Publications

Unmanned Aerial Vehicles (UAVs) have revolutionized inspection tasks by offering a safer, more efficient, and flexible alternative to traditional methods. However, battery limitations often constrain their effectiveness, necessitating the development of optimized flight paths and data collection techniques. While existing approaches like coverage path planning (CPP) ensure comprehensive data collection, they can be inefficient, especially when in...

Agentic AI refers to autonomous systems that can perceive their environment, make decisions, and take actions to achieve goals with minimal or no human intervention. Recent advances in Large Language Models (LLMs) have opened new pathways to imbue robots with such “agentic” behaviors by leveraging the LLMs' vast knowledge and reasoning capabilities for planning and control. This survey provides the first comprehensive exploration of LLM-based rob...

This dataset was collected to support Vehicle Routing Problem (VRP) optimization by providing structured time and distance matrices. A Third-Party Logistics (3PL) company granted access to its order management software, from which data on daily delivery problems involving pharmaceutical distribution were obtained. The dataset consists of carefully processed distance and time matrices, over a period of nine days. Each day's problem involved 60-85 ...

Affordable and modular ground robots are key in robotics research and education. However, many existing platforms rely on expensive hardware and rigid architectures, limiting their reproducibility and practical deployment in resource-constrained environments. This work presents the design and implementation of a low-cost, 3D-printed omnidirectional robot that combines mechanical flexibility with modern embedded software capabilities. The proposed...

Multi-UAV Coverage Path Planning (mCPP) algorithms in popular commercial software typically treat a Region of Interest (RoI) only as a 2D plane, ignoring important 3D structure characteristics. This leads to incomplete 3D reconstructions, especially around occluded or vertical surfaces. In this paper, we propose a modular algorithm that can extend commercial two-dimensional path planners to facilitate terrain-aware planning by adjusting altitude ...

In this paper we present a Blender add-on named LFG that allows for easy, large and realistic, 3D model LandFill Generation. Large datasets of vast, diverse synthetic landfills are hard to come by, and greatly in need for the purposes of developing and evaluating a multitude of algorithms (e.g. waste classification, 3D-reconstruction, volume estimation algorithms) in the context of research against environment crime. Additionally, they can be use...

The increasing number of electric vehicles (EVs) necessitates the installation of more charging stations. The challenge of managing these grid-connected charging stations leads to a multi-objective optimal control problem where station profitability, user preferences, grid requirements and stability should be optimized. However, it is challenging to determine the optimal charging/discharging EV schedule, since the controller should exploit fluctu...

This paper focuses on Coverage Path Planning (CPP) methodologies, particularly in the context of multi-robot missions, to efficiently cover user-defined Regions of Interest (ROIs) using groups of UAVs, while emphasizing on the reduction of energy consumption and mission duration. Optimizing the efficiency of multi-robot CPP missions involves addressing critical factors such as path length, the number of turns, re-visitations, and launch positions...

This paper deals with the problem of informative path planning for a UAV deployed for precision agriculture applications. First, we observe that the “fear of missing out” data lead to uniform, conservative scanning policies over the whole agricultural field. Consequently, employing a non-uniform scanning approach can mitigate the expenditure of time in areas with minimal or negligible real value, while ensuring heightened precision in information...

The current paper proposes a hierarchical reinforcement learning (HRL) method to decompose a complex task into simpler sub-tasks and leverage those to improve the training of an autonomous agent in a simulated environment. For practical reasons (i.e., illustrating purposes, easy implementation, user-friendly interface, and useful functionalities), we employ two Python frameworks called TextWorld and MiniGrid. MiniGrid functions as a 2D simulated ...

While reinforcement learning (RL) algorithms have generated impressive strategies for a wide range of tasks, the performance improvements in continuous-domain, real-world problems do not follow the same trend. Poor exploration and quick convergence to locally optimal solutions play a dominant role. Advanced RL algorithms attempt to mitigate this issue by introducing exploration signals during the training procedure. This successful integration ha...

This paper presents a modular and holistic Precision Agriculture platform, named CoFly, incorporating custom-developed AI and ICT technologies with pioneering functionalities in a UAV-agnostic system. Cognitional operations of micro Flying vehicles are utilized for data acquisition incorporating advanced coverage path planning and obstacle avoidance functionalities. Photogrammetric outcomes are extracted by processing UAV data into 2D fields and ...

This work focuses on the efficiency improvement of grid-based Coverage Path Planning (CPP) methodologies in real-world applications with UAVs. While several sophisticated approaches are met in literature, grid-based methods are not commonly used in real-life operations. This happens mostly due to the error that is introduced during the region’s representation on the grid, a step mandatory for such methods, that can have a great negative impact on...

