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Analysis of a sensor fusion hybrid solution for indoor/outdoor robot navigation

  • Martí, Enrique David
  • García, Jesús
  • Molina, José M.
Proceedings of: 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC 2010). Noordwij, Netherlands, 8-10 December 2010, Autonomous mobile robots need robust, flexible and accurate navigation algorithms. One approach consists in fusing as many information sources as possible, integrating measures from internal sensors with data obtained from external sensing entities. This work presents a solution for combined indoor/outdoor robot navigation, and analyzes some preliminary results in an outdoor environment using a Particle Filter for GPS/INS sensor fusion. Experiments are based in predesigned trajectories which have been simulated in first place and then reproduced using a robotic platform. As a concluding remark, some considerations about the use of Particle Filters and the differences between simulated and real data are presented, This work was supported in part by Projects ATLANTIDA, CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008- 06732-C02-02/TEC, SINPROB, CAM MADRINET S- 0505/TIC/0255 DPS2008-07029-C02-02., Publicado
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MB-GNG: Addressing drawbacks in multi-objective optimization estimation of distribution algorithms

  • Martí, Luis
  • García, Jesús
  • Berlanga de Jesús, Antonio
  • Coello Coello, Carlos A.
  • Molina López, José Manuel
We examine the model-building issue related to multi-objective estimation of distribution algorithms (MOEDAs) and show that some of their, as yet overlooked, characteristics render most current MOEDAs unviable when addressing optimization problems with many objectives. We propose a novel model-building growing neural gas (MB-GNG) network that is specially devised for properly dealing with that issue and therefore yields a better performance. Experiments are conducted in order to show from an empirical point of view the advantages of the new algorithm., assigned to this paper for their comments and suggestions. They helped to substantially improve the paper. They also wish to thank Prof. Elisenda Molina for her assistance in the preparation of the manuscript. LM, JG, AB and JMM were supported by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM CONTEXTS S2009/TIC-1485 and DPS2008-07029- C02-02. CACC was supported by CONACyT project 103570., Publicado
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Neighborhood-based Regularization of Proposal Distribution for Improving Resampling Quality in Particle Filters

  • Martí, Enrique David
  • García, Jesús
  • Molina, José M.
Proceedings of: 14th International Conference on Information Fusion (FUSION 2011). Chicago, Illinois, USA 5-8 July 2011, Particle Filter is a sequential Montecarlo algorithm extensively used for solving estimation problems with non-linear and non-Gaussian features. In spite of its relative simplicity, it is known to suffer some undesired effects that can spoil its performance. Among these problems we can account the one known as sample depletion. This paper reviews the different causes of sample depletion and the many solutions proposed in the existing literature. It also introduces a new strategy for particle resampling which relies in a local linearization of the proposal distribution. The particles drawn using the proposed method are not affected by sample impoverishment and can indirectly lead to better results thanks to a reduction in the plant noise employed, as well to increased performance because of requiring a lower number of particles to achieve same results., Publicado
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Improving Multiple-Model Context-Aided Tracking through an Autocorrelation Approach

  • Martí, Enrique David
  • García, Jesús
  • Crassidis, John
Proceedings of: 15th International Conference on Information Fusion (FUSION), Singapore, 9-12 July 2012, This paper continues a previous work, where the context-aided tracker "ConTracker" was used to detect suspicious behaviors in maritime vehicle trajectories. ConTracker takes into account map-based contextual information - which includes water depth, shipping channels and areas/buildings with a high strategy value - to determine anomalies in ship trajectories. The different areas act as repellers or attractors that modify the expected trajectory of the tracked vessel. In the original scheme, a multiple-model adaptive estimator (MMAE) is used to estimate the noise parameters of the tracking system: sudden increases on the output reflect unexpected maneuvers - such as entering a forbidden area - that are translated as alarms. The work presented here shows the results obtained by implementing a generalized version of the multiple-model adaptive estimator (GMMAE). While the former approach uses information of the last cycle to update the weight/importance of each model, our proposal calculates a likelihood value based on the time-domain autocorrelation function of the last few indicators. GMMAE provides a much faster response, which ultimately leads to a general performance boost: alarms are faster and clearer. Compared with previous works, GMMAE is particularly effective returning back to normal state after an alarm has been raised: this results in alarms with a better defined duration. Results are presented over several simulated trajectories, featuring a variety of realistic anomalies which are correctly identified. They include direct comparison with the previous approach, for an objective demonstration of the achieved improvement., This work was supported in part by Projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02- 02, CAM CONTEXTS (S2009/TIC-1485) and DPS2008- 07029-C02-02., Publicado
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Personalized Alert Notifications and Evacuation Routes in Indoor Environments

