Robust Visual-Aided Autonomous Takeoff, Tracking, and Landing of a Small UAV on a Moving Landing Platform for Life-Long Operation

The paper "Robust Visual-Aided Autonomous Takeoff, Tracking, and Landing of a Small UAV on a Moving Landing Platform for Life-Long Operation" has been published by Applied Sciences in the Special Issue on Multi-Robot Systems: Challenges, Trends and Applications.

Robot cooperation is key in Search and Rescue (SaR) tasks. Frequently, these tasks take place in complex scenarios affected by different types of disasters, so an aerial viewpoint is useful for autonomous navigation or human tele-operation. In such cases, an Unmanned Aerial Vehicle (UAV) in cooperation with an Unmanned Ground Vehicle (UGV) can provide valuable insight into the area. To carry out its work successfully, such as multi-robot system requires the autonomous takeoff, tracking, and landing of the UAV on the moving UGV. Furthermore, it needs to be robust and capable of life-long operation. In this paper, we present an autonomous system that enables a UAV to take off autonomously from a moving landing platform, locate it using visual cues, follow it, and robustly land on it. The system relies on a finite state machine, which together with a novel re-localization module allows the system to operate robustly for extended periods of time and to recover from potential failed landing maneuvers. Two approaches for tracking and landing are developed, implemented, and tested. The first variant is based on a novel height-adaptive PID controller that uses the current position of the landing platform as the target. The second one combines this height-adaptive PID controller with a Kalman filter in order to predict the future positions of the platform and provide them as input to the PID controller. This facilitates tracking and, mainly, landing. Both the system as a whole and the re-localization module in particular have been tested extensively in a simulated environment (Gazebo). We also present a qualitative evaluation of the system on the real robotic platforms, demonstrating that our system can also be deployed on real robotic platforms. For the benefit of the community, we make our software open source.

I would like to thank Pablo R. Palafox, Mario Garzón and João Valente to give me the opportunity to collaborate with them and get this publication.

P.R. Palafox, M. Garzón, J. Valente, J.J. Roldán and A. Barrientos. Robust Visual-Aided Autonomous Takeoff, Tracking and Landing of a small UAV on a Moving Landing Platform for Life-Long Operation. Applied Sciences, 9 (13), 2661, 2019. Impact Factor (2018): 2.217, Q2. Article

SUREVEG Project: Developing robots for strip-cropping systems

The SUREVEG project proposes the development and application of new organic cropping systems using strip-cropping and fertility strategies to improve resilience, system sustainability, local nutrient recycling and soil carbon storage. The project has three main goals: 1) Designing and testing strip-cropping systems in vegetable producing countries at different geographical locations in Europe, 2) Developing and testing soil-improvers and fertilizers based on pre-treated organic plant residues, and 3) Developing and testing smart technologies for management of strip-cropping systems.

The Technical University of Madrid and the Centre for Automation and Robotics are involved in the third goal: Smart machinery for strip-cropping systems. This work aims at developing a robotic tool for the automation of field operations in strip-cropping systems, including the adequate sensors to collect valuable data and actuators to apply precise fertilization. Specifically, it comprises four goals: 1) Designing a multi-purpose robotic tool, 2) Developing sensing systems and algorithms, 3) Developing an actuation system, and 4) Implementing motion planning strategies.

Here you can see the first prototype (I have worked on the manipulator robot):