1,721,019 research outputs found
MPC trajectory planner for autonomous driving solved by genetic algorithm technique
No full textFocusing on autonomous driving algorithm development, this paper proposes a novel real-time trajectory planner formulated as a Nonlinear Model Predictive Control (NMPC) algorithm. The mathematical formulation of the problem is deeply reported and discussed. The numerical solution of the NMPC problem is the result of a novel genetic algorithm strategy that represents the innovative aspect of the work proposed. The aim of this paper is also to show how genetic algorithm can be a valid approach for motion planning strategies. Numerical results are discussed through simulations that show a reasonable behaviour of the proposed strategy in the presence of moving obstacles as well as in a wide range of road friction conditions. Moreover, a real-time implementation for research purposes is assumed as possible by considering computational time analysis reported
Autonomous vehicle driving via deep deterministic policy gradient
No full textAutonomous driving has became one of the most hot trends in artificial intelligence area in recent years thanks to the machine learning algorithms. However, most of the autonomous driving studies are still limited to discrete action space. In this study, we propose to implement Deep Deterministic Policy Gradient algorithm for learning driving behavior over the continuous actions. For this purpose, a driving simulator is employed which interfaces with IPG CarMker software where the virtual environment and dynamical vehicle model can be built.”Human-in-the-loop” is performed in order to gather the data and a neural network which is implemented in Behavior Layer is trained to recognize two different scenarios-forward driving and stop. Based on the scenario the agent is dealing with, the actions are learnt and suggested from the DDPG algorithm. The experimental results show that DDPG algorithm is able to learn the optimal policy with continuous actions reliably for both scenarios
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
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
An interactive human-machine control interface for an autonomous shuttle
No full textAutonomous Shuttles are touted to be the first widespread implementation of autonomous vehicles for the first and last-mile applications in urban mobility. Extensive research in the field of autonomous mobility is being carried out in various aspects which include sensor data fusion, planning, perception, localization, mapping, and control algorithms. These algorithms need real-world data for testing, development, and validation. This paper proposes a modular architecture for easy integration of diverse autonomous driving logics in an autonomous driving system. Further, the proposed architecture is applied on an autonomous shuttle to develop a human-machine interface for facilitating the research in Politecnico di Milano
Control of a Hexapod Robot Considering Terrain Interaction
Full text linkBioinspired walking hexapod robots are a relatively young branch of robotics. Despite the high degree of flexibility and adaptability derived from their redundant design, open-source implementations do not fully utilize this potential. This paper proposes an exhaustive description of a hexapod robot-specific control architecture based on open-source code that allows for complete control over a robot's speed, body orientation, and walk gait type. Furthermore, terrain interaction is deeply investigated, leading to the development of a terrain-adapting control algorithm that allows the robot to react swiftly to the terrain shape and asperities, such as non-linearities and non-continuity within the workspace. For this purpose, a dynamic model derived from interpreting the hexapod movement is presented and validated through a Matlab SimMechanicsTM simulation. Furthermore, a feedback control system is developed, which is able to recognize leg-terrain touch and react accordingly to ensure movement stability. Finally, the results from an experimental campaign based on the PhantomX AX Metal Hexapod Mark II robotic platform by Trossen RoboticsTM are reported
Fault Resistant Odometry Estimation using Message Passing Neural Network
No full textMulti-modal sensor fusion constitutes an essential ingredient for safe autonomous navigation. In the last years, many works have improved the accuracy of Deep-Learning-based odometry estimators. However, the robustness of these algorithms to sensor failure or measurement degradation, which are very likely to happen during navigation, has been studied less extensively. Furthermore, works studying the robustness of the fusion modules are developed without modeling the correlation between sensor features, which is crucial to filter out features derived from noisy measurements and in sensor faults scenarios. To bridge this gap, in this paper, we propose a fault-resistant odometry estimator, which produces robust estimates even when the sensors completely fail, or measurements progressively degrade. Our framework models the correlation between the sensor embedding using Message Passing Neural Network (MPNN), a particular type of Graph Neural Network (GNN). A mask is then computed from the updated node features of the graph to weigh the multi-modal features computed from different sensors. We evaluate the proposed fusion strategy on the modified raw KITTI dataset with sensor degradation scenarios. Finally, we compare against state-of-the-art baselines based on trivial features concatenation and soft-fusion to demonstrate our method's superiority in terms of accuracy and robustness to sensor degradation and failures
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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