998 resultados para Natural Landmarks


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This paper describes the current state of RatSLAM, a Simultaneous Localisation and Mapping (SLAM) system based on models of the rodent hippocampus. RatSLAM uses a competitive attractor network to fuse visual and odometry information. Energy packets in the network represent pose hypotheses, which are updated by odometry and can be enhanced or inhibited by visual input. This paper shows the effectiveness of the system in real robot tests in unmodified indoor environments using a learning vision system. Results are shown for two test environments; a large corridor loop and the complete floor of an office building.

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A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system

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SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

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Mode of access: Internet.

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Mode of access: Internet.

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Prepared under contract 14-10-9-990-186, Article II as revised 5 April 1970 with the U.S. Dept. of the Interior, National park Service.

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SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

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SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

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This paper presents a novel coarse-to-fine global localization approach inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by scale-invariant transformation feature descriptors are used as natural landmarks. They are indexed into two databases: a location vector space model (LVSM) and a location database. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the LVSM is fast, but not accurate enough, whereas localization from the location database using a voting algorithm is relatively slow, but more accurate. The integration of coarse and fine stages makes fast and reliable localization possible. If necessary, the localization result can be verified by epipolar geometry between the representative view in the database and the view to be localized. In addition, the localization system recovers the position of the camera by essential matrix decomposition. The localization system has been tested in indoor and outdoor environments. The results show that our approach is efficient and reliable. © 2006 IEEE.

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In this paper, we propose a vision based mobile robot localization strategy. Local scale-invariant features are used as natural landmarks in unstructured and unmodified environment. The local characteristics of the features we use prove to be robust to occlusion and outliers. In addition, the invariance of the features to viewpoint change makes them suitable landmarks for mobile robot localization. Scale-invariant features detected in the first exploration are indexed into a location database. Indexing and voting allow efficient recognition of global localization. The localization result is verified by epipolar geometry between the representative view in database and the view to be localized, thus the probability of false localization will be decreased. The localization system can recover the pose of the camera mounted on the robot by essential matrix decomposition. Then the position of the robot can be computed easily. Both calibrated and un-calibrated cases are discussed and relative position estimation based on calibrated camera turns out to be the better choice. Experimental results show that our approach is effective and reliable in the case of illumination changes, similarity transformations and extraneous features. © 2004 IEEE.

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Several methods of mobile robot navigation request the mensuration of robot position and orientation in its workspace. In the wheeled mobile robot case, techniques based on odometry allow to determine the robot localization by the integration of incremental displacements of its wheels. However, this technique is subject to errors that accumulate with the distance traveled by the robot, making unfeasible its exclusive use. Other methods are based on the detection of natural or artificial landmarks present in the environment and whose location is known. This technique doesnt generate cumulative errors, but it can request a larger processing time than the methods based on odometry. Thus, many methods make use of both techniques, in such a way that the odometry errors are periodically corrected through mensurations obtained from landmarks. Accordding to this approach, this work proposes a hybrid localization system for wheeled mobile robots in indoor environments based on odometry and natural landmarks. The landmarks are straight lines de.ned by the junctions in environments floor, forming a bi-dimensional grid. The landmark detection from digital images is perfomed through the Hough transform. Heuristics are associated with that transform to allow its application in real time. To reduce the search time of landmarks, we propose to map odometry errors in an area of the captured image that possesses high probability of containing the sought mark

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BACKGROUND: In this paper we present a landmark-based augmented reality (AR) endoscope system for endoscopic paranasal and transnasal surgeries along with fast and automatic calibration and registration procedures for the endoscope. METHODS: Preoperatively the surgeon selects natural landmarks or can define new landmarks in CT volume. These landmarks are overlaid, after proper registration of preoperative CT to the patient, on the endoscopic video stream. The specified name of the landmark, along with selected colour and its distance from the endoscope tip, is also augmented. The endoscope optics are calibrated and registered by fast and automatic methods. Accuracy of the system is evaluated in a metallic grid and cadaver set-up. RESULTS: Root mean square (RMS) error of the system is 0.8 mm in a controlled laboratory set-up (metallic grid) and was 2.25 mm during cadaver studies. CONCLUSIONS: A novel landmark-based AR endoscope system is implemented and its accuracy is evaluated. Augmented landmarks will help the surgeon to orientate and navigate the surgical field. Studies prove the capability of the system for the proposed application. Further clinical studies are planned in near future.

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In this study, we investigated the role of routes and information attainment for the queenless ant species Dinoponera quadriceps foraging efficiency. Two queenless ant colonies were observed in an area of Atlantic secondary Forest at the FLONA-ICMBio of Nisia Floresta, in the state of Rio Grande do Norte, northeastern Brazil, at least once a week. In the first stage of the study, we observed the workers, from leaving until returning to the colony. In the second stage, we introduced a acrylic plate (100 x 30 x 0,8 cm) on a selected entrance of the nest early in the morning before the ants left the nest. All behavioral recordings were done through focal time and all occurence samplings. The recording windows were of 15 minutes with 1 minute interval, and 5 minute intervals between each observation window. Foraging was the main activity when the workers were outside the nest. There was a positive correlation between time outside the nest and distance travelled by the ants. These variables influenced the proportion of resource that was taken to the nest, that is, the bigger its proportion, the longer the time outside and distance travelled during the search. That proportion also influenced the time the worker remained in the nest before a new trip, the bigger the proportion of the item, the shorter was the time in the nest. During all the study, workers showed fidelity to the route and to the sectors in the home range, even when the screen was in the ant´s way, once they deviated and kept the route. The features of foraging concerning time, distance, route and flexibility to go astray by the workers indicate that decisions are made by each individual and are optimal in terms of a cost-benefit relation. The strategy chosen by queenless ants fits the central place foraging and marginal value theorem theories and demonstrate its flexibility to new informations. This indicates that the workers can learn new environmental landmarks to guide their routes