for studying complex phenomena. Robotic sensing systems will
revolutionize this area by enabling access to data gathered at
unprecedented spatio-temporal scales. Environmental science
applications, in turn, motivate challenging robotics research problems.
In this talk, I will present new algorithms for sensing planning
problems motivated by these applications, and the design of robotic
monitoring systems developed for two real-world applications.
In the first part, I will present the design of an autonomous robotic
system developed for monitoring invasive fish in lakes. In the second
part, we will focus on the algorithmic aspects of the art gallery
problem, a classical camera placement problem, under constraints
motivated by surveillance and visual monitoring. The standard
formulation does not take into account self-occlusions of an
object-of-interest within the environment. We will formulate the art
gallery problem to guarantee that despite self-occlusions, any convex
object present anywhere in the environment, will be seen from all sides.
I will present bounds and approximation algorithms for placing cameras
under these constraints. In the third part, I will describe a robotic
data collection system for precision agriculture. We will study the
problem of planning energy-aware trajectories for collaborative aerial
and ground robots in the context of this application.
Throughout the talk, along with theoretical results, I will present
experiments conducted with autonomous boats in Minnesota lakes, wheeled
robots operating on frozen lakes, and an aerial robot operating over a