Kostas Alexis

Kostas Alexis
Norwegian University of Science and Technology | NTNU · Department of Engineering Cybernetics

PhD

About

157
Publications
67,313
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5,242
Citations
Citations since 2016
106 Research Items
4703 Citations
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20162017201820192020202120220200400600800
20162017201820192020202120220200400600800

Publications

Publications (157)
Article
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This paper presents a strategy for field estimation and informative path planning towards autonomous mapping and radiological characterization of distributed gamma radiation fields within confined GPS-denied environments using aerial robots. First, an online distributed radiation field estimation and spectroscopic analysis framework is presented wh...
Preprint
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This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT competition. In particular, the paper has four main goals. First, we review the algorithms, architectures, and systems adopted by the teams; particular emphasis is put on l...
Preprint
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This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably explore diverse underground environments despite the grueling challenges they present for robotic a...
Article
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This article presents the core technologies and deployment strategies of Team CERBERUS that enabled our winning run in the DARPA Subterranean Challenge finals. CERBERUS is a robotic system-of-systems involving walking and flying robots presenting resilient autonomy, as well as mapping and navigation capabilities to explore complex underground envir...
Preprint
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This work contributes a marsupial robotic system-of-systems involving a legged and an aerial robot capable of collaborative mapping and exploration path planning that exploits the heterogeneous properties of the two systems and the ability to selectively deploy the aerial system from the ground robot. Exploiting the dexterous locomotion capabilitie...
Article
Full-text available
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In...
Preprint
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This work presents the design, hardware realization, autonomous exploration and object detection capabilities of RMF-Owl, a new collision-tolerant aerial robot tailored for resilient autonomous subterranean exploration. The system is custom built for underground exploration with focus on collision tolerance, resilient autonomy with robust localizat...
Preprint
This paper contributes a method to design a novel navigation planner exploiting a learning-based collision prediction network. The neural network is tasked to predict the collision cost of each action sequence in a predefined motion primitives library in the robot's velocity-steering angle space, given only the current depth image and the estimated...
Preprint
This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings, such as cave networks and underground mines, often involve complex, large-scale and multi-branched topologies, while wireless communication within them can be particular...
Preprint
Full-text available
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy hard to achieve. This has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In response...
Preprint
Full-text available
In this paper, a computational resources-aware parameter adaptation method for visual-inertial navigation systems is proposed with the goal of enabling the improved deployment of such algorithms on computationally constrained systems. Such a capacity can prove critical when employed on ultra-lightweight systems or alongside mission critical computa...
Article
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This paper presents the system design, modeling, and control of the Aerial Robotic Chain Manipulator. This new robot design offers the potential to exert strong forces and moments on the environment, carry and lift significant payloads, and simultaneously navigate through narrow corridors. We contribute a hybrid modeling framework to model the syst...
Preprint
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This report accompanies a dataset release on visual and thermal camera data and details a procedure followed to align such multi-modal camera frames in order to provide pixel-level correspondence between the two without using intrinsic or extrinsic calibration information. To achieve this goal we benefit from progress in the domain of multi-modal i...
Chapter
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In this research we present a novel algorithm for background subtraction using a moving camera. Our algorithm is based purely on visual information obtained from a camera mounted on an electric bus, operating in downtown Reno which automatically detects moving objects of interest with the view to provide information for collision avoidance and numb...
Preprint
This manuscript presents enhancements on our motion-primitives exploration path planning method for agile exploration using aerial robots. The method now further integrates a global planning layer to facilitate reliable large-scale exploration. The implemented bifurcation between local and global planning allows for efficient exploration combined w...
Preprint
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This paper presents a review of the design and application of model predictive control strategies for Micro Aerial Vehicles and specifically multirotor configurations such as quadrotors. The diverse set of works in the domain is organized based on the control law being optimized over linear or nonlinear dynamics, the integration of state and input...
Article
Full-text available
Autonomous exploration of subterranean environments remains a major challenge for robotic systems. In response, this paper contributes a novel graph-based subterranean exploration path planning method that is attuned to key topological properties of subterranean settings, such as large-scale tunnel-like networks and complex multi-branched topologie...
Conference Paper
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Resilient pose estimation for autonomous systems, and especially small unmanned aerial robots, is one of the core capabilities required for these robots to perform their assigned tasks in a reliable and efficient manner. Different sensing modalities have been utilized for the robot pose estimation process, particularly in GPS-denied environments. H...
Preprint
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This paper presents the design concept, modeling and motion planning solution for the aerial robotic chain. This design represents a configurable robotic system of systems, consisting of multi-linked micro aerial vehicles that simultaneously presents the ability to cross narrow sections, morph its shape, ferry significant payloads, offer the potent...
Preprint
Research in visual anomaly detection draws much interest due to its applications in surveillance. Common datasets for evaluation are constructed using a stationary camera overlooking a region of interest. Previous research has shown promising results in detecting spatial as well as temporal anomalies in these settings. The advent of self-driving ca...
Conference Paper
Full-text available
This paper overviews the system design, modeling and control of the Aerial Robotic Chain. This new design corresponds to a reconfigurable robotic system of systems consisting of multilinked micro aerial vehicles that presents the ability to cross narrow sections, morph its shape, ferry significant payloads, offer the potential of distributed sensin...
Preprint
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In this paper we present an overview of the methods and systems that give rise to a flying robotic system capable of autonomous inspection, surveying, comprehensive multi-modal mapping and inventory tracking of construction sites with high degree of systematicity. The robotic system can operate assuming either no prior knowledge of the environment...
Preprint
This discussion paper aims to support the argument process for the need to develop a comprehensive science of resilient robotic autonomy. Resilience and its key characteristics relating to robustness, redundancy, and resourcefulness are discussed, followed by a selected - but not exhaustive - list of research themes and domains that are crucial to...
Chapter
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The informative path planning problem is a fundamental problem for autonomous robots in which an algorithm aims to find collision-free and feasible paths that optimize a certain objective (or multiple objectives) and respect imposed system and mission constraints such as a maximum available time budget. In this chapter, the emphasis is put on reced...
Conference Paper
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In this paper we present an experimental results driven system design to enable more robust and self-deployed wireless communications for robotic systems autonomously operating in underground environments such as mines, caves, and tunnels. Subterranean environments pose severe challenges for wireless communications as wireless signal suffers extra...
Conference Paper
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In this paper we present a comprehensive solution for autonomous underground mine rescue using aerial robots. In particular, a new class of Micro Aerial Vehicles are equipped with the ability to localize and map in subterranean settings, explore unknown mine environments on their own, and perform detection and localization of objects of interest fo...
Article
Full-text available
This paper presents the design concept, modeling and motion planning solution for the aerial robotic chain. This design represents a configurable robotic system of systems, consisting of multi-linked micro aerial vehicles that simultaneously presents the ability to cross narrow sections, morph its shape, ferry significant payloads, offer the potent...
Conference Paper
Full-text available
This paper presents a path planning strategy for the autonomous exploration of subterranean environments. Tailored to the specific challenges and particularities of underground settings, and especially the fact that they often are extremely large in scale, tunnel-like, narrow and multi-branched, the proposed method employs a bifurcated local-and gl...
Article
Full-text available
This work presents an uncertainty-aware path-planning strategy to achieve autonomous aerial robotic exploration of unknown environments while ensuring mapping consistency on-the-go. The planner follows a paradigm of hierarchically optimized objectives, which are executed in receding horizon fashion. Initially, a random tree over the known feasible...
Article
Full-text available
Autonomous navigation of microaerial vehicles in environments that are simultaneously GPS‐denied and visually degraded, and especially in the dark, texture‐less and dust‐ or smoke‐filled settings, is rendered particularly hard. However, a potential solution arises if such aerial robots are equipped with long wave infrared thermal vision systems tha...
Conference Paper
Full-text available
This paper presents a novel strategy for autonomous graph-based exploration path planning in subterranean environments. Attuned to the fact that subterranean settings, such as underground mines, are often large-scale networks of narrow tunnel-like and multi-branched topologies, the proposed planner is structured around a bifurcated local-and global...
Conference Paper
Full-text available
In this paper a comprehensive approach to enable resilient robotic autonomy in subterranean environments is presented. Emphasizing on the use of aerial robots to explore underground settings such as mines and tunnels, the presented methods address critical challenges related to extreme sensor degradation, path planning in large-scale, multi-branche...
Conference Paper
Full-text available
In this paper we address the problem of un-supervised anomaly detection and cognizant path planning for surveillance operations using aerial robots. Through one-class classification exploiting deep learned features on image data and a Bayesian technique to fuse, encode and update anomaly information on a real-time reconstructed occupancy map, the r...
