Papers by Mario Ferreira Martins
Architectures, Networks, and Intelligent Systems for Manufacturing Integration, 1997
CONTROLAB is an environment which integrates intelligent systems and control algorithms aiming at... more CONTROLAB is an environment which integrates intelligent systems and control algorithms aiming at applications in the area of robotics. Within CONTROLAB, two neural network architectures based on the backpropagation and the recursive models are proposed for the implementation of a robust speaker-independent word recognition system. The robustness of the system using the backpropagation network has been largely verified through use by children and adults in totally uncontrolled environments such as large public halls for the exhibition of new technology products. Experimental results with the recursive network show that it is able to overcome the backpropagation network major drawback, the frequent generation of false alarms. In addition, within CONTROLAB, the trajectory to be followed by a robot arm under self-tuning control is determined by a system which uses either VGRAPH or PFIELD algorithms to avoid obstacles detected by the computer vision system. The performance of the second algorithm is greatly improved when it is applied under the control of a rule-based system. An application in which a SCARA robot arm is commanded by voice to pick up a specific tool placed on a table among other tools and obstacles is currently running. This application is used to evaluate the performance of each sub-system within CONTROLAB.
SIMULATION …, 2003
This paper describes CPNSim, a tool to simulate Computational Process Networks. In the process ne... more This paper describes CPNSim, a tool to simulate Computational Process Networks. In the process network model of computation, concurrent processes are connected by unidirectional first in, first out (FIFO) queues to form a network. This model is a natural way to describe, for instance, streams of data samples in a signal processing system. The Computational Process Network (CPN) model augments the original process network by considering firing thresholds. In this paper, after presenting the theory of CPNs, the structure of the event-driven simulator is detailed. As a case study, the simulation of a workload composed of signal processing jobs is presented and analyzed.
Proceedings of the …, 2002
This paper investigates the application of gang scheduling-based algorithms for real time systems... more This paper investigates the application of gang scheduling-based algorithms for real time systems that contain multiple processors. We derive the worst-case response time analysis for gang scheduling with and without machine sharing among jobs. The framework presented for calculating ...
Este trabalho descreve o sistema ARCO de geracao de layout de placas de circuito impresso. O sist... more Este trabalho descreve o sistema ARCO de geracao de layout de placas de circuito impresso. O sistema possui um acelerador em hardware para execucao da etapa de roteamento, baseada no algoritmo de Lee. O software do sistema e composto dos seguintes modulos: interface com o programa de captura de esquematicos do ORCAD, alocador de componentes, ordenador de sinais para roteamento, gerador de descricao grafica da placa e sofisticada interface grafica com o usuario. O sistema ARCO roda em microcomputadores nacionais compativeis com IBM-PC/XT, AT ou 386.
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This paper discusses the integration of intelligent systems and the use of sensor fusion within a... more This paper discusses the integration of intelligent systems and the use of sensor fusion within a Multi-Level Fusion Architecture (MUFA) designed for controlling the navigation of a tele-commanded Autonomous Guided Vehicle (AGV). The AGV can move autonomously within any office environment, following instructions issued by client stations connected to the Internet and reacting accordingly to different situations found in the real world. The modules which integrate the MUFA architecture are discussed and special emphasis is given to the role played by the intelligent obstacle avoidance procedure. The AGV detailed trajectory is firstly defmed by a rule-based PFIELD algorithm from sub-goals established by a global trajectory planner. However, when an unexpected obstacle is detected by the neural network which performs the fusion of information produced by the vision system and sonar sensors, the obstacle avoidance procedure uses a special set of rules to redefine the AGV trajectory. The architecture of the neural network used for performing the sensor fusion function and the adopted set of rules are discussed. In addition, results of some simulation experiments demonstrate the ability ofthe system to define a new global trajectory when unexpected blocked regions are detected.
Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), 2003
− − − − The CONTROLAB AGV is an electric tricycle vehicle that, following issues from client stat... more − − − − The CONTROLAB AGV is an electric tricycle vehicle that, following issues from client stations connected to the network office, moves autonomously through an office environment with a known floorplan and uses an electronic stick, which consists of infrared sensors, to detect and avoid unknown obstacles. This paper presents the global real-time solution for the CONTROLAB AGV to move smoothly within an adaptive grided potencial field which changes each time the electronic stick detects a collision point. This modification is simply performed by the addition of previously calculated potential field values on a grid which represents the room working area. The trajectory between two calculated field values is a continuous-curvature path given by a fifth order polynomial function. The interpolating conditions of the fifth order polynomial function have to fit in with the AGV dynamics so as to allow complex motions to be performed. The real-time AGV motion system consists of periodic and aperiodic tasks released by external clocked events. The system is programmed using concurrent processes and threads to improve its robustness and efficiency. The video of the AGV in motion can be seen in the web page www.nce.ufrj.br/controlab.
42nd Midwest Symposium on Circuits and Systems (Cat. No.99CH36356), 2000
The CONTROLAB AGV moves autonomously through any type of office environment, avoiding obstacles d... more The CONTROLAB AGV moves autonomously through any type of office environment, avoiding obstacles detected by vision and sonar sensors in real-time, and follows requests issued by any client station connected to the office network This paper presents the CONTROLAB client-server architecture using the Internet, the techniques employed for wireless communication between the server and the AGV and the adopted approaches
Proceedings of 1995 IEEE International Conference on Robotics and Automation, 1995
Page 1. C rated System for Intel o Eliana P. L. Aude *, E A .B. Silva *, EP Lopes **, M. E Martin... more Page 1. C rated System for Intel o Eliana P. L. Aude *, E A .B. Silva *, EP Lopes **, M. E Martins *, H. Serdeira * NCE-UFRT* Instituto de Matembtica - UFRT ** PO Box 2324, Rio de Janeiro, RJ - 20001-970, BRAZIL Abstract CONTROLAB ...
International Conference on Robotics and Automation, 1995
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001
This paper proposes a new obstacle avoidance algorithm for the CONTROLAB AGV which uses a similar... more This paper proposes a new obstacle avoidance algorithm for the CONTROLAB AGV which uses a similar strategy adopted by a blind person to avoid obstacles while walking. The AGV moves within an office environment with a known floorplan and uses an "electronic stick" consisting of infrared sensors to detect unknown obstacles. Initially a global potential field function is defined for each floorplan room. While the AGV is moving, the original potential function is modified each time an obstacle is detected by the infrared sensors. This modification is simply performed by the addition of previously calculated potential field values on a grid which represents the room working area. The interesting aspects of the proposed approach are that the potential function adaptation involves very low computational burden, the algorithm is free from local minima, the obstacles can have any shape and low cost sensors can be used to detect obstacles.
SPIE Proceedings, 1999
This paper discusses the integration of intelligent systems and the use of sensor fusion within a... more This paper discusses the integration of intelligent systems and the use of sensor fusion within a Multi-Level Fusion Architecture (MUFA) designed for controlling the navigation of a tele-commanded Autonomous Guided Vehicle (AGV). The AGV can move autonomously within any office environment, following instructions issued by client stations connected to the Internet and reacting accordingly to different situations found in the real world. The modules which integrate the MUFA architecture are discussed and special emphasis is given to the role played by the intelligent obstacle avoidance procedure. The AGV detailed trajectory is firstly defmed by a rule-based PFIELD algorithm from sub-goals established by a global trajectory planner. However, when an unexpected obstacle is detected by the neural network which performs the fusion of information produced by the vision system and sonar sensors, the obstacle avoidance procedure uses a special set of rules to redefine the AGV trajectory. The architecture of the neural network used for performing the sensor fusion function and the adopted set of rules are discussed. In addition, results of some simulation experiments demonstrate the ability ofthe system to define a new global trajectory when unexpected blocked regions are detected.
Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), 1999
l%ispaper proposes a MVi'ti-levelFusion Architecture @4UFA) for controlling the navigation of a t... more l%ispaper proposes a MVi'ti-levelFusion Architecture @4UFA) for controlling the navigation of a telecommanded Autonomous Guided Vehicle (AG~. The architecture combines ia%as derived from the jimahental concepts of sensor @ion and distributed intelligence. The fmus of the work is the development of an intelligent navigation system for a tricycle hive AGV with the abili~to move autonomously w-thin any ofice environment, follm"ng instructions issued by client stations connected to the ofice network and reacting accordingly to dl~erent situations found in the real world l%e modules which integrate the MUFA architecture are discussed and results of some simulation expem"ments are presented
Eighth International IFAC Symposium on Robot Control, 2006, 2006
This paper presents a new algorithm used to identify door states autonomously and without any pre... more This paper presents a new algorithm used to identify door states autonomously and without any previous information about door aperture, color and texture or about the location of the robot. Our approach imposes no constraint on the aperture of the door and enables a robot to identify doors in any state ranging from totally open, widely open and slightly open to closed using visual information. In this proposed solution, the robot is also able to judge whether the aperture of the door is suitable for crossing and to drive itself safely across the door.
Applications of Artificial Intelligence 1993: Machine Vision and Robotics, 1993
ABSTRACT
CONTROLAB is an environment which integrates intelligent systems and control algorithms aiming at... more CONTROLAB is an environment which integrates intelligent systems and control algorithms aiming at applications in the area of robotics. Within CONTROLAB, two neural network architectures based on the backpropagation and the recursive models are proposed for the implementation of a robust speaker-independent word recognition system. The robustness of the system using the backpropagation network has been largely verified through use by children and adults in a totally uncontrolled environment such as large public halls for the exhibition of new technology products. Initial experimental results with the recursive network show that it will be able to overcome the backpropagation network major drawback, which is the frequent generation of false alarms. In addition, within CONTROLAB, a multivariable self-tuning algorithm is proposed to perform high-precision control of the trajectory, to be followed by a robot arm. High-precision control is achieved due to the ability of the algorithm to ...
The Controlab AGV is an electric tricycle vehicle that, following issues from client stations con... more The Controlab AGV is an electric tricycle vehicle that, following issues from client stations connected to the network office, moves autonomously through an office environment with a known floorplan and uses an electronic stick, which consists of infrared sensors, to detect and avoid unknown obstacles. This paper presents the global real-time solution for the Controlab AGV to move smoothly within an adaptive grided potential field which changes each time the electronic stick detects a collision point. This modification is simply performed by the addition of previously calculated potential field values on a grid which represents the room working area. The trajectory between two calculated field values is a continuous-curvature path given by a fifth order polynomial function. The interpolating conditions of the fifth order polynomial function have to fit in with the AGV dynamics so as to allow complex motions to be performed. The real-time AGV motion system consists of periodic and ap...
This paper discusses the integration of intelligent systems and the use of sensor fusion within a... more This paper discusses the integration of intelligent systems and the use of sensor fusion within a Multi-Level Fusion Architecture (MUFA) designed for controlling the navigation of a tele-commanded Autonomous Guided Vehicle (AGV). The AGV can move autonomously within any office environment, following instructions issued by client stations connected to the Internet and reacting accordingly to different situations found in the real world. The modules which integrate the MUFA architecture are discussed and special emphasis is given to the role played by the intelligent obstacle avoidance procedure. The AGV detailed trajectory is firstly defmed by a rule-based PFIELD algorithm from sub-goals established by a global trajectory planner. However, when an unexpected obstacle is detected by the neural network which performs the fusion of information produced by the vision system and sonar sensors, the obstacle avoidance procedure uses a special set of rules to redefine the AGV trajectory. The architecture of the neural network used for performing the sensor fusion function and the adopted set of rules are discussed. In addition, results of some simulation experiments demonstrate the ability ofthe system to define a new global trajectory when unexpected blocked regions are detected.
l%ispaper proposes a MVi'ti-levelFusion Architecture @4UFA) for controlling the navigation of a t... more l%ispaper proposes a MVi'ti-levelFusion Architecture @4UFA) for controlling the navigation of a telecommanded Autonomous Guided Vehicle (AG~. The architecture combines ia%as derived from the jimahental concepts of sensor @ion and distributed intelligence. The fmus of the work is the development of an intelligent navigation system for a tricycle hive AGV with the abili~to move autonomously w-thin any ofice environment, follm"ng instructions issued by client stations connected to the ofice network and reacting accordingly to dl~erent situations found in the real world l%e modules which integrate the MUFA architecture are discussed and results of some simulation expem"ments are presented
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Papers by Mario Ferreira Martins