An Aerial Robotic Framework to address Area Coverage in Precision Agriculture Practices

Abstract

In recent years, precision agriculture (PA) researchers have found that the use of unmanned aerial vehicles (UAV) could significantly improve agricultural sciences research. Their motivation was conceived by its availability, simple assemblage and maintenance, as well as its low cost compared with traditional tools (e.g. Satellites, manned aircrafts). For this reason, significant efforts are being made to use a new generation of mini unmanned aerial vehicles (UAV) applied to remote sensing (RS). In order to obtain a collection of images from an agricultural site, an UAV must perform a discrete smooth trajectory that covers all area of interest. The problem to coverage an entire area subjected by constraints from the platform itself and workspace is known by the coverage path planning (CPP) problem. Albeit many efforts have been done in the past to address this problem in the context of autonomous ground vehicles (UGV), very few have been extended to UAVs. This thesis therefore, aims to give a step forward in this research direction. The main contributions are summarized in a comprehensive study of the CPP problem applied to mini UAVs capable of vertical take off and landing (VTOL). This study covers single robotic systems (SRS) and multi robotic systems (MRS). The solutions provided rely in the combination of heuristic and non heuristic algorithms to allow an easy replication of the findings. To achieve this, the robots workspace were decomposed through an approximate cellular decomposition of the workspace and manipulated through computer graphics algorithms. Finally, The developments mentioned above are translated into a full developed aerial framework endowed with tools which facilitates the real time evaluation and execution of missions in farming sites. The proposed approaches have been validated computationally as well as in real agricultural lands where several aerial surveys have been performed. The mini UAV employed are denoted as quad-rotor, which are rotary wings aircrafts capable of vertical take off and landing. To date this work is one of the firsts, if not the first to put in practice coverage path planning strategies employing mini UAVs in the precision agriculture context. Should be highlight that the present thesis have been developed under the project RHEA: Robot Fleets for Highly Effective Agriculture and Forestry Management (CP-IP 245986-2 RHEA) approved by the European Union in 2010, and the project ROBOCITY 2030 sponsored by the Community of Madrid (S-0505/DPI/000235).