Smoothing of Piecewise Linear Paths

We present an anytime-capable fast deterministic greedy algorithm for smoothing piecewise linear paths consisting of connected linear segments. With this method, path points with only a small influence on path geometry (i.e. aligned or nearly aligned points) are successively removed. Due to the removal of less important path points, the computational and memory requirements of the paths are reduced and traversing the path is accelerated. Our algorithm can be used in many different applications, e.g. sweeping, path finding, programming-by-demonstration in a virtual environment, or 6D CNC milling. The algorithm handles points with positional and orientational coordinates of arbitrary dimension

Efficient Smoothing of Piecewise Linear Paths with Minimal Deviation

Abstract- We present an anytime fast deterministic greedy method for smoothing piecewise linear paths consisting of connected linear segments by incrementally removing path points. First, points with only a small influence on path geometry are removed, i.e. aligned or nearly aligned points. Due to the removal of less important path points, the high computational and storage space requirements of the paths are reduced and traversal of the path is accelerated. Our algorithm can be used in the most diverse applications, i.e. sweeping, path finding or programming-bydemonstration in a virtual environment. Index Terms – linear path, smoothing, shortening, merging, thinning, anytime, deviatio

Entwicklung einer semantischen Missionssteuerung für autonome Inspektionsroboter

Ziel dieser Arbeit ist die Entwicklung einer semantischen Missionssteuerung für autonome Inspektionsroboter, welche es ermöglicht, den Regelkreis bestehend aus Inspektionsplanung, Planausführung, Inspektionsdatenauswertung, Bewertung der Datenauswertungsergebnisse, Entscheidungsfindung und Neuplanung an Bord des Roboters zu schließen