)
Drones are actively used in precision agriculture with one of its major applications of spraying pesticides, herbicides, fertilizers, etc. in the agricultural field. The aim of this project is to develop a reliable sense and avoid technology to make UAV-based spraying completely autonomous.
The major challenge in achieving autonomy is the requirement of flying low in an agricultural environment with lots of obstacles like trees, poles, cables, etc.
As a senior engineer at TIH, IIT-Bombay, I led a team of engineers for the development of a robust obstacle detection and avoidance suite capable of navigating through common obstacles in the agricultural field. The figure below displays the functioning of our sense and avoid technology.
In collaboration with General Aeronautics (GA), Bangalore, we tested our technology on different scenarios.
- Trees of different shapes and sizes,
- Detection and avoidance at different heights,
- Detection and avoidance for multiple obstacles.
We have successfully tested our implementation in the presence of dust and high winds. Currently, we are working towards modifying the avoidance algorithm to maximize spraying in the marked area in the agricultural field.