897 resultados para Concurrent localization and mapping


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In this paper we discuss how a network of sensors and robots can cooperate to solve important robotics problems such as localization and navigation. We use a robot to localize sensor nodes, and we then use these localized nodes to navigate robots and humans through the sensorized space. We explore these novel ideas with results from two large-scale sensor network and robot experiments involving 50 motes, two types of flying robot: an autonomous helicopter and a large indoor cable array robot, and a human-network interface. We present the distributed algorithms for localization, geographic routing, path definition and incremental navigation. We also describe how a human can be guided using a simple hand-held device that interfaces to this same environmental infrastructure.

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We consider multi-robot systems that include sensor nodes and aerial or ground robots networked together. We describe two cooperative algorithms that allow robots and sensors to enhance each other's performance. In the first algorithm, an aerial robot assists the localization of the sensors. In the second algorithm, a localized sensor network controls the navigation of an aerial robot. We present physical experiments with an flying robot and a large Mica Mote sensor network.

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Maps are used to represent three-dimensional space and are integral to a range of everyday experiences. They are increasingly used in mathematics, being prominent both in school curricula and as a form of assessing students understanding of mathematics ideas. In order to successfully interpret maps, students need to be able to understand that maps: represent space, have their own perspective and scale, and their own set of symbols and texts. Despite the fact that maps have an increased prevalence in society and school, there is evidence to suggest that students have difficulty interpreting maps. This study investigated 43 primary-aged students’ (aged 9-12 years) verbal and gestural behaviours as they engaged with and solved map tasks. Within a multiliteracies framework that focuses on spatial, visual, linguistic, and gestural elements, the study investigated how students interpret map tasks. Specifically, the study sought to understand students’ skills and approaches used to solving map tasks and the gestural behaviours they utilised as they engaged with map tasks. The investigation was undertaken using the Knowledge Discovery in Data (KDD) design. The design of this study capitalised on existing research data to carry out a more detailed analysis of students’ interpretation of map tasks. Video data from an existing data set was reorganised according to two distinct episodes—Task Solution and Task Explanation—and analysed within the multiliteracies framework. Content Analysis was used with these data and through anticipatory data reduction techniques, patterns of behaviour were identified in relation to each specific map task by looking at task solution, task correctness and gesture use. The findings of this study revealed that students had a relatively sound understanding of general mapping knowledge such as identifying landmarks, using keys, compass points and coordinates. However, their understanding of mathematical concepts pertinent to map tasks including location, direction, and movement were less developed. Successful students were able to interpret the map tasks and apply relevant mathematical understanding to navigate the spatial demands of the map tasks while the unsuccessful students were only able to interpret and understand basic map conventions. In terms of their gesture use, the more difficult the task, the more likely students were to exhibit gestural behaviours to solve the task. The most common form of gestural behaviour was deictic, that is a pointing gesture. Deictic gestures not only aided the students capacity to explain how they solved the map tasks but they were also a tool which assisted them to navigate and monitor their spatial movements when solving the tasks. There were a number of implications for theory, learning and teaching, and test and curriculum design arising from the study. From a theoretical perspective, the findings of the study suggest that gesturing is an important element of multimodal engagement in mapping tasks. In terms of teaching and learning, implications include the need for students to utilise gesturing techniques when first faced with new or novel map tasks. As students become more proficient in solving such tasks, they should be encouraged to move beyond a reliance on such gesture use in order to progress to more sophisticated understandings of map tasks. Additionally, teachers need to provide students with opportunities to interpret and attend to multiple modes of information when interpreting map tasks.

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The indecision surrounding the definition of Technology extends to the classroom as not knowing what a subject “is” affects how it is taught. Similarly, its relative newness – and consequent lack of habitus in school settings - means that it is still struggling to find its own place in the curriculum as well as resolve its relationship with more established subject domains, particularly Science and Mathematics. The guidance from syllabus documents points to open-ended student-directed projects where extant studies indicate a more common experience of teacher –directed activities and an emphasis on product over process. There are issues too for researchers in documenting classroom observations and in analysing teacher practice in new learning environments. This paper presents a framework for defining and mapping classroom practice and for attempting to describe the social practice in the Technology classroom. The framework is a bricolage which draws on contemporary research. More formally, the development of the framework is consonant with the aim of design-based research to develop a flexible, adaptive and generalisable theory to better understanding a teaching domain where promise is not seen to match current reality. The framework may also inform emergent approaches to STEM (Science, Technology, Education and Mathematics) in education.

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This paper addresses the challenge of developing robots that map and navigate autonomously in real world, dynamic environments throughout the robot’s entire lifetime – the problem of lifelong navigation. Static mapping algorithms can produce highly accurate maps, but have found few applications in real environments that are in constant flux. Environments change in many ways: both rapidly and gradually, transiently and permanently, geometrically and in appearance. This paper demonstrates a biologically inspired navigation algorithm, RatSLAM, that uses principles found in rodent neural circuits. The algorithm is demonstrated in an office delivery challenge where the robot was required to perform mock deliveries to goal locations in two different buildings. The robot successfully completed 1177 out of 1178 navigation trials over 37 hours of around the clock operation spread over 11 days.

