Mobile Sensor Networks based on Autonomous Platforms for Homeland Security
|
|
- Adrian White
- 6 years ago
- Views:
Transcription
1 Mobile Sensor Networks based on Autonomous Platforms for Homeland Security A. Buonanno (+), M. D Urso (+),G.Prisco (+), M.Felaco (+,*) (+)SELEX Sistemi Integrati S.p.A. Via Circumvallazione Esterna di Napoli, zona ASI, I Giugliano, Napoli, Italy {anbuonanno, mdurso }@selex-si.com E. F. Meliadò (*), M. Mattei (*), F. Palmieri (*), D. Ciuonzo (*) (*)Seconda Università degli Studi di Napoli Via Roma 29, 81031, Aversa, Caserta Abstract The development of intelligent surveillance systems is an active research area of increasing interest. In recent years, autonomous or semi-autonomous mobile robots have been adopted as useful means to reduce fixed installations and number of devices needed for surveillance of a given area. In this context SELEX Sistemi Integrati is investigating the possibility to use robots-sensors systems to improve the monitoring of large and populated indoor areas. In particular, the joint use of the Swarm Logic and heterogeneous sensors, some installed at strategic points of the infrastructure and other installed on mobile robots, allows the creation of a very dynamic network of cooperating sensors, that is able to ensure a high level of protection and a fast reaction to threats. In this paper an integrated intelligent system based on swarm logic to improve monitoring performance of large critical infrastructures such as airport terminals, warehouses, railway stations, production facilities is presented. The adopted system architecture, consisting of two hierarchical levels, is introduced and discussed. In each of these levels novel aspects, developed by the team, are present. T I. INTRODUCTION AND MOTIVATIONS HE terrorism events of the last decade shifted the attention from the boundaries to the heart of nations, focusing on all those infrastructures that are central for economic, political, cultural or religious interests. These circumstances push toward the development of new security systems, more sophisticated and effective but also cheaper, due to the increasing number of critical infrastructures to be kept under control. In indoor environments such as airports, warehouses, production plants, etc., the need for automated surveillance systems has stimulated the development of intelligent systems based on mobile sensors, possibly mounted on autonomous or semi-autonomous robots. Differently from traditional nonmobile surveillance devices, those based on mobile robots are still in their initial stage of development, and many issues are under investigations [1-2]. Robots expand significantly the capabilities of surveillance systems with their active role in the environment sensing, consisting of the interaction with both humans (to perform adaptive tasks) and other robots (to perform coordinated tasks). The use of mobile robots allows to obtain an easily reconfigurable solution able to suit the characteristics of different operating scenarios, as: different structural constraints; different human behaviours; different threats to detect; different reactions; different environments. Furthermore, the use of mobile platforms as active mobile sensors needs for a complex system with a modular architecture, flexible and open to integration with different sensors and functionalities. To achieve this goal, SELEX Sistemi Integrati is developing a new easily integrable platform into the existing security systems. Particular attention will be devoted to the development of mobile robotic sensor networks for monitoring large and densely populated areas and for increasing the capability of human operators working in critical situations like anti-fire, antiterrorism, police missions and on the battlefield (Figure 1). Different hardware and software components are under evaluation (Figure 2), while parallel investigations on suitable algorithms and methodologies are being carried out. Figure 1 New semi-autonomous robotic systems. One possible architecture for monitoring of large and populated area, such as airport terminal, is the subject of the first part of the paper. In this part, the algorithms for mobile robot guidance and navigation in a partially known 2012 CNIT Tyrrhenian Workshop
2 environment, already introduced in [3], are briefly recalled. In the second part, the decision fusion algorithms to track risky targets in a dynamic environment through distributed wireless sensors are introduced. The proposed algorithms are the basis for an optimal allocation of the mobile sensing resources to minimize the probability of false alarms and missed detections. Figure 2 Some Robotic platforms evaluated by the team for the development of the surveillance system. II. THE SYSTEM ARCHITECTURE The possibility to monitor wide and densely populated areas such as airport terminals, train and naval stations, warehouses, production plants, sport stadiums, etc., requires the concurrence of different technologies and a high level of integration between them. Modern systems can take advantage of networks of sensors installed both on infrastructures and mobile devices as robots or human operators. In particular, data fusion systems can maximize the effective information, and increase the situational awareness of the operators to take rapid and efficient decisions. SELEX-SI is studying new technologies and methodologies based on mobile robot platforms to introduce into a novel surveillance system including the command and control systems architectures already developed. The proposed architecture of such a system is composed of two hierarchic layers (Figure 3). The higher level layer, based on a net-centric topology, is the layer closest to the security human operators and is devoted to the following tasks. Data fusion: extraction of synthetic information for risk evaluation; Decision making and interface with human operators to increase situational awareness; Classification of targets and tracking of the risky ones. The lower layer (see also Figure 4), distributed among fixed sensors and the robot swarm, is involved in very important tasks: Sensing resource optimization: optimization of mobile devices position to minimize false or missed alarms in a cooperative approach; Tasks Management: assigning and managing dynamically tasks between different platform according to priority of the task and platform capability; Detection of system faults: detection and management of the faults reassigned appropriately the tasks. Furthermore, each robot of the swarm must be able to perform the following tasks: Map Building; Path planning; Obstacle avoidance; Self localization; Motion Control; Detection of robot faults. We note that this is a crucial part of the system. Indeed, to provide the previous capability to each robot of the swarm is essential to obtain the proposed goal, and this is an hard problem due to the complexity of considered scenarios. The presence of different tasks to be accomplished by the robotic agents can produce conflicts in decision making. Resolution of conflicts can be obtained by using competitive or cooperative approaches. A possibility under analysis is the adoption of the Real Time Swarm Intelligence Platform (RT- SIP) for resolution of conflicts. Figure 3 The hierarchic layers of the proposed architecture for the autonomous surveillance system.
