In this thesis we deal with the problem of navigating a team of robots in both known and unknown environments, so as the mission's objectives to be fulfilled. The structure of this thesis is divided into two main pillars. In the first pillar we deal with the problem of determining an optimal path involving all points of a given area of interest (offline), while avoiding sub-areas with specific characteristics (e.g. obstacles, no-fly zones, etc.). This problem, which is usually referred as multi-robot coverage path planning (mCPP), has been proven to be NP-hard. Currently, existing approaches produce polynomial algorithms that are able to only approximate the minimum covering time. In chapter 3, a novel methodology is proposed, capable of producing such optimal paths in approximately polynomial time. In the heart of the proposed approach lies the DARP algorithm, which divides the terrain into a number of equal areas each corresponding to a specific robot, in such a way to guarantee: complete coverage, non-backtracking solution, minimum coverage path, while at the same time does not need any preparatory stage. In the second pillar of this thesis, we design algorithms capable of navigating team of robots without any prior knowledge. More specifically, we deal with problems where the objectives of the multi-robot system can be transformed to the optimization of a specifically defined cost-function. Due to the unknown environment, unknown robots' dynamics, sensor nonlinearities, etc., the analytic form of the cost-function is not available a priori. Therefore, standard gradient descent-like algorithms are not applicable to these problems. In chapter 4, we first show that optimal one-step-ahead exploration schemes that are based on a transformed optimization criterion can lead to highly efficient solutions to the multi-robot exploration. As, however, optimal one-step-ahead solutions to the transformed optimization criterion cannot be practically obtained using conventional optimization schemes, the second step in our ...
Towards a fully autonomous and cooperative deployment of multi-robot teams for exploration and coverage in unknown or partially known environments ; Πλήρως αυτόνομες και συνεργατικές μέθοδοι για ομάδες ρομπότ με στόχο την εξερεύνηση και κάλυψη αγνώστων ή μερικώς γνωστών περιοχών
2017-01-01
Hochschulschrift
Elektronische Ressource
Englisch
Αυτόνομη πλοήγηση , Ομάδες ρομπότ , Βελτιστοποίηση συνάρτησης κόστους , Κάλυψη περιοχών , Χαρτογράφηση , Προσαρμοστικά συστήματα , Ελάχιστα μονοπάτια κάλυψης , Θαλάσσια ρομποτικά συστήματα , Autonomous navigation , Multi-robot teams , Cost function optimization , Multi-robot coverage , Multi-robot mapping , Learning and adaptive system , Minimum coverage paths , Marine robotics , Επιστήμες Μηχανικού και Τεχνολογία , Επιστήμη Ηλεκτρολόγου Μηχανικού , Ηλεκτρονικού Μηχανικού , Μηχανικού Η/Υ , Engineering and Technology , Electrical Engineering , Electronic Engineering , Information Engineering
DDC: | 629 |
Cooperative multi-robot belief space planning for autonomous navigation in unknown environments
British Library Online Contents | 2018
|Human-Robot Teams for Unknown and Uncertain Environments
NTIS | 2015
|Human-Robot Teams for Unknown and Uncertain Environments
NTRS | 2015
|A Frontier Based Multi-Robot Approach for Coverage of Unknown Environments
BASE | 2015
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