Collaborative Tracking and Capture of Aerial Object using UAVs

This work details the problem of aerial target capture using multiple UAVs. This problem is motivated from the challenge 1 of Mohammed Bin Zayed International Robotic Challenge 2020. The UAVs utilise visual feedback to autonomously detect target, approach it and capture without disturbing the vehicle which carries the target. Multi-UAV collaboration improves the efficiency of the system and increases the chance of capturing the ball robustly in short span of time. In this paper, the proposed architecture is validated through simulation in ROS-Gazebo environment and is further implemented on hardware.

Implementation of Survivor Detection Strategies Using Drones

Survivors stranded during floods tend to seek refuge on dry land. It is important to search for these survivors and help them reach safety as quickly as possible. The terrain in such situations however, is heavily damaged and restricts the movement of emergency personnel towards these survivors. Therefore, it is advantageous to utilize Unmanned Aerial Vehicles (UAVs) in cooperation with on-ground first responders to aid search and rescue efforts. In this article we demonstrate an implementation and improvement of the weight-based path planning algorithm using an off-the-shelf UAV. The coordinates of the survivor and their heading is reported by an on-ground observer to the UAV to generate a weighted map of the surroundings for exploration. Each coordinate in the map is assigned a weight which dictates the priority of exploration. These waypoints are then sorted on the basis of their weights to arrive at an ordered list for exploration by the UAV. We developed the model in MATLAB, followed by prototyping on Robot Operating System (ROS) using a 3DR Iris quadcopter. We tested the model on an off-the-shelf UAV by utilizing the MAVROS and MAVLINK capabilities of ROS. During the implementation of the algorithm on the UAV, several additional factors such as unreliable GPS signals and limited field of view which could effect the performance of the model were in effect, despite which the algorithm performed fairly well. We compared our model with conventional algorithms described in the literature, and showed that our implementation outperforms them.