3 RT-SIP is an innovative multi-agent middleware which provides cooperation and coordination services based upon the Swarm Intelligence model. Thanks to the adoption of a datacentric, server-less architecture, based on the Real Time Data Distribution Services (RT-DDS) standard, the RT-SIP is interoperable and can be included in the network-centric systems. The RT-SIP complements the adaptive control of Swarm Intelligence to the scalability, dependability and predictability of the RT-DDS, thus resulting into a valuable component of systems that needs to operate in complex and dynamic scenarios. environmental information. According to our definition, a map is represented by a set of geometric primitives, suitable to describe most of structured indoor environments. In the paper we propose the use of line segments as basic geometrical primitive. In Figure 6 the flow-chart of the proposed algorithm is showed. Start LS acquisition Local segment based map extraction Estimation of the laser pose and its orientation Fusion of the Local map and Global map last scan? N Y Stop Figure 4 Task of the lower layer. Figure 6 - Flow-chart of the proposed algorithm III. THE SYSTEM ARCHITECTURE In this section we briefly re-introduce the key points of the algorithms for mobile robot guidance and navigation in a partially known environment. A. Map Building via Laser Rangefinder The purpose of this algorithm is to obtain a Global Map that represents the whole environment, exploiting Local Maps that are extracted from the laser scanner measures [4-7] (Figure 5). More detail are in [3]. B. Robots Self Localization A reliable estimation of the robot position is another key point in the implementation of the proposed hybrid sensing system. The presence of a dynamic environment with a lot of fixed and moving obstacles makes this problem very complex. One of the most common methods adopted to perform this fusion exploits the Extended Kalman Filter (EKF, [8]). Unscented Kalman Filter (UKF [3]) has been demonstrated to work much better than EKF when system dynamics and output function are nonlinear. We have implemented a dynamic variant of the UKF that has shown to be robust to occasional changes of the environment such as opened/closed doors or walking people [3]. Figure 5 Superimposition of the obtained Global map with an available building map More specifically, a local map is built from a scanner acquisition and it is used to update the global map, so that in each step the global map contains all the acquired C. Path Planning In the proposed approach, based on potential fields [9-11], a fluid mechanics similitude to generate the control vector valued function is used for both obtaining the nominal control sequence to reach the target positions in presence of known obstacles, and updating the control vector map in presence of unknown obstacles (Figure 7). Control actions are computed by solving in the geometrical domain of interest, with Finite Elements Methods, the following problem: 2 φ = 0
4 subject to the Dirichlet s boundary conditions: ( ) = 1 obstacle φ. φ ( arg ) = 0 t The control action map is directed along the gradient of the solution v = λ φ. et leads to the so called Parallel Range Limited Marginalization (PRLM) algorithm. These algorithms have already shown good performances when they are used with fixed sensors, we will extend their utilization in the case of mobile sensors (Figure 8). The proposed algorithms have the further advantage that they allow to decentralize part of the fusion control decisions to fusion devices covering different zones of the monitored area. Figure 1. Figure 7 Example of vector field of control actions driving mobile robots to targets without obstacles Figure 2. Figure 8 :Block diagram of the considered system. IV. RISKY TARGETS DETECTION ALGORITHMS An important aspect for the high level automation system is the detection of potentially risky targets moving in the monitored area. The possibility to increase the reliability of this detection by means of mobile sensing devices has to be evaluated starting from the analysis of possible risk classification algorithms. Assume that the high level system has to track and classify N different targets moving into the area of interest. Two sub-optimal decision fusion algorithms, namely the Range Limited Marginalization (RLM) and its parallelized form (PRLM) [12] are under investigation, which are based on the separation of the fusion process of each target. An optimal decision fusion algorithm for multi-target classification requires [13] to calculate the Bayes recursive update, this optimal approach cannot be implemented with reasonable time responses. We proposed two sub-optimal approach to obtain a reduced complexity, first of all we update the classification of each target separately from the others, this clearly leads to sub-optimal performance related to the error probability, but that can be implemented in practice. This proposed algorithm, named Range Limited Marginalization (RLM), starts from the exact computation formula of the N marginal posteriors through the Bayes update obtained by the conditioning chain rule [14], due to space-time independency of decisions which are transmitted from the sensor. After, identifying a subset of targets which are inside the maximum detection range of the sensor at each instant of time, we approximate that each conditional distribution for each sensor can be implemented in parallel with each other. This V. CONCLUSIONS SELEX Sistemi Integrati S.p.A is studying new technologies and methodologies to be implemented into a novel surveillance system based on swarm logic that will be integrated in the higher level command and control systems architectures already developed by the company or under development such as in that of the Airport Turn-Key system. The proposed architecture makes use of wireless sensor networks and sensing devices mounted on mobile autonomous or semi-autonomous, terrestrial or flying robots. Modern techniques and technologies will be integrated in such a system. An overview of the proposed hierarchic architecture and of some investigations carried out in the field of mobile robot guidance, navigation, and localization, and in the field of indoor map building is provided. Future work will be devoted to investigate the possibility of using alternative techniques for path generation of robot, and particle filters localization algorithms. Moreover, all the developed algorithms will be tested and optimized in terms of computational cost proving the effectiveness in real operative scenarios. To improve the efficiency of the surveillance system and to optimize the task assignment among different robots, also solutions diverse of the use of RT-SIP and logic swarm will be studied. This last problem finds several points of contact with the decision fusion algorithms proposed to classify risky targets in a multi sensor dynamic environment. All the proposed methodologies are under assessment by using two experimental set-up, one located in Centro Eccellenza Grandi Sistemi of SELEX Sistemi Integrati and the other located in the Test Bed room of the SELEX Sistemi integrati
