1,721,141 research outputs found
Deep introspective SLAM: deep reinforcement learning based approach to avoid tracking failure in visual SLAM
No full textReliable and consistent tracking is essential to realize the dream of power-on-and-go autonomy in mobile robots. Our investigation with state-of-the-art visual navigation and mapping tools (e.g. ORB-SLAM) reveals that these tools suffer from frequent and unexpected tracking failures, especially when tested in the wild. This hinders the ability of robots to reach a goal position less than 10 meters away, without tracking failure, thereby limiting the prospects of real autonomy. We present an introspection-based approach (Introspective-SLAM) that enables SLAM to evaluate safety of navigation steps with respect to tracking failure, before the steps are actually taken. Navigation steps that appear unsafe are thereby avoided, and an alternative path to the goal is planned. We propose a novel deep reinforcement learning (DQN) based network to evaluate safety of future navigation steps using a single image only. Surprisingly, training of our DQN completes in a short amount of time (< 60 h). Even then, this network outperforms several handcrafted and Q-learning based pipelines to achieve state-of-the-art performance. Interestingly, training the DQN in realistic simulators (MINOS), consisting of reconstructed interiors, shows good generalization across real world indoor-outdoor settings. Finally, extensive testing of visual SLAM, equipped with our DQN, shows that tracking failures occur frequently and are a major hindrance in reaching the goal. Currently, there is no standard benchmark to evaluate active visual SLAM approaches. We have released a benchmark of 50 episodes with this work. We hope these findings/benchmark will encourage progress for power-on-and-go visual SLAM without any manual supervision.
EVALUATION OF CT SCANNING EFFICACY AND FAST SCANNING EFFICACY IN BLUNT ABDOMEN TRAUMA PATIENTS
No full text*Jannat Anjum, Muhammad Bilal and Bushra Gul
Sensor Data Fusion Using Unscented Kalman Filter for VOR-Based Vision Tracking System for Mobile Robots
Full text linkThis paper presents sensor data fusion using Unscented Kalman Filter (UKF) to implement high performance vestibulo-ocular reflex (VOR) based vision tracking system for mobile robots. Information from various sensors is required to be integrated using an efficient sensor fusion algorithm to achieve a continuous and robust vision tracking system. We use data from low cost accelerometer, gyroscope, and encoders to calculate robot motion information. The Unscented Kalman Filter is used as an efficient sensor fusion algorithm. The UKF is an advanced filtering technique which outperforms widely used Extended Kalman Filter (EKF) in many applications. The system is able to compensate for the slip errors by switching between two different UKF models built for slip and no-slip cases. Since the accelerometer error accumulates with time because of the double integration, the system uses accelerometer data only for the slip case UKF model. Using sensor fusion by UKF, the position and orientation of the robot is estimated and is used to rotate the camera mounted on top of the robot towards a fixed target. This concept is derived from the vestibule-ocular reflex (VOR) of the human eye. The experimental results show that the system is able to track the fixed target in various robot motion scenarios including the scenario when an intentional slip is generated during robot navigation
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Using time proportionate intensity images with non-linear classifiers for hand gesture recognition
No full textGestures are spatiotemporal signals that contain valuable information. Humans can understand gestures with ease, but for computers or robots it is a challenging task involving thousands of computations per video frame. Current state of the art gesture recognition systems treat gestures as Markov Chains. Then the task of gesture recognition is to match the incoming video sequence to these Markov Chains. Each Markov State is modeled with spatial features such as hand location and temporal features like the motion vectors. The main problem with this approach is the high order of computational complexity. In this paper we propose a novel gesture recognition technique based on projecting the temporal axis information onto the spatial plane. Then this spatial intensity image is fed to a machine learning classifier (SVM in our case) for recognition. We show that the proposed algorithm achieves an accuracy that is comparable to the current state of the art approaches, but with a (much) reduced computational burde
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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