Karl J. Obermeyer

TL;DR: In this paper, the authors defined cardinality of a set A A, A, A, @A = interior, closure, and boundary of set A, respectively C = cost of an aircraft reconnaissance tour, m d x;x0 = length of shortest aircraft path from state x to state x0, m nsamples = actual number of samples to build a roadmap nsamples are estimated number of sampled to build roadmap rmin = Dubins aircraft minimum turn radius R = s-dimensional Euclidean space S = circle parameterized by angle radians ranging from 0 to

TL;DR: A genetic algorithm is designed to solve the general aircraft visual reconnaissance problem for static ground targets in terrain and shown that, under simplifying assumptions, it can be reduced to a variant of the Traveling Salesman Probem which is called the PVDTSP (Polygon-Visiting Dubins Traveling salesman Problem).

TL;DR: Two algorithms are developed to solve the general aircraft visual reconnaissance problem for static ground targets in terrain, called the PVDTSP (Polygon-Visiting Dubins Traveling Salesman Problem), which is shown extensible to handle wind, airspace constraints, any vehicle dynamics, and open-path problems.

TL;DR: A distributed algorithm for a group of robotic agents with omnidirectional vision to deploy into nonconvex polygonal environments with holes to achieve full visibility coverage of the environment while maintaining line‐of‐sight connectivity with each other.

TL;DR: An algorithm for a group of guards statically positioned in a nonconvex polygonal environment with holes that takes an approach known as exact cell decomposition in the motion planning literature to compute a schedule to rotate a set of searchlights in such a way that any target in an environment will necessarily be detected in finite time.