76 citations · 132 across the 5 of their papers we have counts for
7 papers
Cooperative Multi-UAV Coverage Mission Planning Platform for Remote Sensing Applications
Savvas D. Apostolidis, Pavlos Ch. Kapoutsis, Athanasios Ch. Kapoutsis +1
This paper proposes a novel mission planning platform, capable of efficiently deploying a team of UAVs to cover complex-shaped areas, in various remote sensing applications. Under…
A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions
Athanasios Ch. Kapoutsis, Savvas A. Chatzichristofis, Elias B. Kosmatopoulos
This paper presents a distributed algorithm applicable to a wide range of practical multi-robot applications. In such multi-robot applications, the user-defined objectives of the m…
MarsExplorer: Exploration of Unknown Terrains via Deep Reinforcement Learning and Procedurally Generated Environments
Dimitrios I. Koutras, Athanasios Ch. Kapoutsis, Angelos A. Amanatiadis +1
This paper is an initial endeavor to bridge the gap between powerful Deep Reinforcement Learning methodologies and the problem of exploration/coverage of unknown terrains. Within t…
Autonomous and cooperative design of the monitor positions for a team of UAVs to maximize the quantity and quality of detected objects
Dimitrios I. Koutras, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos
This paper tackles the problem of positioning a swarm of UAVs inside a completely unknown terrain, having as objective to maximize the overall situational awareness. The situationa…
The Lagrangian remainder of Taylor's series, distinguishes time complexities to polynomials or not
Nikolaos P. Bakas, Elias Kosmatopoulos, Mihalis Nicolaou +1
The purpose of this letter is to investigate the time complexity consequences of the truncated Taylor series, known as Taylor Polynomials \cite{bakas2019taylor,Katsoprinakis2011,Ne…
Understanding Deep Convolutional Networks through Gestalt Theory
Angelos Amanatiadis, Vasileios Kaburlasos, Elias Kosmatopoulos
The superior performance of deep convolutional networks over high-dimensional problems have made them very popular for several applications. Despite their wide adoption, their unde…