| 1. |
- Aviles, Marcos, et al.
(författare)
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A co-design methodology for implementing computer vision algorithms for rover navigation onto reconfigurable hardware
- 2011
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Ingår i: Proceedings of the FPL2011 Workshop on Computer Vision on Low-Power Reconfigurable Architectures. ; , s. 9-10
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Vision-based robotics applications have been widely studied in the last years. However, up to now solutions that have been proposed were affecting mostly software level. The SPARTAN project focuses in the tight and optimal implementation of computer vision algorithms targeting to rover navigation. For evaluation purposes, these algorithms will be implemented with a co-design methodology onto a Virtex-6 FPGA device.
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| 2. |
- Kostavelis, Ioannis, et al.
(författare)
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Comparative presentation of real-time obstacle avoidance algorithms using solely stereo vision
- 2010
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Konferensbidrag (refereegranskat)abstract
- This work presents a comparison between vision-based obstacle avoidance algorithms for mobile robot navigation. The issue of obstacle avoidance in robotics demands a reliable solution since mobile platforms often have to maneuver in arbitrary environments with high level of risk. The most significant advantage of the presented work is the use of only one sensor, i.e. a stereo camera, which significantly diminishes the computational cost. Three different versions of the proposed method have been developed. The implementation of these algorithms consists of a stereo vision module, which is common for all the versions, and a decision making module, which is different in each version and proposes an efficient method of processing stereo information in order to navigate a robotic platform. The algorithms have been implemented in C++ and the produced frame rate ensures that the robot will be able to accomplish the proposed decisions in real time. The presented algorithms have been tested on various different input images and their results are shown and discussed.
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| 3. |
- Kostavelis, Ioannis, et al.
(författare)
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Real-time algorithm for obstacle avoidance
- 2009
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Konferensbidrag (refereegranskat)abstract
- This work presents a vision-based obstacle detection and avoidance method for autonomous mobile robots. The implementation of an algorithm able to navigate a robot in arbitrary environments usually demands of the synergy of several sensors. This work presents an algorithm employing only one sensor, i.e. a stereo camera, thus significantly diminishing the system’s complexity. The implementation of this algorithm can be divided into two separate and independent modules. First, the stereo vision module retrieves information from the environment and produces disparity maps and then the decision making module analyses the data of the disparity maps and governs the robot’s direction. The achieved frame rate ensures that the robot will have enough time to accomplish the proposed decisions in real time. Both of the modules have been implemented in C++. The complete algorithm has been examined by being applied on an extensive set of pre-captured stereo images.
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| 4. |
- Kostavelis, Ioannis, et al.
(författare)
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SPARTAN system : Towards a low-cost and high-performance vision architecture for space exploratory rovers
- 2011
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Konferensbidrag (refereegranskat)abstract
- 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 desig- nated 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 com- puter 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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| 5. |
- Kostavelis, Ioannis, et al.
(författare)
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Supervised traversability learning for robot navigation
- 2011
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Ingår i: 12th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2011. - Berlin, Heidelberg : Springer Berlin/Heidelberg. ; , s. 289-298
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Konferensbidrag (refereegranskat)abstract
- 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 non-traversable 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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| 6. |
- Nalpantidis, Lazaros, et al.
(författare)
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Stereovision-based algorithm for obstacle avoidance
- 2009
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Ingår i: Intelligent Robotics And Applications, Proceedings. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642108167 ; , s. 195-204
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Konferensbidrag (refereegranskat)abstract
- 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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| 7. |
- Siozios, K., et al.
(författare)
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SPARTAN project : Efficient implementation of computer vision algorithms onto reconfigurable platform targeting to space applications
- 2011
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Ingår i: 6th International Workshop on Reconfigurable Communication-Centric Systems-on-Chip, ReCoSoC 2011 - Proceedings. - 9781457706424
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Konferensbidrag (refereegranskat)abstract
- 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.
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