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Publications

Publications by Armando Sousa

2015

3 DoF/6 DoF Localization System for Low Computing Power Mobile Robot Platforms

Authors
Costa, CM; Sobreira, HM; Sousa, AJ; Veiga, G;

Publication
Cutting Edge Research in Technologies

Abstract

2016

Agricultural Wireless Sensor Mapping for Robot Localization

Authors
Duarte, M; dos Santos, FN; Sousa, A; Morais, R;

Publication
ROBOT 2015: SECOND IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 1

Abstract
Crop monitoring and harvesting by ground robots in steep slope vineyards is an intrinsically complex challenge, due to two main reasons: harsh conditions of the terrain and reduced time availability and unstable localization accuracy of the Global Positioning System (GPS). In this paper the use of agricultural wireless sensors as artificial landmarks for robot localization is explored. The Received Signal Strength Indication (RSSI), of Bluetooth (BT) based sensors/technology, has been characterized for distance estimation. Based on this characterization, a mapping procedure based on Histogram Mapping concept was evaluated. The results allow us to conclude that agricultural wireless sensors can be used to support the robot localization procedures in critical moments (GPS blockage) and to create redundant localization information.

2016

Recognition of Banknotes in Multiple Perspectives Using Selective Feature Matching and Shape Analysis

Authors
Costa, CM; Veiga, G; Sousa, A;

Publication
2016 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2016)

Abstract
Reliable banknote recognition is critical for detecting counterfeit banknotes in ATMs and help visual impaired people. To solve this problem, it was implemented a computer vision system that can recognize multiple banknotes in different perspective views and scales, even when they are within cluttered environments in which the lighting conditions may vary considerably. The system is also able to recognize banknotes that are partially visible, folded, wrinkled or even worn by usage. To accomplish this task, the system relies on computer vision algorithms, such as image preprocessing, feature detection, description and matching. To improve the confidence of the banknote recognition the feature matching results are used to compute the contour of the banknotes using an homography that later on is validated using shape analysis algorithms. The system successfully recognized all Euro banknotes in 80 test images even when there were several overlapping banknotes in the same test image.

2017

Evaluation of Stanford NER for extraction of assembly information from instruction manuals

Authors
Costa, CM; Veiga, G; Sousa, A; Nunes, S;

Publication
2017 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2017, Coimbra, Portugal, April 26-28, 2017

Abstract

2017

Pose Invariant Object Recognition Using a Bag of Words Approach

Authors
Costa, CM; Sousa, A; Veiga, G;

Publication
ROBOT 2017: Third Iberian Robotics Conference - Advances in Intelligent Systems and Computing

Abstract

2016

Robotics: Using a Competition Mindset as a Tool for Learning ROS

Authors
Costa, V; Cunha, T; Oliveira, M; Sobreira, H; Sousa, A;

Publication
ROBOT 2015: SECOND IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 1

Abstract
In this article, a course that explores the potential of learning ROS using a collaborative game world is presented. The competitive mindset and its origins are explored, and an analysis of a collaborative game is presented in detail, showing how some key design features lead participants to overcome the challenges proposed through cooperation and collaboration. The data analysis is supported through observation of two different game simulations: the first, where all competitors were playing solo, and the second, where the players were divided in groups of three. Lastly, the authors reflect on the potentials that this course provides as a tool for learning ROS.

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