This paper presents a novel, low-cost, user-friendly Precision Agriculture platform that attempts to alleviate the drawbacks of limited battery life by carefully designing missions tailored to each field’s specific, time-changing characteristics. The proposed system is capable of designing coverage missions for any type of UAV, integrating field characteristics into the resulting trajectory, such as irregular field shape and obstacles. The collec...

In this study we propose a model-based dynamic path planning algorithm that is designed to navigate Autonomous Vehicles through complex and dynamic environments. To achieve that, a novel spline-based approach is utilized for the production of several candidate paths along a predetermined route and a Gaussian-based function is utilized for their evaluation. Our algorithm takes into account various factors, such as static and dynamic objects, to ma...

In this paper, we are trying to examine the role of robots in the Industry 4.0 Era. After a brief chronology and an updated literature review on the field, we are trying to examine one of the biggest problems in today's industrial automation, namely in Robotic bin-picking. Its objective is to manage to control a robot with multiple sensory motors attached and be able to collect identified objects with random poses out of a bin, containing a colle...

The CoFly-WeedDB contains 201 RGB images (~436 MB) from the attached camera of DJI Phantom Pro 4 from a cotton field in Larissa, Greece during the first stages of plant growth. The 1280 x 720 RGB images were collected while the Unmanned Aerial Vehicle (UAV) was performing a coverage mission over the field's area. During the designed mission, the camera angle was adjusted to -87°, vertically with the field. The flight altitude and speed of the UAV...

In order to sufficiently protect active personnel and physical environment from hazardous leaks, recent industrial practices integrate innovative multi-modalities so as to maximize response efficiency. Since the early detection of such incidents portrays the most critical factor for providing efficient response measures, the continuous and reliable surveying of industrial spaces is of primary importance. Current study develops a surveying mechani...

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 the hood lies a novel optimization scheme for grid-based methods, utilizing Simulated Annealing algorithm, that significantly increases the achieved percentage of coverage and improves the qualitative features of the generated paths. Extensive simulated evaluation in co...

Unmanned Aerial Vehicles (UAVs) consist of emerging technologies that have the potential to be used gradually in various sectors providing a wide range of applications. In agricultural tasks, the UAV-based solutions are supplanting the labor and time-intensive traditional crop management practices. In this direction, this work proposes an automated framework for efficient data collection in crops employing autonomous path planning operational mod...

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 this scope, MarsExplorer, an openai-gym compatible environment tailored to exploration/coverage of unknown areas, is presented. MarsExplorer translates the original robotics problem into a Reinforcement Learning setup that various off-the-shelf algorithms can tackle. Any...

This article investigates the problem of deploying a swarm of UAVs equipped with gas sensors for industrial remote gas-plume sensing. This setup's objective is to continuously adjust the swarm formation to maximize the combined perception for the dynamically evolved plume’s cloud, focusing around areas with the highest concentration/intensity. Initially, such a setup is formulated into an optimization problem, the solution of which could be acqui...

Recently, special attention has been paid in developing methodologies and systems for embedding autonomy within smart devices (Things). Moreover, as Things typically operate in an interconnected IoT ecosystem, autonomous operation must be performed in a cooperative fashion so the different Things coordinate their autonomous actions towards meeting high-level objectives and policies. Embedding Things with cooperative autonomy typically requires a ...

The current study focuses on the problem of continuously tracking a dynamically evolving CH4 plume utilizing a mutually built consensus by heterogeneous sensing platforms: mobile and static sensors. Identifying the major complexities and emergent dynamics (leakage source, intensity, time) of such problem, a distributed, multi-agent, optimization algorithm was developed and evaluated in an indoor continuous plume-tracking application (where reacti...

Cross-border crime utilizes recent advanced systems to perform their illegal activities. Innovative sensory systems and specialized equipment are examples that were used for trafficking of human and of various illicit materials. The increasing challenges that border personnel must resolve require the usage of recent technological advances as well. Thus, the utilization of pioneer technologies seems imperative to precede technologically organized ...

This letter tackles the problem of positioning a swarm of UAVs inside a completely unknown terrain, having as objective to maximize the overall situational awareness. The situational awareness is expressed by the number and quality of unique objects of interest, inside the UAVs' fields of view. YOLOv3 and a system to identify duplicate objects of interest were employed to assign a single score to each UAVs' configuration. Then, a novel navigation...

Political instability around the world continues to place a significant emphasis on border control. Monitoring these borders requires persistent surveillance in a variety of remote, hazardous and hostile environments. While recent developments in autonomous and unmanned systems promise to provide a new generation of tools to assist in border control missions, the complexity of designing, testing and operating large-scale systems limits their adop...

Over the last years, an intensified interest has been shown in many studies for precision agriculture. Unmanned Aircraft Systems (UASs) are capable of solving a plethora of surveying tasks due to their flexibility, independence and customization. The incorporation of UASs remote sensing in precision agriculture enhances the abilities of crop mapping, management and identification through vegetation indices. In addition to this, different image an...