5 in Giugliano in Campania, with the support of Mechanical Engineering Department of the Second University of Naples and of Sistemi Software Integrati. REFERENCES [1] H. Everett, Robotic security systems, IEEE Instruments and Measurements Magazine, vol. 6, no. 4, pp , December [2] T. Duckett, G. Cielniak, H. Andreasson, L. Jun, A. Lilienthal, P. Biber, T. Martínez, Robotic Security Guard - Autonomous Surveillance and Remote Perception, Proceedings of IEEE International Workshop on Safety, Security, and Rescue Robotics, Bonn, Germany, May [3] POLARIS Innovation Journal N 8 [4] F. Amigoni, S. Gasparini, M. Gini, Building Segment-Based Maps Without Pose Information, Proceedings of the IEEE, vol.94, no.7, pp , July [5] Zezhong Xu, Jilin Liu, Zhiyu Xiang, Han Li, Map building for indoor environment with laser range scanner, Proceedings of IEEE 5th Int. Conf. on Intelligent Transportation Systems, pp , [6] L. Zalud, L. Kopecny, T. Neuzil, Laser proximity scanner correlation based method for cooperative localization and map building, Proceedings of th Int. Workshop on Advanced Motion Control, pp , [7] S. F. Hernandez-Alamilla, E. F. Morales, Global Localization of Mobile Robots for Indoor Environments Using Natural Landmarks, Proceedings of 2006 IEEE Conf. on Robotics, Automation and Mechatronis, pp.1-6, Dec [8] Crowley, J.L., (1989). World Modeling and Position Estimation for a Mobile Robot Using Ultrasonic Ranging. IEEE Int. Conf. on Robotics and Automation (ICRA), Scottsdale, AZ, USA, 1989 [9] G. Antonelli, and S. Chiaverini, Kinematic control of platoons of autonomous vehicles, IEEE Trans. Robotics, Vol. 22, No.6, pp , [10] Hwand, Y., K., and Ahuja, N., A Potential Field Approach to Path Planning, IEEE Trans. Robot. Automat., Vol. 6, 1992, pp [11] Cen, Y., Wang, L., and Zhang, H., Real-time Obstacle Avoidance Strategy for Mobile Robot Based On Improved Coordinating Potential Field with Genetic Algorithm, Proceedings of 16th IEEE Intern. Conf. on Control Appl., Singapore, 1-3 October [12] D. Ciuonzo, A. Buonanno, M. D Urso and A.N. Palmieri, Distributed Classification of Multiple Moving Targets with Binary Wireless Sensor Networks. International Conference on Information Fusion, Chicago, USA, 5-8 July [13] J.H. Kotecha, V. Ramachandran, and A.M. Sayeed. Distributed multitarget classification in wireless sensor networks. IEEE Journal on Selected Areas in Communications, 23(4): , april [14] T.M. Cover and J.A. Thomas. Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing). Wiley- Interscience, 2006.
* Intelli Robotic Wheel Chair for Specialty Operations & Physically Challenged
ADVANCED ROBOTICS SOLUTIONS * Intelli Mobile Robot for Multi Specialty Operations * Advanced Robotic Pick and Place Arm and Hand System * Automatic Color Sensing Robot using PC * AI Based Image Capturing
More informationNCCT IEEE PROJECTS ADVANCED ROBOTICS SOLUTIONS. Latest Projects, in various Domains. Promise for the Best Projects
NCCT Promise for the Best Projects IEEE PROJECTS in various Domains Latest Projects, 2009-2010 ADVANCED ROBOTICS SOLUTIONS EMBEDDED SYSTEM PROJECTS Microcontrollers VLSI DSP Matlab Robotics ADVANCED ROBOTICS
More informationAN AUTONOMOUS SIMULATION BASED SYSTEM FOR ROBOTIC SERVICES IN PARTIALLY KNOWN ENVIRONMENTS
AN AUTONOMOUS SIMULATION BASED SYSTEM FOR ROBOTIC SERVICES IN PARTIALLY KNOWN ENVIRONMENTS Eva Cipi, PhD in Computer Engineering University of Vlora, Albania Abstract This paper is focused on presenting
More informationPlanning in autonomous mobile robotics
Sistemi Intelligenti Corso di Laurea in Informatica, A.A. 2017-2018 Università degli Studi di Milano Planning in autonomous mobile robotics Nicola Basilico Dipartimento di Informatica Via Comelico 39/41-20135
More informationSPQR RoboCup 2016 Standard Platform League Qualification Report
SPQR RoboCup 2016 Standard Platform League Qualification Report V. Suriani, F. Riccio, L. Iocchi, D. Nardi Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti Sapienza Università
More informationFuzzy-Heuristic Robot Navigation in a Simulated Environment
Fuzzy-Heuristic Robot Navigation in a Simulated Environment S. K. Deshpande, M. Blumenstein and B. Verma School of Information Technology, Griffith University-Gold Coast, PMB 50, GCMC, Bundall, QLD 9726,
More informationArtificial Beacons with RGB-D Environment Mapping for Indoor Mobile Robot Localization
Sensors and Materials, Vol. 28, No. 6 (2016) 695 705 MYU Tokyo 695 S & M 1227 Artificial Beacons with RGB-D Environment Mapping for Indoor Mobile Robot Localization Chun-Chi Lai and Kuo-Lan Su * Department
More informationCS 599: Distributed Intelligence in Robotics
CS 599: Distributed Intelligence in Robotics Winter 2016 www.cpp.edu/~ftang/courses/cs599-di/ Dr. Daisy Tang All lecture notes are adapted from Dr. Lynne Parker s lecture notes on Distributed Intelligence
More informationAn Agent-based Heterogeneous UAV Simulator Design
An Agent-based Heterogeneous UAV Simulator Design MARTIN LUNDELL 1, JINGPENG TANG 1, THADDEUS HOGAN 1, KENDALL NYGARD 2 1 Math, Science and Technology University of Minnesota Crookston Crookston, MN56716
More informationCAPACITIES FOR TECHNOLOGY TRANSFER
CAPACITIES FOR TECHNOLOGY TRANSFER The Institut de Robòtica i Informàtica Industrial (IRI) is a Joint University Research Institute of the Spanish Council for Scientific Research (CSIC) and the Technical