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In this paper an existing method for indoor Simultaneous Localisation and Mapping (SLAM) is extended to operate in large outdoor environments using an omnidirectional camera as its principal external sensor. The method, RatSLAM, is based upon computational models of the area in the rat brain that maintains the rodent’s idea of its position in the world. The system uses the visual appearance of different locations to build hybrid spatial-topological maps of places it has experienced that facilitate relocalisation and path planning. A large dataset was acquired from a dynamic campus environment and used to verify the system’s ability to construct representations of the world and simultaneously use these representations to maintain localisation.

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One of the major challenges in achieving long term robot autonomy is the need for a SLAM algorithm that can perform SLAM over the operational lifetime of the robot, preferably without human intervention or supervision. In this paper we present insights gained from a two week long persistent SLAM experiment, in which a Pioneer robot performed mock deliveries in a busy office environment. We used the biologically inspired visual SLAM system, RatSLAM, combined with a hybrid control architecture that selected between exploring the environment, performing deliveries, and recharging. The robot performed more than a thousand successful deliveries with only one failure (from which it recovered), travelled more than 40 km over 37 hours of active operation, and recharged autonomously 23 times. We discuss several issues arising from the success (and limitations) of this experiment and two subsequent avenues of work.

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This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

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A strongly progressive surveying and mapping industry depends on a shared understanding of the industry as it exists, some shared vision or imagination of what the industry might become, and some shared action plan capable of bringing about a realisation of that vision. The emphasis on sharing implies a need for consensus reached through widespread discussion and mutual understanding. Unless this occurs, concerted action is unlikely. A more likely outcome is that industry representatives will negate each other's efforts in their separate bids for progress. The process of bringing about consensual viewpoints is essentially one of establishing an industry identity. Establishing the industry's identity and purpose is a prerequisite for rational development of the industry's education and training, its promotion and marketing, and operational research that can deal .with industry potential and efficiency. This paper interprets evolutionary developments occurring within Queensland's surveying and mapping industry within a framework that sets out logical requirements for a viable industry.

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Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.

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Democratic governments raise taxes and charges and spend revenue on delivering peace, order and good government. The delivery process begins with a legislature as that can provide a framework of legally enforceable rules enacted according to the government’s constitution. These rules confer rights and obligations that allow particular people to carry on particular functions at particular places and times. Metadata standards as applied to public records contain information about the functioning of government as distinct from the non-government sector of society. Metadata standards apply to database construction. Data entry, storage, maintenance, interrogation and retrieval depend on a controlled vocabulary needed to enable accurate retrieval of suitably catalogued records in a global information environment. Queensland’s socioeconomic progress now depends in part on technical efficiency in database construction to address queries about who does what, where and when; under what legally enforceable authority; and how the evidence of those facts is recorded. The Survey and Mapping Infrastructure Act 2003 (Qld) addresses technical aspects of where questions – typically the officially recognised name of a place and a description of its boundaries. The current 10-year review of the Survey and Mapping Regulation 2004 provides a valuable opportunity to consider whether the Regulation makes sense in the context of a number of later laws concerned with management of Public Sector Information (PSI) as well as policies for ICT hardware and software procurement. Removing ambiguities about how official place names are to be regarded on a whole-of-government basis can achieve some short term goals. Longer-term goals depend on a more holistic approach to information management – and current aspirations for more open government and community engagement are unlikely to occur without such a longer-term vision.

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This thesis presents a novel approach to mobile robot navigation using visual information towards the goal of long-term autonomy. A novel concept of a continuous appearance-based trajectory is proposed in order to solve the limitations of previous robot navigation systems, and two new algorithms for mobile robots, CAT-SLAM and CAT-Graph, are presented and evaluated. These algorithms yield performance exceeding state-of-the-art methods on public benchmark datasets and large-scale real-world environments, and will help enable widespread use of mobile robots in everyday applications.

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This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

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We identified, mapped, and characterized a widespread area (gt;1,020 km2) of patterned ground in the Saginaw Lowlands of Michigan, a wet, flat plain composed of waterlain tills, lacustrine deposits, or both. The polygonal patterned ground is interpreted as a possible relict permafrost feature, formed in the Late Wisconsin when this area was proximal to the Laurentide ice sheet. Cold-air drainage off the ice sheet might have pooled in the Saginaw Lowlands, which sloped toward the ice margin, possibly creating widespread but short-lived permafrost on this glacial lake plain. The majority of the polygons occur between the Glacial Lake Warren strandline (~14.8 cal. ka) and the shoreline of Glacial Lake Elkton (~14.3 cal. ka), providing a relative age bracket for the patterned ground. Most of the polygons formed in dense, wet, silt loam soils on flat-lying sites and take the form of reticulate nets with polygon long axes of 150 to 160 m and short axes of 60 to 90 m. Interpolygon swales, often shown as dark curvilinears on aerial photographs, are typically slightly lower than are the polygon centers they bound. Some portions of these interpolygon swales are infilled with gravel-free, sandy loam sediments. The subtle morphology and sedimentological characteristics of the patterned ground in the Saginaw Lowlands suggest that thermokarst erosion, rather than ice-wedge replacement, was the dominant geomorphic process associated with the degradation of the Late-Wisconsin permafrost in the study area and, therefore, was primarily responsible for the soil patterns seen there today.