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 mission can be cast as a general optimization problem, without explicit guidelines of the subtasks per different robot. Owing to the unknown environment, unknown robot dynamics, sensor nonlinearities, etc., the analytic form of the optimization cost function is not avail...

The introduction of Unmanned vehicles (UxVs) in the recent years has created a new security field that can use them as both a potential threat as well as new technological weapons against those threats. Dealing with these issues from the counter-threat perspective, the proposed architecture project focuses on designing and developing a complete system which utilizes the capabilities of multiple UxVs for surveillance objectives in different operat...

This research develops a new on-line trajectory planning algorithm for a team of Autonomous Underwater Vehicles (AUVs). The goal of the AUVs is to cooperatively explore and map the ocean seafloor. As the morphology of the seabed is unknown and complex, standard non-convex algorithms perform insufficiently. To tackle this, a new simulation-based approach is proposed and numerically evaluated. This approach adapts the Parametrized Cognitive-based A...

This paper deals with the path planning problem of a team of mobile robots, in order to cover an area of interest, with prior-defined obstacles. For the single robot case, also known as single robot coverage path planning (CPP), an O(n) optimal methodology has already been proposed and evaluated in the literature, where n is the grid size. The majority of existing algorithms for the multi robot case (mCPP), utilize the aforementioned algorithm. D...

This paper deals with the problem of retrieving the optimal path between two points inside an unknown environment, utilizing a robot-scouter. The vast majority of the path planning frameworks for an unknown environment focuses on the problem of navigating a robot, as soon as possible, towards a pre-specified location. As a result, the final followed path between the start and end location is not necessarily the optimal one, as the objective of th...

This paper deals with the problem of autonomous exploration of unknown areas using teams of Autonomous X Vehicles (AXVs)—with X standing for Aerial, Underwater or Sea-surface—where the AXVs have to autonomously navigate themselves so as to construct an accurate map of the unknown area. Such a problem can be transformed into a dynamic optimization problem which, however, is NP-complete and thus infeasible to be solved. A usual attempt is to relax ...

In this paper, we explore, extend and simplify the localization of the description ability of the well-established MPEG-7 (Scalable Colour Descriptor (SCD), Colour Layout Descriptor (CLD) and Edge Histogram Descriptor (EHD)) and MPEG-7-like (Color and Edge Directivity Descriptor (CEDD)) global descriptors, which we call the SIMPLE family of descriptors. Sixteen novel descriptors are introduced that utilize four different sampling strategies for t...

Within the project NOPTILUS, a fully functional system/methodology had been developed that allows the cooperative, fully-autonomous navigation of teams of AUVs when deployed in Static or Dynamic Underwater Map Construction (SDUMC) or Dynamic Underwater Phenomena Tracking (DUPT) missions. The key ingredient of this fully functional system/methodology (called the NOPTILUS Planning, Assignment and Navigation Module - NOPTILUS PAN) is an optimal cont...

Accurate maps are essential in the case of robot teams, so that they can operate autonomously and accomplish their tasks efficiently. In this work we present an approach which allows the generation of detailed maps, suitable for robot navigation, from a mesh of sparse points using Cellular Automata and simple evolutions rules. The entire map area can be considered as a 2D Cellular Automaton (CA) where the value at each CA cell represents the heig...

In this paper we propose and evaluate a new technique that localizes the description ability of the well established MPEG-7 and MPEG-7-like global descriptors. We employ the SURF detector to define salient image patches of blob-like textures and use the MPEG-7 Scalable Color (SC), Color Layout (CL) and Edge Histogram (EH) descriptors and the global MPEG-7-like Color and Edge Directivity Descriptor (CEDD), to produce the final local features' vect...

In this paper, we present a new approach that is able to efficiently and fully-autonomously navigate a team of Unmanned Aerial or Underwater Vehicles (UAUV's) when deployed in exploration of unknown static and dynamic environments towards providing accurate static/dynamic maps of the environment. Additionally to achieving to efficiently and fully-autonomously navigate the UAUV team, the proposed approach possesses certain advantages such as its e...

Current multi-AUV systems are far from being capable of fully autonomously taking over real-life complex situation-awareness operations. As such operations require advanced reasoning and decision-making abilities, current designs have to heavily rely on human operators. The involvement of humans, however, is by no means a guarantee of performance; humans can easily be over-whelmed by the information overload, fatigue can act detrimentally to thei...

This paper tackles the problem of the user's incapability to describe exactly the image that he seeks by introducing an innovative image search engine called TsoKaDo. Until now the traditional web image search was based only on the comparison between metadata of the webpage and the user's textual description. In the method proposed, images from various search engines are classified based on visual content and new tags are proposed to the user. Re...