Sensor planning for a symbiotic UAV and UGV system for precision agriculture

Abstract

Abstract-We study the problem of coordinating an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) for a precision agriculture application. In this application, the ground and aerial measurements are used for estimating nitrogen (N) levels on-demand across a farm. Our goal is to estimate the N map over a field and classify each point based on N deficiency levels. These estimates in turn guide fertilizer application. Applying the right amount of fertilizer at the right time can drastically reduce fertilizer usage.Towards building such a system, this paper makes the following contributions: First, we present a method to identify points whose probability of being misclassified is above a threshold. Second, we study the problem of maximizing the number of such points visited by an UAV subject to its energy budget. The novelty of our formulation is the capability of the UGV to mule the UAV to deployment points. This allows the system to conserve the short battery life of a typical UAV. Third, we introduce a new path planning problem in which the UGV must take a measurement within a disk centered at each point visited by the UAV. The goal is to minimize the total time spent in traveling and measuring. For both problems, we present constant-factor approximation algorithms. Finally, we demonstrate the utility of our system with simulations which use manually collected soil measurements from the field.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

“…Requirements for minimum and maximum flight angles of fixed‐wing drones should be taken into account during landings and takeoffs . Some optimization problems introduce constant setup‐time parameters for each landing and takeoff . In photography applications, certain terrain types, such as mountains or trees, may require a specific angle of flight in order to optimally position the camera . Limited payload .…”

“…The trade‐off between energy consumption and flying altitude is especially important in surveillance applications: a higher flying altitude enables observation of a larger area at the cost of higher energy consumption . The limited capacity of the energy unit is usually modeled as maximal operation time , maximal flying distance , or the limited number of addresses a drone can visit during one flight . Emerging technologies, such as thin film photovoltaic panels, enable so‐called energy harvesting: Small drones may recharge their batteries during flight in the sunlight .…”

Comparison of Vegetation Indices From Rpas and Sentinel-2 Imagery for Detecting Permanent Pastures

“…2.2.1 NDVI: is the well-known normalized ratio between red (R) and near infrared (NIR) (Rouse et al 1973) and it is one of the most used vegetation indices (Baluja et al 2012, Bendig et al 2015, Diaz-Varela et al 2014, Herwitz et al, 2004, Pérez-Ortiz et al 2015, Sugiura et al 2005, Tokekar et al 2013, Torres-Sánchez et al 2015, Tucker 1979, Turner et al 2010 ). The formula is the following:…”

Radiation search operations using scene understanding with autonomous UAV and UGV

“…Some examples of the applications of these unmanned systems are search and rescue operations, post‐disaster surveying, target localization and tracking, and precision agriculture monitoring. Previous works have focused on the collaboration between multiple UAV, multiple UGV, the collaboration between UAV and UGV, and much more. Garzon et al.…”

“…For the topic of UAV‐UGV collaboration, Tokekar et al. studied the problem of coordinating UAV and UGV for precision agriculture, where they found energy‐efficient ways to visit areas with misclassified nitrogen levels. UAV and UGV have also been used in a collaborative manner to perform target localization .…”