More informationARCHITECTURE AND MODEL OF DATA INTEGRATION BETWEEN MANAGEMENT SYSTEMS AND AGRICULTURAL MACHINES FOR PRECISION AGRICULTURE
ARCHITECTURE AND MODEL OF DATA INTEGRATION BETWEEN MANAGEMENT SYSTEMS AND AGRICULTURAL MACHINES FOR PRECISION AGRICULTURE W. C. Lopes, R. R. D. Pereira, M. L. Tronco, A. J. V. Porto NepAS [Center for Teaching
More informationBehaviour-Based Control. IAR Lecture 5 Barbara Webb
Behaviour-Based Control IAR Lecture 5 Barbara Webb Traditional sense-plan-act approach suggests a vertical (serial) task decomposition Sensors Actuators perception modelling planning task execution motor
More informationDistributed Vision System: A Perceptual Information Infrastructure for Robot Navigation
Distributed Vision System: A Perceptual Information Infrastructure for Robot Navigation Hiroshi Ishiguro Department of Information Science, Kyoto University Sakyo-ku, Kyoto 606-01, Japan E-mail: ishiguro@kuis.kyoto-u.ac.jp
More informationMobile Robots Exploration and Mapping in 2D
ASEE 2014 Zone I Conference, April 3-5, 2014, University of Bridgeport, Bridgpeort, CT, USA. Mobile Robots Exploration and Mapping in 2D Sithisone Kalaya Robotics, Intelligent Sensing & Control (RISC)
More informationReal-time Systems in Tokamak Devices. A case study: the JET Tokamak May 25, 2010
Real-time Systems in Tokamak Devices. A case study: the JET Tokamak May 25, 2010 May 25, 2010-17 th Real-Time Conference, Lisbon 1 D. Alves 2 T. Bellizio 1 R. Felton 3 A. C. Neto 2 F. Sartori 4 R. Vitelli
More informationCMRE La Spezia, Italy
Innovative Interoperable M&S within Extended Maritime Domain for Critical Infrastructure Protection and C-IED CMRE La Spezia, Italy Agostino G. Bruzzone 1,2, Alberto Tremori 1 1 NATO STO CMRE& 2 Genoa
More informationMulti-Robot Coordination. Chapter 11
Multi-Robot Coordination Chapter 11 Objectives To understand some of the problems being studied with multiple robots To understand the challenges involved with coordinating robots To investigate a simple
More informationMulti-Platform Soccer Robot Development System
Multi-Platform Soccer Robot Development System Hui Wang, Han Wang, Chunmiao Wang, William Y. C. Soh Division of Control & Instrumentation, School of EEE Nanyang Technological University Nanyang Avenue,
More informationUnmanned Ground Military and Construction Systems Technology Gaps Exploration
Unmanned Ground Military and Construction Systems Technology Gaps Exploration Eugeniusz Budny a, Piotr Szynkarczyk a and Józef Wrona b a Industrial Research Institute for Automation and Measurements Al.
More informationRearrangement task realization by multiple mobile robots with efficient calculation of task constraints
2007 IEEE International Conference on Robotics and Automation Roma, Italy, 10-14 April 2007 WeA1.2 Rearrangement task realization by multiple mobile robots with efficient calculation of task constraints
More informationBluetooth Low Energy Sensing Technology for Proximity Construction Applications
Bluetooth Low Energy Sensing Technology for Proximity Construction Applications JeeWoong Park School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Dr. N.W., Atlanta,
More informationExperiments in the Coordination of Large Groups of Robots
Experiments in the Coordination of Large Groups of Robots Leandro Soriano Marcolino and Luiz Chaimowicz VeRLab - Vision and Robotics Laboratory Computer Science Department - UFMG - Brazil {soriano, chaimo}@dcc.ufmg.br
More informationS.P.Q.R. Legged Team Report from RoboCup 2003
S.P.Q.R. Legged Team Report from RoboCup 2003 L. Iocchi and D. Nardi Dipartimento di Informatica e Sistemistica Universitá di Roma La Sapienza Via Salaria 113-00198 Roma, Italy {iocchi,nardi}@dis.uniroma1.it,
More informationSIMULTANEOUS OBSTACLE DETECTION FOR MOBILE ROBOTS AND ITS LOCALIZATION FOR AUTOMATIC BATTERY RECHARGING
SIMULTANEOUS OBSTACLE DETECTION FOR MOBILE ROBOTS AND ITS LOCALIZATION FOR AUTOMATIC BATTERY RECHARGING *Sang-Il Gho*, Jong-Suk Choi*, *Ji-Yoon Yoo**, Mun-Sang Kim* *Department of Electrical Engineering
More informationIndoor navigation with smartphones
Indoor navigation with smartphones REinEU2016 Conference September 22 2016 PAVEL DAVIDSON Outline Indoor navigation system for smartphone: goals and requirements WiFi based positioning Application of BLE
More informationLocalisation et navigation de robots
Localisation et navigation de robots UPJV, Département EEA M2 EEAII, parcours ViRob Année Universitaire 2017/2018 Fabio MORBIDI Laboratoire MIS Équipe Perception ique E-mail: fabio.morbidi@u-picardie.fr
More informationPerception platform and fusion modules results. Angelos Amditis - ICCS and Lali Ghosh - DEL interactive final event
Perception platform and fusion modules results Angelos Amditis - ICCS and Lali Ghosh - DEL interactive final event 20 th -21 st November 2013 Agenda Introduction Environment Perception in Intelligent Transport
More informationCombining Air Defense and Missile Defense
Brigadier General Armament Corp (ret.) Michel Billard Thalesraytheonsystems 1 Avenue Carnot 91883 MASSY CEDEX FRANCE michel.billard@thalesraytheon-fr.com ABSTRACT A number of NATO Nations will use fixed
More informationMotion Control of a Three Active Wheeled Mobile Robot and Collision-Free Human Following Navigation in Outdoor Environment
Proceedings of the International MultiConference of Engineers and Computer Scientists 2016 Vol I,, March 16-18, 2016, Hong Kong Motion Control of a Three Active Wheeled Mobile Robot and Collision-Free
More informationPath Planning in Dynamic Environments Using Time Warps. S. Farzan and G. N. DeSouza
Path Planning in Dynamic Environments Using Time Warps S. Farzan and G. N. DeSouza Outline Introduction Harmonic Potential Fields Rubber Band Model Time Warps Kalman Filtering Experimental Results 2 Introduction
More informationSubsumption Architecture in Swarm Robotics. Cuong Nguyen Viet 16/11/2015
Subsumption Architecture in Swarm Robotics Cuong Nguyen Viet 16/11/2015 1 Table of content Motivation Subsumption Architecture Background Architecture decomposition Implementation Swarm robotics Swarm
More informationWednesday, October 29, :00-04:00pm EB: 3546D. TELEOPERATION OF MOBILE MANIPULATORS By Yunyi Jia Advisor: Prof.
