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Visual Control

A System for the Design and Development of Vision-based Multi-robot Quadrotor Swarms

We present a cost-effective framework for the prototyping of vision-based quadrotor multi-robot systems, which core characteristics are: modularity, compatibility with different platforms and being flight-proven. The framework is fully operative and was demonstrated with the participation in the 2013 International Micro Air Vehicle Indoor Flight Competition (Toulouse, France) where it was awarded with the First Prize in the Indoors Autonomy Challenge.

We present a cost-effective framework for the prototyping of vision-based quadrotor multi-robot systems, which core characteristics are: modularity, compatibility with different platforms and being flight-proven. The framework is fully operative and was demonstrated with the participation in the 2013 International Micro Air Vehicle Indoor Flight Competition (Toulouse, France) where it was awarded with the First Prize in the Indoors Autonomy Challenge.

A Vision-based Quadrotor Swarm for the participation in the 2013 International Micro Air Vehicle Competition (Toulouse, France)

We present a completely autonomous solution to participate in the 2013 International Micro Air Vehicle Indoor Flight Competition (IMAV2013). Our proposal is a modular multi-robot swarm architecture, based on the Robot Operating System (ROS) software framework, where the only information shared among swarm agents is each robot's position. In order to present a completely visual-based solution the localization problem is simplified by the usage of visual markers.

We present a completely autonomous solution to participate in the 2013 International Micro Air Vehicle Indoor Flight Competition (IMAV2013). Our proposal is a modular multi-robot swarm architecture, based on the Robot Operating System (ROS) software framework, where the only information shared among swarm agents is each robot's position. In order to present a completely visual-based solution the localization problem is simplified by the usage of visual markers.

Vision based GPS-denied Object Tracking and Following for Unmanned Aerial Vehicles

This paper presents a robotic system that performs visual based object tracking and following using a GPS-denied Unmanned Aerial Vehicle. The robot tracks and follows a user specified object keeping a constant distance to the target. During object following, our solution requires only forward-facing camera images and IMU data. When the target tracking is lost the system starts to hover and waits for an autonomous second target detection, additionally utilizing odometry measurements for self stabilization.