Joshua Vander Hook

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

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.

Tracking Aquatic Invaders: Autonomous Robots for Monitoring Invasive Fish

Carp is a highly invasive bottom-feeding fish that pollutes and dominates lakes by releasing harmful nutrients. Recently, biologists started studying the behavior of carp by tagging the fish with radio emitters. The biologists search for and localize the radio-tagged fish manually using a global positioning system (GPS) and a directional antenna. We are developing a novel robotic sensor system in which human effort is replaced by autonomous robots capable of finding and tracking tagged carp. In this article, we report the current state of our system. We present a new coverage algorithm for finding tagged fish and active localization algorithms for precisely localizing them. In addition to theoretical analysis and simulation results, we report results from field experiments.

Sensor Planning for a Symbiotic UAV and UGV System for Precision Agriculture

We study two new informative path planning problems that are motivated by the use of aerial and ground robots in precision agriculture. The first problem, termed sampling traveling salesperson problem with neighborhoods ( Sampling TSPN), is motivated by scenarios in which unmanned ground vehicles (UGVs) are used to obtain time-consuming soil measurements. The input in SamplingTSPN is a set of possibly overlapping disks. The objective is to choose a sampling location in each disk and a tour to visit the set of sampling locations so as to minimize the sum of the travel and measurement times. The second problem concerns obtaining the maximum number of aerial measurements using an unmanned aerial vehicle (UAV) with limited energy. We study the scenario in which the two types of robots form a symbiotic system—the UAV lands on the UGV, and the UGV transports the UAV between deployment locations. This paper makes the following contributions. First, we present an

Active target localization for bearing based robotic telemetry

\operatornamewithlimits{\mathcal {O}}(\frac{r_{\max }}{r_{\min }})

Cautious Greedy Strategy for Bearing-only Active Localization: Analysis and Field Experiments

approximation algorithm for SamplingTSPN , where

Algorithms for Cooperative Active Localization of Static Targets With Mobile Bearing Sensors Under Communication Constraints

r_{\min }

Local-Search Strategy for Active Localization of Multiple Invasive Fish

and

Cautious greedy strategy for bearing-based active localization: Experiments and theoretical analysis

r_{\max }

Environment and Solar Map Construction for Solar-Powered Mobile Systems

are the minimum and maximum radii of input disks. Second, we show how to model the UAV planning problem using a metric graph and formulate an orienteering instance to which a known approximation algorithm can be applied. Third, we apply the two algorithms to the problem of obtaining ground and aerial measurements in order to accurately estimate a nitrogen map of a plot. Along with theoretical results, we present results from simulations conducted using real soil data and preliminary field experiments with the UAV.

Finding and tracking targets in the wild: Algorithms and field deployments

We present a novel robotic telemetry system for localizing radio-tagged invasive fish in frozen lakes using coarse bearing measurements. We address the problem of selecting sensing locations so as to minimize the uncertainty in the location of the target. For this purpose, we propose three active localization algorithms and evaluate them both in simulations and through field experiments. We also present a novel technique for bearing-estimation from directional radio antenna which is critical for the successful execution of the active localization algorithms. Our system is able to operate on frozen lakes and localize the target to within values as low as one meter.