Wednesday, October 29, 2014 02:00-04:00pm EB: 3546D TELEOPERATION OF MOBILE MANIPULATORS By Yunyi Jia Advisor: Prof. Ning Xi ABSTRACT Mobile manipulators provide larger working spaces and more flexibility
More informationA simple embedded stereoscopic vision system for an autonomous rover
In Proceedings of the 8th ESA Workshop on Advanced Space Technologies for Robotics and Automation 'ASTRA 2004' ESTEC, Noordwijk, The Netherlands, November 2-4, 2004 A simple embedded stereoscopic vision
More informationSummary of robot visual servo system
Abstract Summary of robot visual servo system Xu Liu, Lingwen Tang School of Mechanical engineering, Southwest Petroleum University, Chengdu 610000, China In this paper, the survey of robot visual servoing
More informationCS594, Section 30682:
CS594, Section 30682: Distributed Intelligence in Autonomous Robotics Spring 2003 Tuesday/Thursday 11:10 12:25 http://www.cs.utk.edu/~parker/courses/cs594-spring03 Instructor: Dr. Lynne E. Parker ½ TA:
More informationIntelligent Power Economy System (Ipes)
American Journal of Engineering Research (AJER) e-issn : 2320-0847 p-issn : 2320-0936 Volume-02, Issue-08, pp-108-114 www.ajer.org Research Paper Open Access Intelligent Power Economy System (Ipes) Salman
More informationTHE NEPTUS C4ISR FRAMEWORK: MODELS, TOOLS AND EXPERIMENTATION. Gil M. Gonçalves and João Borges Sousa {gil,
THE NEPTUS C4ISR FRAMEWORK: MODELS, TOOLS AND EXPERIMENTATION Gil M. Gonçalves and João Borges Sousa {gil, jtasso}@fe.up.pt Faculdade de Engenharia da Universidade do Porto Rua Dr. Roberto Frias s/n 4200-465
More informationKey-Words: - Fuzzy Behaviour Controls, Multiple Target Tracking, Obstacle Avoidance, Ultrasonic Range Finders
Fuzzy Behaviour Based Navigation of a Mobile Robot for Tracking Multiple Targets in an Unstructured Environment NASIR RAHMAN, ALI RAZA JAFRI, M. USMAN KEERIO School of Mechatronics Engineering Beijing
More informationObstacle avoidance based on fuzzy logic method for mobile robots in Cluttered Environment
Obstacle avoidance based on fuzzy logic method for mobile robots in Cluttered Environment Fatma Boufera 1, Fatima Debbat 2 1,2 Mustapha Stambouli University, Math and Computer Science Department Faculty
More informationApplications & Theory
Applications & Theory Azadeh Kushki azadeh.kushki@ieee.org Professor K N Plataniotis Professor K.N. Plataniotis Professor A.N. Venetsanopoulos Presentation Outline 2 Part I: The case for WLAN positioning
More informationSwarm Intelligence W7: Application of Machine- Learning Techniques to Automatic Control Design and Optimization
Swarm Intelligence W7: Application of Machine- Learning Techniques to Automatic Control Design and Optimization Learning to avoid obstacles Outline Problem encoding using GA and ANN Floreano and Mondada
More informationAutonomous and Autonomic Systems: With Applications to NASA Intelligent Spacecraft Operations and Exploration Systems
Walt Truszkowski, Harold L. Hallock, Christopher Rouff, Jay Karlin, James Rash, Mike Hinchey, and Roy Sterritt Autonomous and Autonomic Systems: With Applications to NASA Intelligent Spacecraft Operations
More informationUChile Team Research Report 2009
UChile Team Research Report 2009 Javier Ruiz-del-Solar, Rodrigo Palma-Amestoy, Pablo Guerrero, Román Marchant, Luis Alberto Herrera, David Monasterio Department of Electrical Engineering, Universidad de
More informationNAVIGATION OF MOBILE ROBOT USING THE PSO PARTICLE SWARM OPTIMIZATION
Journal of Academic and Applied Studies (JAAS) Vol. 2(1) Jan 2012, pp. 32-38 Available online @ www.academians.org ISSN1925-931X NAVIGATION OF MOBILE ROBOT USING THE PSO PARTICLE SWARM OPTIMIZATION Sedigheh
More informationNTU Robot PAL 2009 Team Report
NTU Robot PAL 2009 Team Report Chieh-Chih Wang, Shao-Chen Wang, Hsiao-Chieh Yen, and Chun-Hua Chang The Robot Perception and Learning Laboratory Department of Computer Science and Information Engineering
More informationOptic Flow Based Skill Learning for A Humanoid to Trap, Approach to, and Pass a Ball
Optic Flow Based Skill Learning for A Humanoid to Trap, Approach to, and Pass a Ball Masaki Ogino 1, Masaaki Kikuchi 1, Jun ichiro Ooga 1, Masahiro Aono 1 and Minoru Asada 1,2 1 Dept. of Adaptive Machine
More informationinteractive IP: Perception platform and modules
interactive IP: Perception platform and modules Angelos Amditis, ICCS 19 th ITS-WC-SIS76: Advanced integrated safety applications based on enhanced perception, active interventions and new advanced sensors
More informationEE631 Cooperating Autonomous Mobile Robots. Lecture 1: Introduction. Prof. Yi Guo ECE Department
EE631 Cooperating Autonomous Mobile Robots Lecture 1: Introduction Prof. Yi Guo ECE Department Plan Overview of Syllabus Introduction to Robotics Applications of Mobile Robots Ways of Operation Single
More informationCollective Robotics. Marcin Pilat
Collective Robotics Marcin Pilat Introduction Painting a room Complex behaviors: Perceptions, deductions, motivations, choices Robotics: Past: single robot Future: multiple, simple robots working in teams
