34 research outputs found

    A Navigation Framework for Multiple Mobile Robots and its Application at the Expo.02 Exhibition

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    This paper presents a navigation framework which enables multiple mobile robots to attain individual goals, coordinate their actions and work safely and reliably in a highly dynamic environment. We give an overview of the framework architecture, its layering and the subsystems reactive obstacle avoidance, local path planning, global path planning, multi-robot planning and localization. The latter receives particular attention as the localization problem is a key issue for navigation in unmodified and difficult environments. The framework permits a lightweight implementation on a fully autonomous robot. This is the result of a design effort striving for compact representations and computational efficiency. The experimental testbed was the ТRoboticsУ pavilion at the Swiss National Exhibition Expo.02 where ten fully autonomous robots were interacting with more than half a million visitors during a five-month period on 3,316 km

    Robust mobile robot localization based on a security laser: An industry case study

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    This paper aims to address a mobile robot localization system that avoids using a dedicated laser scanner, making it possible to reduce implementation costs and the robot's size. The system has enough precision and robustness to meet the requirements of industrial environments. Design/methodology/approach - Using an algorithm for artificial beacon detection combined with a Kalman Filter and an outlier rejection method, it was possible to enhance the precision and robustness of the overall localization system. Findings - Usually, industrial automatic guide vehicles feature two kinds of lasers: one for navigation placed on top of the robot and another for obstacle detection (security lasers). Recently, security lasers extended their output data with obstacle distance (contours) and reflectivity. These new features made it possible to develop a novel localization system based on a security laser. Research limitations/implications - Once the proposed methodology is completely validated, in the future, a scheme for global localization and failure detection should be addressed. Practical implications - This paper presents a comparison between the presented approach and a commercial localization system for industry. The proposed algorithms were tested in an industrial application under realistic working conditions. Social implications - The presented methodology represents a gain in the effective cost of the mobile robot platform, as it discards the need for a dedicated laser for localization purposes. Originality/value - This paper presents a novel approach that benefits from the presence of a security laser on mobile robots (mandatory sensor when considering industrial applications), using it simultaneously with other sensors, not only to guarantee safety conditions during operation but also to locate the robot in the environment. This paper is also valuable because of the comparison made with a commercialized system, as well as the tests conducted in real industrial environments, which prove that the approach presented is suitable for working under these demanding conditions.Project "TEC4Growth" - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145-FEDER-000020" is fnanced by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).info:eu-repo/semantics/publishedVersio

    Cost-effective robot for steep slope crops monitoring

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    This project aims to develop a low cost, simple and robust robot able to autonomously monitorcrops using simple sensors. It will be required do develop robotic sub-systems and integrate them with pre-selected mechanical components, electrical interfaces and robot systems (localization, navigation and perception) using ROS, for wine making regions and maize fields

    Navigation and Grasping with a Mobile Manipulator: from Simulation to Experimental Results

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    Cobot is the name for collaborative robots. This kind of robot is intended to work in close contact with the human being and to collaborate, by increasing the production rate and by reducing the human onerous tasks, in terms of repetitiveness and precision. At the state of the art, Cobots are often fixed on a support platform, static in their workstation. The aim of this thesis is, hence, to explore, test and validate navigation algorithms for a holonomic mobile robot and in a second moment, to study its behavior with a Cobot mounted on it, in a pick-move-place application. To this purpose, the first part of the thesis addresses the mobile navigation, while the second part the mobile manipulation. Concerning mobile robotics, in the first place, a theoretical background is given and the kinematic model of a holonomic robot is derived. Then, the problem of simultaneous localization and mapping (SLAM) is addressed, i.e. how the robot is able to build a map while localizing itself. Finally, a dedicated chapter will explain the algorithms responsible for exploration and navigation: planners, exploration of frontiers and Monte Carlo localization. Once the necessary theoretical background has been given, these algorithms will be tested both in simulation and in practice on a real robot. In the second part, some theoretical knowledge about manipulators is given and also the kinematic model of the Cobot is derived, together with the algorithm used for a collision free trajectory planning. To conclude, the results of the complete task are shown, first of all in simulation and then on the real robotic system

    Langattomien anturiverkkojen sotilas-, agroteknologia- ja energiatutkimussovelluksia