  • Aedo Cuevas, Ignacio
  • Shuxin, Yu
  • Díaz, Paloma
  • Acuña, Pablo
  • Onorati, Teresa
The preparedness phase is crucial in the emergency management process for reaching an adequate level of readiness to react to potential threats and hazards. During this phase, emergency plans are developed to establish, among other procedures, evacuation and emergency escape routes. Information and Communication Technologies (ICT) can support and improve these procedures providing appropriate, updated and accessible information to all people in the affected zone. Current emergency management and evacuation systems do not adapt information to the context and the profile of each person, so messages received in the emergency might be useless. In this paper, we propose a set of criteria that ICT-based systems could achieve in order to avoid this problem adapting emergency alerts and evacuation routes to different situations and people. Moreover, in order to prove the applicability of such criteria, we define a mechanism that can be used as a complement of traditional evacuation systems to provide personalized alerts and evacuation routes to all kinds of people during emergency situations in working places. This mechanism is composed by three main components: CAP-ONES for notifying emergency alerts, NERES for defining emergency plans and generating personalized evacuation routes, and iNeres as the interface to receive and visualize these routes on smartphones. The usability and understandability of proposed interface has been assessed through a user study performed in a fire simulation in an indoor environment. This evaluation demonstrated that users considered iNeres easy to understand, to learn and to use, and they also found very innovative the idea to use smartphones as a support for escaping instead of static signals on walls and doors.
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Distributed Active-Camera Control Architecture Based on Multi-Agent Systems

  • Luis Bustamante, Álvaro
  • Molina, José M.
  • Patricio Guisado, Miguel Ángel
Proceedings of: 10th Conference on Practical Applications of Agents and Multi-Agent Systems, Salamanca (Spain), 28-30 March 2012 (PAAMS`12), In this contribution a Multi-Agent System architecture is proposed to deal with the management of spatially distributed heterogeneous nets of sensors, specially is described the problem of Pan-Tilt-Zoom or active cameras. The design of surveillance multi-sensor systems implies undertaking to solve two related problems: data fusion and coordinated sensor-task management. Generally, proposed architectures for the coordinated operation of multiple sensors are based on centralization of management decisions at the fusion center. However, the existence of intelligent sensors capable of taking decisions brings the possibility of conceiving alternative decentralized architectures. This problem could be approached by means of a Multi-Agent System (MAS). In specific, this paper proposes a MAS architecture for automatically control sensors in video surveillance environments., This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/ TIC-1485) and DPS2008- 07029-C02-02., Publicado
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The DI@L-log System: Integration of Speech Technologies in Healthcare Applications

  • Griol, David
  • Molina, José M.
Proceedings of: XIV Conferencia de la Asociación Española para la Inteligencia Artificial CAEPIA'11. AIHealth. I Workshop on Artificial Intelligence in Healthcare and Biomedical Applications. San Cristobal de la Laguna, Tenerife. 07-10 noviembre 2011, In this paper, we describe a spoken dialog system developed to collect monitored data from patients su ering from diabetes. The dialog model of this system has been developed by means of a statistical methodology for automatically exploring the dialog space and learning new enhanced dialog strategies from a dialog corpus. A dialog simulation technique has been applied to acquire data required to train the dialog model and then explore the new dialog strategies. A set of measures has also been defined to evaluate the dialog strategy. The results of the evaluation show how the dialog manager deviates from the initially predefined strategy, allowing the dialog manager to tackle new situations and generate new coherent answers for the situations already present in the initial corpus. The proposed technique can be used not only to develop new dialog managers but also to explore new enhanced strategies., Research funded by projects CICYT TIN 2008-06742-C02-02/TSI, CICYT TEC 2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS 2008-07029- C02-02., Publicado
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Ontology-based context representation and reasoning for object tracking and scene interpretation in video

  • Gómez Romero, Juan
  • Patricio Guisado, Miguel Ángel
  • García, Jesús
  • Molina, José M.
Computer vision research has been traditionally focused on the development of quantitative techniques to calculate the properties and relations of the entities appearing in a video sequence. Most object tracking methods are based on statistical methods, which often result inadequate to process complex scenarios. Recently, new techniques based on the exploitation of contextual information have been proposed to overcome the problems that these classical approaches do not solve. The present paper is a contribution in this direction: we propose a Computer Vision framework aimed at the construction of a symbolic model of the scene by integrating tracking data and contextual information. The scene model, represented with formal ontologies, supports the execution of reasoning procedures in order to: (i) obtain a high-level interpretation of the scenario; (ii) provide feedback to the low-level tracking procedure to improve its accuracy and performance. The paper describes the layered architecture of the framework and the structure of the knowledge model, which have been designed in compliance with the JDL model for Information Fusion. We also explain how deductive and abductive reasoning is performed within the model to accomplish scene interpretation and tracking improvement. To show the advantages of our approach, we develop an example of the use of the framework in a video-surveillance application., This work was supported in part by Projects CICYT TIN2008- 06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008–07029-C02–02., Publicado
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