I Kostavelis

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Papers by I Kostavelis

A case study on 3D scanning, digital reparation and rapid metal additive manufacturing of a centrifugal impeller

IOP Conference Series: Materials Science and Engineering

ArchGenTool: A system-independent collaborative tool for robotic architecture design

2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR), 2016

The AVERT project: Autonomous Vehicle Emergency Recovery Tool

2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2013

Terrorism threatens horrific loss of life, extensive disruption to city transport and damage to c... more Terrorism threatens horrific loss of life, extensive disruption to city transport and damage to commercial real estate. Vehicles provide an ideal delivery mechanism because they can be meticulously prepared well in advance of deployment and then brought into the area of operations. Furthermore, a real and present danger comes from the threat of Chemical, Radiological, Biological and Nuclear (CRBN) contamination. Current methods of bomb disruption and neutralisation are hindered in the event that the device is shielded, blocked or for whatever reason cannot be accessed for examination. The Autonomous Vehicle Emergency Recovery Tool (AVERT) project introduces a unique capability to Police and Armed Services to rapidly deploy, extract and remove blocking vehicles from vulnerable positions such as enclosed infrastructure spaces, tunnels, low bridges as well as under-building and underground car parks. Within the AVERT project, vehicles can be removed from confined spaces with delicate handling, swiftly and in any direction to a safer disposal point to reduce or eliminate collateral damage to infrastructure and personnel. The overall system will be commanded remotely and shall operate autonomously under its own power and sensor awareness, as a critical tool alongside existing technologies, thereby enhancing bomb disposal response speed and safety.

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Semantic mapping for mobile robotics tasks: A survey

Robotics and Autonomous Systems, 2015

ABSTRACT The evolution of contemporary mobile robotics has given thrust to a series of additional... more ABSTRACT The evolution of contemporary mobile robotics has given thrust to a series of additional conjunct technologies. Of such is the semantic mapping, which provides an abstraction of space and a means for human–robot communication. The recent introduction and evolution of semantic mapping motivated this survey, in which an explicit analysis of the existing methods is sought. The several algorithms are categorized according to their primary characteristics, namely scalability, inference model, temporal coherence and topological map usage. The applications involving semantic maps are also outlined in the work at hand, emphasizing on human interaction, knowledge representation and planning. The existence of public available validation datasets and benchmarking, suitable for the evaluation of semantic mapping techniques is also discussed in detail. Last, an attempt to address open issues and questions is also made.

Robotics and Automation Lab., Production and Management Engineering Dept, Democritus University of Thrace, Xanthi, Greece

3D Maps Registration and Path Planning for Autonomous Robot Navigation

Mobile robots dedicated in security tasks should be capable of clearly perceiving their environme... more Mobile robots dedicated in security tasks should be capable of clearly perceiving their environment to competently navigate within cluttered areas, so as to accomplish their assigned mission. The paper in hand describes such an autonomous agent designed to deploy competently in hazardous environments equipped with a laser scanner sensor. During the robot's motion, consecutive scans are obtained to produce dense 3D maps of the area. A 3D point cloud registration technique is exploited to merge the successively created maps during the robot's motion followed by an ICP refinement step. The reconstructed 3D area is then top-down projected with great resolution, to be fed in a path planning algorithm suitable to trace obstacle-free trajectories in the explored area. The main characteristic of the path planner is that the robot's embodiment is considered for producing detailed and safe trajectories of 1 cm resolution. The proposed method has been evaluated with our mobile robot in several outdoor scenarios revealing remarkable performance.

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Real-Time Robot Path Planning for Dynamic Obstacle Avoidance

SPARTAN: Efficient Implementation of Computer Vision Algorithms for Autonomous Rover Navigation

Thorough robot navigation based on SVM local planning

Robotics and Autonomous Systems, 2015

How Do You Help a Robot to Find a Place? A Supervised Learning Paradigm to Semantically Infer about Places

Lecture Notes in Computer Science, 2013

In this paper a visual place recognition algorithm suitable for semantic inference is presented. ... more In this paper a visual place recognition algorithm suitable for semantic inference is presented. It combines place and object classification attributes suitable for the recognition of congested and cluttered scenes. The place learning task is undertaken by a method capable of abstracting appearance information from the places to be memorized. The detected visual features are treated as a bag of words and quantized by a clustering algorithm to form a visual vocabulary of the explored places. Each query image is represented by a consistency histogram spread over the memorized vocabulary. Simultaneously, an object recognition approach based on Hierarchical Temporal Memory network, updates the robot's belief of its current position exploiting the features of scattered objects within the scene. The input images which are introduced to the network undergo a saliency computation step and are subsequently thresholded based on an entropy metric for detecting multiple objects. The place and object decisions are fused by voting to infer the semantic attributes of a particular place. The efficiency of the proposed framework has been experimentally evaluated on a real dataset and proved capable of accurately recognizing multiple dissimilar places.

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Place categorization through object classification

2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings, 2014

Stereovision-based algorithm for obstacle avoidance

This work presents a vision-based obstacle avoidance algorithm for autonomous mobile robots. It p... more This work presents a vision-based obstacle avoidance algorithm for autonomous mobile robots. It provides an efficient solution that uses a minimum of sensors and avoids, as much as possible, computationally complex processes. The only sensor required is a stereo camera. The proposed algorithm consists of two building blocks. The first one is a stereo algorithm, able to provide reliable depth maps of the scenery in frame rates suitable for a robot to move autonomously. The second building block is a decision making algorithm that analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on sequences of self-captured outdoor images and its results have been evaluated. The performance of the algorithm is presented and discussed.