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    The physical quantities nowadays are widely measured by using electronic sensors. Wireless sensor networks (WSNs) are low-cost, low-power electronic devices capable of collecting data using their onboard sensors. Some wireless sensor nodes are equipped with actuators, providing the possibility to change the state of the physical world. The ability to change the state of a physical system means that WSNs can be used in control and automation applications. This research focuses on appropriate system design for four different wireless measurement and control cases. The first case provides a hardware and software solution for camera integration to a wireless sensor node. The images are captured and processed inside the sensor node using low power computational techniques. In the second application, two different wireless sensor networks function in cooperation to overcome seeding problems in agricultural machinery. The third case focuses on indoor deployment of the wireless sensor nodes into an area of urban crisis, where the nodes supply localization information to friendly assets such as soldiers, firefighters and medical personnel. The last application focuses on a feasibility study for energy harvesting from asphalt surfaces in the form of heat.Fysikaaliset suureet mitataan nykyisin elektronisten anturien avulla. Langattomat anturiverkot ovat kustannustasoltaan edullisia, matalan tehonkulutuksen elektronisia laitteita, jotka kykenevät suorittamaan mittauksia niissä olevilla antureilla. Langattomat anturinoodit voidaan myös liittää toimilaitteisiin, jolloin ne voivat vaikuttaa fyysiseen ympäristöönsä. Koska langattomilla anturi- ja toimilaiteverkoilla voidaan vaikuttaa niiden fysikaalisen ympäristön tilaan, niiden avulla voidaan toteuttaa säätö- ja automaatiosovelluksia. Tässä väitöskirjaty össä suunnitellaan ja toteutetaan neljä erilaista langattomien anturi- ja toimilaiteverkkojen automaatiosovellusta. Ensimmäisenä tapauksena toteutetaan elektroniikka- ja ohjelmistosovellus, jolla integroidaan kamera langattomaan anturinoodiin. Kuvat tallennetaan ja prosessoidaan anturinoodissa vähän energiaa kuluttavia laskentamenetelmiä käyttäen. Toisessa sovelluksessa kahdesta erilaisesta langattomasta anturiverkosta koostuvalla järjestelmällä valvotaan siementen syöttöä kylvökoneessa. Kolmannessa sovelluksessa levitetään kaupunkiympäristössä kriisitilanteessa rakennuksen sisätiloihin langaton anturiverkko. Sen anturinoodit välittävät paikkatietoa rakennuksessa operoiville omille joukoille, jotka voivat tilanteesta riippuen olla esimerkiksi sotilaita, palomiehiä tai lääkintähenkilökuntaa. Neljännessä sovelluksessa toteutetaan langaton anturiverkko, jonka keräämää mittausdataa käytetään arvioitaessa lämpöenergian keräämismahdollisuuksia asfalttipinnoilta.fi=vertaisarvioitu|en=peerReviewed

    Stochastic filtering on mobile devices in complex dynamic environments

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    Gathering information, especially about the immediately surrounding world, is a central aspect of any smart device, whether it is a robot, a partially autonomous vehicle, or a mobile handheld device. The consequential use of electrical sensors always implies the need to filter the imperfect sensor data output in order to gain reliable information. While the challenge of perception and cognition in machines is not a new one, new technology constantly opens up new possibilities and challenges. This is stressed further by the advent of cheap sensor technology and the possibility to use a multitude of small sensors, with the simultaneous constraint of limited resources on mobile, battery-powered computing devices. In this work, stochastic methods are used to filter sensor data, which is gathered by mobile devices, to model the devices' location and eventually also relevant parts of their dynamic environment. This is done with a focus on online algorithms and computation on these mobile devices themselves, which implies limited available processing power and the necessity for computational efficiency. This dissertation's purpose is to impart a better understanding about the conception and design of stochastic filtering solutions, to propose localization algorithms beyond the current state of the art, and to show the use of simultaneous localization and mapping algorithms in the context of cooperatively estimating the surrounding world of a team of robots in a fast changing, dynamic environment. To achieve these goals, the concepts are depicted in multiple application scenarios, design choices and their implications systematically cover all aspects of sensing and estimation, and the proposed systems are evaluated in real-world experiments on humanoid robots and other mobile devices

    Map building, localization and exploration for multi-robot systems

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    The idea of having robots performing the task for which they have been designed completely autonomously and interacting with the environment has been the main objective since the beginning of mobile robotics. In order to achieve such a degree of autonomy, it is indispensable for the robot to have a map of the environment and to know its location in it, in addition to being able to solve other problems such as motion control and path planning towards its goal. During the fulfillment of certain missions without a prior knowledge of its environment, the robot must use the inaccurate information provided by its on-board sensors to build a map at the same time it is located in it, arising the problem of Simultaneous Localization and Mapping (SLAM) extensively studied in mobile robotics. In recent years, there has been a growing interest in the use of robot teams due to their multiple benefits with respect to single-robot systems such as higher robustness, accuracy, efficiency and the possibility to cooperate to perform a task or to cover larger environments in less time. Robot formations also belongs to this field of cooperative robots, where they have to maintain a predefined structure while navigating in the environment. Despite their advantages, the complexity of autonomous multi-robot systems increases with the number of robots as a consequence of the larger amount of information available that must be handled, stored and transmitted through the communications network. Therefore, the development of these systems presents new difficulties when solving the aforementioned problems which, instead of being addressed individually for each robot, must be solved cooperatively to efficiently exploit all the information collected by the team. The design of algorithms in this multi-robot context should be directed to obtain greater scalability and performance to allow their online execution. This thesis is developed in the field of multi-robot systems and proposes solutions to the navigation, localization, mapping and path planning processes which form an autonomous system. The first part of contributions presented in this thesis is developed in the context of robot formations, which require greater team cooperation and synchronization, although they can be extended to systems without this navigation constraint. We propose localization, map refinement and exploration techniques under the assumption that the formation is provided with a map of the environment, possibly partial and inaccurate, wherein it has to carry out its commanded mission. In a second part, we propose a multi-robot SLAM approach without any assumption about the prior knowledge of a map nor the relationships between robots in which we make use of state of the art methodologies to efficiently manage the resources available in the system. The performance and efficiency of the proposed robot formation and multi-robot SLAM systems have been demonstrated through their implementation and testing both in simulations and with real robots
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