Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots

This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.This work has been partially funded by FEDER-CICYT projects with references DPI2011-28507-C02-01 and DPI2010-20814-C02-02, financed by Ministerio de Ciencia e Innovacion (Spain). Also, the financial support from the University of Costa Rica is greatly appreciated.Marín, L.; Vallés Miquel, M.; Soriano Vigueras, Á.; Valera Fernández, Á.; Albertos Pérez, P. (2013). Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots. 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Low cost two dimension navigation using an augmented Kalman filter/Fast Orthogonal Search module for the integration of reduced inertial sensor system and Global Positioning System. Transportation Research Part C: Emerging Technologies, 19(6), 1111-1132. doi:10.1016/j.trc.2011.01.001Kotecha, J. H., & Djuric, P. M. (2003). Gaussian particle filtering. IEEE Transactions on Signal Processing, 51(10), 2592-2601. doi:10.1109/tsp.2003.816758Seyboth, G. S., Dimarogonas, D. V., & Johansson, K. H. (2013). Event-based broadcasting for multi-agent average consensus. Automatica, 49(1), 245-252. doi:10.1016/j.automatica.2012.08.042Guinaldo, M., Fábregas, E., Farias, G., Dormido-Canto, S., Chaos, D., Sánchez, J., & Dormido, S. (2013). A Mobile Robots Experimental Environment with Event-Based Wireless Communication. Sensors, 13(7), 9396-9413. doi:10.3390/s130709396Meng, X., & Chen, T. (2013). Event based agreement protocols for multi-agent networks. Automatica, 49(7), 2125-2132. doi:10.1016/j.automatica.2013.03.002Campion, G., Bastin, G., & Dandrea-Novel, B. (1996). Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. IEEE Transactions on Robotics and Automation, 12(1), 47-62. doi:10.1109/70.481750Ward, C. C., & Iagnemma, K. (2008). A Dynamic-Model-Based Wheel Slip Detector for Mobile Robots on Outdoor Terrain. IEEE Transactions on Robotics, 24(4), 821-831. doi:10.1109/tro.2008.924945Zohar, I., Ailon, A., & Rabinovici, R. (2011). Mobile robot characterized by dynamic and kinematic equations and actuator dynamics: Trajectory tracking and related application. Robotics and Autonomous Systems, 59(6), 343-353. doi:10.1016/j.robot.2010.12.001De La Cruz, C., & Carelli, R. (2008). Dynamic model based formation control and obstacle avoidance of multi-robot systems. Robotica, 26(3), 345-356. doi:10.1017/s0263574707004092Attia, H. A. (2005). 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Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments

Distributed sensor architecture for intelligent control that supports quality of control and quality of service

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.The study described in this paper is a part of the coordinated project COBAMI: Mission-based Hierarchical Control. Education and Science Department Spanish Government. CICYT: MICINN: DPI2011-28507-C02-01/02 and project "Real time distributed control systems" of the Support Program for Research and Development 2012 UPV (PAID-06-12).Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE.; Simarro Fernández, R.; Benet Gilabert, G. (2015). Distributed sensor architecture for intelligent control that supports quality of control and quality of service. Sensors. 15(3):4700-4733. https://doi.org/10.3390/s150304700S4700473315

Sensors and Technologies in Spain: State-of-the-Art

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Study on the development of an autonomous mobile robot

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de ComputadoresThis dissertation addresses the subject of Autonomous Mobile Robotics (AMR). It is aimed to evaluate the problems associated with the orientation of the independent vehicles and their technical solutions. There are numerous topics related to the AMR subject. Due to the vast number of topics important for the development of an AMR, it was necessary to dedicate different degrees of attention to each of the topics. The sensors applied in this research were several, e.g. Ultrasonic Sensor, Inertial Sensor, etc. All of them have been studied within the same environment. Employing the information provided by the sensors, a map is constructed, and based on this map a trajectory is planned. The Robot moves, considering the planned trajectory, commanded by a controller based on Linear Quadratic Regulator (LQR) and a specially made model of the robot, through a Kalman Filter (KF). Some of the researched topics were implemented in a real robot in an unstructured environment, collecting measurement data. A final conclusion is indicating the future direction of development

Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots

This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments