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Publicações

Publicações por Germano Veiga

2016

Robust 3/6 DoF self-localization system with selective map update for mobile robot platforms

Autores
Costa, CM; Sobreira, HM; Sousa, AJ; Veiga, GM;

Publicação
ROBOTICS AND AUTONOMOUS SYSTEMS

Abstract
Mobile robot platforms capable of operating safely and accurately in dynamic environments can have a multitude of applications, ranging from simple delivery tasks to advanced assembly operations. These abilities rely heavily on a robust navigation stack, which requires stable and accurate pose estimations within the environment. To solve this problem, a modular localization system suitable for a wide range of mobile robot platforms was developed. By using LIDAR/RGB-D data, the proposed system is capable of achieving 1-2 cm in translation error and 1 degrees-3 degrees degrees in rotation error while requiring only 5-35 ms of processing time (in 3 and 6 DoF respectively). The system was tested in three robot platforms and in several environments with different sensor configurations. It demonstrated high accuracy while performing pose tracking with point cloud registration algorithms and high reliability when estimating the initial pose using feature matching techniques. The system can also build a map of the environment with surface reconstruction and incrementally update it with either the full field of view of the sensor data or only the unknown sections, which allows to reduce the mapping processing time and also gives the possibility to update a CAD model of the environment without degrading the detail of known static areas due to sensor noise.

2015

Robust and Accurate Localization System for Mobile Manipulators in Cluttered Environments

Autores
Costa, CM; Sobreira, HM; Sousa, AJ; Veiga, GM;

Publicação
2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT)

Abstract
Autonomous robots play a pivotal role in improving productivity and reducing operational costs. They excel at both precision and speed in repetitive jobs and can cooperate with humans in complex tasks within dynamic environments. Self-localization is critical to any robot that must navigate or manipulate the environment. To solve this problem, a modular localization system suitable for mobile manipulators was developed. By using LIDAR data the proposed system is capable of achieving less than a centimeter in translation error and less than a degree in rotation error while requiring only 5 to 25 milliseconds of processing time. The system was tested in two different robot platforms at different velocities and in several cluttered and dynamic environments. It demonstrated high accuracy while performing pose tracking and high reliability when estimating the initial pose using feature matching. No artificial landmarks are required and it is able to adjust its operation rate in order to use very few hardware resources when a mobile robot is not moving.

2017

Landmark Detection for Docking Tasks

Autores
Ferreira, F; Sobreira, HM; Veiga, G; Moreira, AP;

Publicação
ROBOT 2017: Third Iberian Robotics Conference - Volume 1, Seville, Spain, November 22-24, 2017

Abstract
For docking manoeuvres, the detection of the objects to dock needs to be precise as the minimum deviation from the objective may lead to the failure of this task. The objective of this article is to test possible ways to detect a landmark using a laser rangefinder for docking manoeuvres. We will test a beacon-based localisation algorithm and an algorithm based on natural landmarks already implemented, however, we will apply modifications to such methods. To verify the possibility of docking using these methods, we will conduct experiments with a real robot. © Springer International Publishing AG 2018.

2013

The ECHORD project proposals analysis - Research profiles, collaboration patterns and research topic trends

Autores
Veiga, G; Silva, C; Araujo, R; Pires, N; Siciliano, B;

Publicação
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
This paper investigates the research profiles, collaboration patterns and research topic trends which can be identified in the proposals submitted to the ECHORD (European Clearing House for Open Robotics Development) FP7 project. On a country level, clusters were identified and characterized by patterns of proposal production per inhabitant, score and international cooperation. Belgium and Sweden constitute a cluster characterized by high proposal production, with very high scores and extensive international collaboration. Belgium also excels from another cluster analysis, being as the only country where 100% of proposals involve industry-academia cooperation and obtain scores above 10. Other findings show that single partner proposals have significantly lower quality than multi-partner proposals but, on the other hand, the number of countries involved shows no influence on the quality of the proposals. Despite the high number of industrial participants present on the proposals, it is observed that they play secondary roles in the proposals, with a very low number projects leaded by companies. Also, it is observed that partnerships between research institutions (non-universities) are the most successful. Concerning topics of the proposals, the technology human-robot interface and the product vision robot for small-scale manufacturing are the most significant. Finally, the paper shows clusters of institutions extracted from the giant network of relations obtained from the ECHORD set of proposals.

2014

The ECHORD Project: A General Perspective

Autores
Griffiths, SS; Natale, C; Araújo, R; Veiga, G; Chiacchio, P; Röhrbein, F; Chiaverini, S; Lafrenz, R;

Publicação
Gearing Up and Accelerating Cross-fertilization between Academic and Industrial Robotics Research in Europe: - Technology Transfer Experiments from the ECHORD Project

Abstract
The European funded ECHORD project1 European Clearing House for Open Robotics Development began in January 2009 with the ambitious goal of bringing together European robotics manufacturers with the excellent European research institutions. Europe has a very strong robot industry and there is significant research potential as well as technological knowledge. There has been a long history of outstanding research and development in both robot manufacturers and research institutes. However, finding common ground between manufacturers and the research community, especially when it comes to defining the future direction of robotics research, has proven difficult in the past. This is one of the recurring themes on both sides, and a new level of cooperation is long overdue. Thus, ECHORD acted as a clearing house to streamline successful know-how transfers. The research leading to the results presented in this book has received funding from the European Union through the 7th Framework Programme (FP7) under grant agreement number FP7-ICT-231143. © Springer International Publishing Switzerland 2014.

2017

Flexible Work Cell Simulator Using Digital Twin Methodology for Highly Complex Systems in Industry 4.0

Autores
Tavares, P; Silva, JA; Costa, P; Veiga, G; Moreira, AP;

Publicação
ROBOT 2017: Third Iberian Robotics Conference - Volume 1, Seville, Spain, November 22-24, 2017

Abstract
The continuous evolution in manufacturing processes has attracted substantial interest from both scientific and research community, as well as from industry. Despite the fact that streamline manufacturing relies on automation systems, most production lines within the industrial environment lack a flexible framework that allows for evaluation and optimisation of the manufacturing process. Consequently, the development of a generic simulators able to mimic any given workflow represent a promising approach within the manufacturing industry. Recently the concept of digital twin methodology has been introduced to mimic the real world through a virtual substitute, such as, a simulator. In this paper, a solution capable of representing any industrial work cell and its properties is presented. Here we describe the key stages of such solution which has enough flexibility to be applied to different working scenarios commonly found in industrial environment. © 2018, Springer International Publishing AG.

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