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SPARTAN project: Efficient implementation of computer vision algorithms onto reconfigurable platform targeting to space applications

6th International Workshop on Reconfigurable Communication-Centric Systems-on-Chip, ReCoSoC 2011 - Proceedings, 2011

Vision-based robotic applications exhibit increased computational complexity. This problem become... more Vision-based robotic applications exhibit increased computational complexity. This problem becomes even more important regarding mission critical application domains. The SPARTAN project focuses in the tight and optimal implementation of computer vision algorithms targeting to rover navigation for space applications. For evaluation purposes, these algorithms will be implemented with a co-design methodology onto a Virtex-6 FPGA device.

SPARTAN system: Towards a low-cost and high-performance vision architecture for space exploratory rovers

Proceedings of the IEEE International Conference on Computer Vision, 2011

The "SPAring Robotics Technologies for Autonomous Navigation" (SPARTAN) activity of the European ... more The "SPAring Robotics Technologies for Autonomous Navigation" (SPARTAN) activity of the European Space Agency (ESA) aims to develop an efficient, low-cost and accurate vision system for the future Martian exploratory rovers. The interest on vision systems for space robots has been steadily growing during the last years. The SPARTAN system considers an optimal implementation of computer vision algorithms for space rover navigation and is designated for application to a space exploratory robotic rover, such as the ExoMars. The goal of the present work is the development of an appropriate architecture for the vision system. Thus, the arrangement and characteristics of the rover's vision sensors will be defined and the required computer vision modules will be presented. The analysis will be performed taking into consideration the constraints defined by ESA about the SPARTAN system.

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Supervised traversability learning for robot navigation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011

This work presents a machine learning method for terrain's traversability classification. Stereo ... more This work presents a machine learning method for terrain's traversability classification. Stereo vision is used to provide the depth map of the scene. Then, a v-disparity image calculation and processing step extracts suitable features about the scene's characteristics. The resulting data are used as input for the training of a support vector machine (SVM). The evaluation of the traversability classification is performed with a leave-one-out cross validation procedure applied on a test image data set. This data set includes manually labeled traversable and nontraversable scenes. The proposed method is able to classify the scene of further stereo image pairs as traversable or non-traversable, which is often the first step towards more advanced autonomous robot navigation behaviours.

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Intelligent stereo vision in autonomous robot traversability estimation

Traversability estimation is the process of assessing whether a robot is able to move across a sp... more Traversability estimation is the process of assessing whether a robot is able to move across a specific area. Autonomous robots need to have such an ability to automatically detect and avoid non-traversable areas and, thus, stereo vision is commonly used towards this end constituting a reliable solution under a variety of circumstances. This chapter discusses two different intelligent approaches to assess the traversability of the terrain in front of a stereo vision-equipped robot. First, an approach based on a fuzzy inference system is examined and then another approach is considered, which extracts geometrical descriptions of the scene depth distribution and uses a trained support vector machine (SVM) to assess the traversability. The two methods are presented and discussed in detail.

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Learning the terrain and planning a collision-free trajectory for indoor post-disaster environments

2012 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2012, 2012

Mobile robots dedicated in post-disaster missions should be capable of moving arbitrarily in unkn... more Mobile robots dedicated in post-disaster missions should be capable of moving arbitrarily in unknown cluttered environments so as to accomplish their assigned security task. The paper in hand describes such an agent equipped with collision risk assessment capabilities, while it is able to trace an obstacle-free path in the scene as well. The robot exploits machine learning techniques for the traversability evaluation of the environment by making use of geometrical features, which derive from a postprocessing step of the depth map, obtained by an RGBD sensor. Then, the traversable scenes, are assessed by the likelihood the robot to collide on any arbitrary direction in front of it. Besides, the collision risk likelihood is combined with a path tracing algorithm based on Cellular Automata so that an obstacle-free route is then detected. The proposed method has been examined for several indoor scenarios revealing remarkable efficiency.

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Object recognition using saliency maps and HTM learning

In this paper a pattern classification and object recognition approach based on bio-inspired tech... more In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems.

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Path tracing on polar depth maps for robot navigation

A Mechatronic Platform for Robotic Educational Activities

Mechatronics represents a unifying interdisciplinary and intelligent engineering science paradigm... more Mechatronics represents a unifying interdisciplinary and intelligent engineering science paradigm [HAB 07]. It describes the synergy of education in science and technology, knowledge, learning, thinking, a way of working, practices and professional skills. Interdisciplinary mechatronics is regarded as a philosophy that supports new ways of thinking, innovations and novel possibilties and new design methodologies that aim to achieve optimum functional synergy. Interdisciplinary mechatronics is supported by a strong engineering science foundation beyond the traditional disciplinary boundaries and features open-ending learning chains with ability to fuse new knowledge and experiences through lifelong learning process. Mechatronics engineering is about mastering a multitude of disciplines, technologies and their interaction, whereas mechatronic science is about invention and the development of new theories, models, concepts and tools in response to the needs evolving from interacting scientific disciplines. This philosophy has led to the development of new products, processes and systems that exhibit quality performance, such as reliability, precision, smartness, flexibility, Chapter written by Maki K. HABIB.

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