Conference Paper
Full-text available
In this paper we address the problem of unsupervised anomaly detection and cognizant path planning for surveillance operations using aerial robots. Through one-class classification exploiting deep learned features on image data and a Bayesian technique to fuse, encode and update anomaly information on a real-time reconstructed occupancy map, the ro...
Conference Paper
Full-text available
In this work the challenge of autonomous navigation , exploration and mapping in underground mines using aerial robots is considered. Despite the paramount importance of underground mine accessing, the relevant challenges of sensor degradation (darkness, dust, smoke) and broadly stringent navigation conditions due to particularly narrow geometries...
Conference Paper
Full-text available
This paper proposes an approach for fusing direct radiometric data from a thermal camera with inertial measurements to extend the robotic capabilities of aerial robots for navigation in GPS-denied and visually degraded environments in the conditions of darkness and in the presence of airborne obscurants such as dust, fog and smoke. An optimization...
Preprint
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Visual Place Recognition (VPR) has seen significant advances at the frontiers of matching performance and computational superiority over the past few years. However, these evaluations are performed for ground-based mobile platforms and cannot be generalized to aerial platforms. The degree of viewpoint variation experienced by aerial robots is compl...
Preprint
Full-text available
GPS-denied localization of aerial robots in sensing-degraded environments and especially in dark, texture-less and dust-or smoked-filled settings is rendered particularly hard. An alternative is to utilize Long Wave Infrared thermal vision which is unaffected by darkness and can penetrate most obscurants. However, utilization of thermal vision is m...
Preprint
With an ever-widening domain of aerial robotic applications, including many mission critical tasks such as disaster response operations, search and rescue missions and infrastructure inspections taking place in GPS-denied environments, the need for reliable autonomous operation of aerial robots has become crucial. Operating in GPS-denied areas aeri...
Conference Paper
Full-text available
In this work we present an integrated approach for autonomous navigation and mapping in underground mines using aerial robots. Underground mines present a set of critical challenges as they are not only GPS-denied by nature, but their environmental circumstances also lead to severe sensor degradation (due to combinations of darkness, dust, and smok...
Conference Paper
Full-text available
In this work, we present an approach for the detection of the direction of free space in order to improve the efficiency of robotic exploration by exploiting the history of free space calculations. As a motivational example, we consider the case of exploration of subterranean environments where the length of corridors can exceed the range of most s...
Conference Paper
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VIDEO:https://youtu.be/aqZugneeCxc During the past decade, aerial robots have seen an unprecedented expansion in their utility as they take on more tasks which had typically been reserved for humans. With an ever widening domain of aerial robotic applications, including many mission critical tasks such as disaster response operations, search and re...
Conference Paper
Full-text available
This paper considers the problem of resilient and collision-tolerant navigation of aerial robots when the estimation of the full robot pose and the map of the environment is not possible due to sensor failure or severe degradation. Typical examples relate to GPS-denied operation in visually-degraded environments (e.g. smoke-filled tunnels, dust-fil...
Preprint
This paper proposes an approach for fusing direct radiometric data from a thermal camera with inertial measurements to extend the robotic capabilities of aerial robots for navigation in GPS-denied and visually degraded environments in the conditions of darkness and in the presence of airborne obscurants such as dust, fog and smoke. An optimization...
Chapter
Full-text available
This use case chapter presents a set of algorithms for the problems of autonomous exploration, terrain monitoring and optimized inspection path planning using aerial robots. The autonomous exploration algorithms described employ a receding horizon structure to iteratively derive the action that the robot should take to optimally explore its environ...
Preprint
Autonomous robots are commonly tasked with the problem of area exploration and search for certain targets or artifacts of interest to be tracked. Traditionally, the problem formulation considered is that of complete search and thus - ideally - identification of all targets of interest. An important problem however which is not often addressed is th...
Conference Paper
Full-text available
For robotic inspection tasks in known environments fiducial markers provide a reliable and low-cost solution for robot localization. However, detection of such markers relies on the quality of RGB camera data, which degrades significantly in the presence of visual obscurants such as fog and smoke. The ability to navigate known environments in the p...
Conference Paper
Full-text available
This paper proposes a method for tight fusion of visual, depth and inertial data in order to extend robotic capabilities for navigation in GPS-denied, poorly illuminated, and textureless environments. Visual and depth information are fused at the feature detection and descriptor extraction levels to augment one sensing modality with the other. Thes...
Preprint
Full-text available
In this research we present a novel algorithm for background subtraction using a moving camera. Our algorithm is based purely on visual information obtained from a camera mounted on an electric bus, operating in downtown Reno which automatically detects moving objects of interest with the view to provide a fully autonomous vehicle. In our approach...