More informationResearch Proposal: Autonomous Mobile Robot Platform for Indoor Applications :xwgn zrvd ziad mipt ineyiil zinepehe`e zciip ziheaex dnxethlt
Research Proposal: Autonomous Mobile Robot Platform for Indoor Applications :xwgn zrvd ziad mipt ineyiil zinepehe`e zciip ziheaex dnxethlt Igal Loevsky, advisor: Ilan Shimshoni email: igal@tx.technion.ac.il
More informationInternational Journal of Informative & Futuristic Research ISSN (Online):
Reviewed Paper Volume 2 Issue 4 December 2014 International Journal of Informative & Futuristic Research ISSN (Online): 2347-1697 A Survey On Simultaneous Localization And Mapping Paper ID IJIFR/ V2/ E4/
More informationChapter 1 Introduction
Chapter 1 Introduction 1.1Motivation The past five decades have seen surprising progress in computing and communication technologies that were stimulated by the presence of cheaper, faster, more reliable
More informationDynamic Data-Driven Adaptive Sampling and Monitoring of Big Spatial-Temporal Data Streams for Real-Time Solar Flare Detection
Dynamic Data-Driven Adaptive Sampling and Monitoring of Big Spatial-Temporal Data Streams for Real-Time Solar Flare Detection Dr. Kaibo Liu Department of Industrial and Systems Engineering University of
More informationMULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT
MULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT F. TIECHE, C. FACCHINETTI and H. HUGLI Institute of Microtechnology, University of Neuchâtel, Rue de Tivoli 28, CH-2003
More informationAutonomous Localization
Autonomous Localization Jennifer Zheng, Maya Kothare-Arora I. Abstract This paper presents an autonomous localization service for the Building-Wide Intelligence segbots at the University of Texas at Austin.
More informationAn Agent-Based Architecture for an Adaptive Human-Robot Interface
An Agent-Based Architecture for an Adaptive Human-Robot Interface Kazuhiko Kawamura, Phongchai Nilas, Kazuhiko Muguruma, Julie A. Adams, and Chen Zhou Center for Intelligent Systems Vanderbilt University
More informationImperfect Monitoring in Multi-agent Opportunistic Channel Access
Imperfect Monitoring in Multi-agent Opportunistic Channel Access Ji Wang Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements
More informationHybrid Positioning through Extended Kalman Filter with Inertial Data Fusion
Hybrid Positioning through Extended Kalman Filter with Inertial Data Fusion Rafiullah Khan, Francesco Sottile, and Maurizio A. Spirito Abstract In wireless sensor networks (WSNs), hybrid algorithms are
More informationMulti-robot Formation Control Based on Leader-follower Method
Journal of Computers Vol. 29 No. 2, 2018, pp. 233-240 doi:10.3966/199115992018042902022 Multi-robot Formation Control Based on Leader-follower Method Xibao Wu 1*, Wenbai Chen 1, Fangfang Ji 1, Jixing Ye
More informationVision-based Localization and Mapping with Heterogeneous Teams of Ground and Micro Flying Robots
Vision-based Localization and Mapping with Heterogeneous Teams of Ground and Micro Flying Robots Davide Scaramuzza Robotics and Perception Group University of Zurich http://rpg.ifi.uzh.ch All videos in
More informationSIS63-Building the Future-Advanced Integrated Safety Applications: interactive Perception platform and fusion modules results
SIS63-Building the Future-Advanced Integrated Safety Applications: interactive Perception platform and fusion modules results Angelos Amditis (ICCS) and Lali Ghosh (DEL) 18 th October 2013 20 th ITS World
More informationJager UAVs to Locate GPS Interference
JIFX 16-1 2-6 November 2015 Camp Roberts, CA Jager UAVs to Locate GPS Interference Stanford GPS Research Laboratory and the Stanford Intelligent Systems Lab Principal Investigator: Sherman Lo, PhD Area
More informationRevolutionizing 2D measurement. Maximizing longevity. Challenging expectations. R2100 Multi-Ray LED Scanner
Revolutionizing 2D measurement. Maximizing longevity. Challenging expectations. R2100 Multi-Ray LED Scanner A Distance Ahead A Distance Ahead: Your Crucial Edge in the Market The new generation of distancebased
More informationMiddleware and Software Frameworks in Robotics Applicability to Small Unmanned Vehicles
Applicability to Small Unmanned Vehicles Daniel Serrano Department of Intelligent Systems, ASCAMM Technology Center Parc Tecnològic del Vallès, Av. Universitat Autònoma, 23 08290 Cerdanyola del Vallès
More informationA MARINE FAULTS TOLERANT CONTROL SYSTEM BASED ON INTELLIGENT MULTI-AGENTS
A MARINE FAULTS TOLERANT CONTROL SYSTEM BASED ON INTELLIGENT MULTI-AGENTS Tianhao Tang and Gang Yao Department of Electrical & Control Engineering, Shanghai Maritime University 1550 Pudong Road, Shanghai,
More informationAUTOMATION & ROBOTICS LABORATORY. Faculty of Electronics and Telecommunications University of Engineering and Technology Vietnam National University
AUTOMATION & ROBOTICS LABORATORY Faculty of Electronics and Telecommunications University of Engineering and Technology Vietnam National University Industrial Robot for Training ED7220 (Korea) SCORBOT
