Covering Paths and Trees for Planar Grids

Given a set of points in the plane, a covering path is a polygonal path that visits all the points. In this paper we consider covering paths of the vertices of an n x m grid. We show that the minimal number of segments of such a path is $2\min(n,m)-1$ except when we allow crossings and $n=m\ge 3$, in which case the minimal number of segments of such a path is $2\min(n,m)-2$, i.e., in this case we can save one segment. In fact we show that these are true even if we consider covering trees instead of paths. These results extend previous works on axis-aligned covering paths of n x m grids and complement the recent study of covering paths for points in general position, in which case the problem becomes significantly harder and is still open

Genetic Algorithms used for Search and Rescue of Vulnerable People in an Urban Setting

The main goal of this research is to design and develop a genetic algorithm (GA) for path planning of an Unmanned Aerial Vehicle (UAV) outfitted with a camera to efficiently search for a lost person in an area of interest. The research focuses on scenarios where the lost person is from a vulnerable population, such as someone suffering from Alzheimer or a small child who has wondered off. To solve this problem, a GA for path planning was designed and implemented in Matlab. The area of interest is considered to be a circle that encompasses the distance the person could have walked in the time they have been missing. The area might also have some subareas that could not be excluded from the search for various reasons, such as a river they could not cross, or a fenced area. A grid is imposed on the area of interest, based on the field of view of the camera that the UAV is carrying and the height the UAV is flying. A chromosome is the encoding of the path the UAV will fly and the fitness function of the GA is designed to ensure that the UAV is covering all areas of the grid with the least amount of backtracking. The results show that the GA can find a path that efficiently covers the area. These results can be generalized to use more than one UAV

Approximation Algorithm for Line Segment Coverage for Wireless Sensor Network

The coverage problem in wireless sensor networks deals with the problem of covering a region or parts of it with sensors. In this paper, we address the problem of covering a set of line segments in sensor networks. A line segment ` is said to be covered if it intersects the sensing regions of at least one sensor distributed in that region. We show that the problem of finding the minimum number of sensors needed to cover each member in a given set of line segments in a rectangular area is NP-hard. Next, we propose a constant factor approximation algorithm for the problem of covering a set of axis-parallel line segments. We also show that a PTAS exists for this problem.Comment: 16 pages, 5 figures