More informationUsing BIM Geometric Properties for BLE-based Indoor Location Tracking
Using BIM Geometric Properties for BLE-based Indoor Location Tracking JeeWoong Park a, Kyungki Kim b, Yong K. Cho c, * a School of Civil and Environmental Engineering, Georgia Institute of Technology,
More informationOBJECTIVE OF THE BOOK ORGANIZATION OF THE BOOK
xv Preface Advancement in technology leads to wide spread use of mounting cameras to capture video imagery. Such surveillance cameras are predominant in commercial institutions through recording the cameras
More informationApplying Multisensor Information Fusion Technology to Develop an UAV Aircraft with Collision Avoidance Model
Applying Multisensor Information Fusion Technology to Develop an UAV Aircraft with Collision Avoidance Model by Dr. Buddy H Jeun and John Younker Sensor Fusion Technology, LLC 4522 Village Springs Run
More informationIntegrated Detection and Tracking in Multistatic Sonar
Stefano Coraluppi Reconnaissance, Surveillance, and Networks Department NATO Undersea Research Centre Viale San Bartolomeo 400 19138 La Spezia ITALY coraluppi@nurc.nato.int ABSTRACT An ongoing research
More informationSimulation of a mobile robot navigation system
Edith Cowan University Research Online ECU Publications 2011 2011 Simulation of a mobile robot navigation system Ahmed Khusheef Edith Cowan University Ganesh Kothapalli Edith Cowan University Majid Tolouei
More informationTraffic Control for a Swarm of Robots: Avoiding Group Conflicts
Traffic Control for a Swarm of Robots: Avoiding Group Conflicts Leandro Soriano Marcolino and Luiz Chaimowicz Abstract A very common problem in the navigation of robotic swarms is when groups of robots
More informationA Reconfigurable Guidance System
Lecture tes for the Class: Unmanned Aircraft Design, Modeling and Control A Reconfigurable Guidance System Application to Unmanned Aerial Vehicles (UAVs) y b right aileron: a2 right elevator: e 2 rudder:
More informationDEVELOPMENT OF A ROBOID COMPONENT FOR PLAYER/STAGE ROBOT SIMULATOR
Proceedings of IC-NIDC2009 DEVELOPMENT OF A ROBOID COMPONENT FOR PLAYER/STAGE ROBOT SIMULATOR Jun Won Lim 1, Sanghoon Lee 2,Il Hong Suh 1, and Kyung Jin Kim 3 1 Dept. Of Electronics and Computer Engineering,
More informationAGENT PLATFORM FOR ROBOT CONTROL IN REAL-TIME DYNAMIC ENVIRONMENTS. Nuno Sousa Eugénio Oliveira
AGENT PLATFORM FOR ROBOT CONTROL IN REAL-TIME DYNAMIC ENVIRONMENTS Nuno Sousa Eugénio Oliveira Faculdade de Egenharia da Universidade do Porto, Portugal Abstract: This paper describes a platform that enables
More informationAvailable theses (October 2012) MERLIN Group
Available theses (October 2012) MERLIN Group Politecnico di Milano - Dipartimento di Elettronica e Informazione MERLIN Group 2 Luca Bascetta bascetta@elet.polimi.it Gianni Ferretti ferretti@elet.polimi.it
More informationRescueRobot: Simulating Complex Robots Behaviors in Emergency Situations
RescueRobot: Simulating Complex Robots Behaviors in Emergency Situations Giuseppe Palestra, Andrea Pazienza, Stefano Ferilli, Berardina De Carolis, and Floriana Esposito Dipartimento di Informatica Università
More informationOFFensive Swarm-Enabled Tactics (OFFSET)
OFFensive Swarm-Enabled Tactics (OFFSET) Dr. Timothy H. Chung, Program Manager Tactical Technology Office Briefing Prepared for OFFSET Proposers Day 1 Why are Swarms Hard: Complexity of Swarms Number Agent
More informationTechnical issues of MRL Virtual Robots Team RoboCup 2016, Leipzig Germany
Technical issues of MRL Virtual Robots Team RoboCup 2016, Leipzig Germany Mohammad H. Shayesteh 1, Edris E. Aliabadi 1, Mahdi Salamati 1, Adib Dehghan 1, Danial JafaryMoghaddam 1 1 Islamic Azad University
More informationFunzionalità per la navigazione di robot mobili. Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo
Funzionalità per la navigazione di robot mobili Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo Variability of the Robotic Domain UNIBG - Corso di Robotica - Prof. Brugali Tourist
More informationCSCI 445 Laurent Itti. Group Robotics. Introduction to Robotics L. Itti & M. J. Mataric 1
Introduction to Robotics CSCI 445 Laurent Itti Group Robotics Introduction to Robotics L. Itti & M. J. Mataric 1 Today s Lecture Outline Defining group behavior Why group behavior is useful Why group behavior
More informationUNIVERSIDAD CARLOS III DE MADRID ESCUELA POLITÉCNICA SUPERIOR
UNIVERSIDAD CARLOS III DE MADRID ESCUELA POLITÉCNICA SUPERIOR TRABAJO DE FIN DE GRADO GRADO EN INGENIERÍA DE SISTEMAS DE COMUNICACIONES CONTROL CENTRALIZADO DE FLOTAS DE ROBOTS CENTRALIZED CONTROL FOR
More informationRobotic Systems ECE 401RB Fall 2007
The following notes are from: Robotic Systems ECE 401RB Fall 2007 Lecture 14: Cooperation among Multiple Robots Part 2 Chapter 12, George A. Bekey, Autonomous Robots: From Biological Inspiration to Implementation
More informationFramework Programme 7
Framework Programme 7 1 Joining the EU programmes as a Belarusian 1. Introduction to the Framework Programme 7 2. Focus on evaluation issues + exercise 3. Strategies for Belarusian organisations + exercise
More informationResilient and Accurate Autonomous Vehicle Navigation via Signals of Opportunity
Resilient and Accurate Autonomous Vehicle Navigation via Signals of Opportunity Zak M. Kassas Autonomous Systems Perception, Intelligence, and Navigation (ASPIN) Laboratory University of California, Riverside
More informationPedestrian Navigation System Using. Shoe-mounted INS. By Yan Li. A thesis submitted for the degree of Master of Engineering (Research)
Pedestrian Navigation System Using Shoe-mounted INS By Yan Li A thesis submitted for the degree of Master of Engineering (Research) Faculty of Engineering and Information Technology University of Technology,
More informationTowards Reliable Underwater Acoustic Video Transmission for Human-Robot Dynamic Interaction
Towards Reliable Underwater Acoustic Video Transmission for Human-Robot Dynamic Interaction Dr. Dario Pompili Associate Professor Rutgers University, NJ, USA pompili@ece.rutgers.edu Semi-autonomous underwater
More informationMultisensory Based Manipulation Architecture
Marine Robot and Dexterous Manipulatin for Enabling Multipurpose Intevention Missions WP7 Multisensory Based Manipulation Architecture GIRONA 2012 Y2 Review Meeting Pedro J Sanz IRS Lab http://www.irs.uji.es/
More informationABSTRACT 1. INTRODUCTION
THE APPLICATION OF SOFTWARE DEFINED RADIO IN A COOPERATIVE WIRELESS NETWORK Jesper M. Kristensen (Aalborg University, Center for Teleinfrastructure, Aalborg, Denmark; jmk@kom.aau.dk); Frank H.P. Fitzek
More informationAn Introduction To Modular Robots
An Introduction To Modular Robots Introduction Morphology and Classification Locomotion Applications Challenges 11/24/09 Sebastian Rockel Introduction Definition (Robot) A robot is an artificial, intelligent,
More informationExperimental Cooperative Control of Fixed-Wing Unmanned Aerial Vehicles
Experimental Cooperative Control of Fixed-Wing Unmanned Aerial Vehicles Selcuk Bayraktar, Georgios E. Fainekos, and George J. Pappas GRASP Laboratory Departments of ESE and CIS University of Pennsylvania
More informationAdaptive Action Selection without Explicit Communication for Multi-robot Box-pushing
Adaptive Action Selection without Explicit Communication for Multi-robot Box-pushing Seiji Yamada Jun ya Saito CISS, IGSSE, Tokyo Institute of Technology 4259 Nagatsuta, Midori, Yokohama 226-8502, JAPAN
More informationKeywords: Multi-robot adversarial environments, real-time autonomous robots
ROBOT SOCCER: A MULTI-ROBOT CHALLENGE EXTENDED ABSTRACT Manuela M. Veloso School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213, USA veloso@cs.cmu.edu Abstract Robot soccer opened
More informationWHO. 6 staff people. Tel: / Fax: Website: vision.unipv.it
It has been active in the Department of Electrical, Computer and Biomedical Engineering of the University of Pavia since the early 70s. The group s initial research activities concentrated on image enhancement
More informationTowards Autonomous Planetary Exploration Collaborative Multi-Robot Localization and Mapping in GPS-denied Environments
DLR.de Chart 1 International Technical Symposium on Navigation and Timing (ITSNT) Toulouse, France, 2017 Towards Autonomous Planetary Exploration Collaborative Multi-Robot Localization and Mapping in GPS-denied
More informationReal-time Cooperative Behavior for Tactical Mobile Robot Teams. September 10, 1998 Ronald C. Arkin and Thomas R. Collins Georgia Tech
Real-time Cooperative Behavior for Tactical Mobile Robot Teams September 10, 1998 Ronald C. Arkin and Thomas R. Collins Georgia Tech Objectives Build upon previous work with multiagent robotic behaviors
More informationCNR-ISSIA. ISSIA: Summary Table. Istituto di Studi sui Sistemi Intelligenti per l Automazione, CNR Via G. Amendola 122/D-O Bari, Italy
CNR-ISSIA ISSIA: Summary Table Institute Istituto di Studi sui Sistemi Intelligenti per l Automazione, CNR Via G. Amendola 122/D-O - 70126 Bari, Italy Year of foundation Refererence person Website Dr.
More informationDevelopment of a Sensor-Based Approach for Local Minima Recovery in Unknown Environments
Development of a Sensor-Based Approach for Local Minima Recovery in Unknown Environments Danial Nakhaeinia 1, Tang Sai Hong 2 and Pierre Payeur 1 1 School of Electrical Engineering and Computer Science,
More informationIMAGE PROCESSING TECHNIQUES FOR CROWD DENSITY ESTIMATION USING A REFERENCE IMAGE
Second Asian Conference on Computer Vision (ACCV9), Singapore, -8 December, Vol. III, pp. 6-1 (invited) IMAGE PROCESSING TECHNIQUES FOR CROWD DENSITY ESTIMATION USING A REFERENCE IMAGE Jia Hong Yin, Sergio
More informationDevelopment of an Intelligent Agent based Manufacturing System
Development of an Intelligent Agent based Manufacturing System Hong-Seok Park 1 and Ngoc-Hien Tran 2 1 School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan 680-749, South Korea 2
More information