85,089 research outputs found
Deep Semantic Classification for 3D LiDAR Data
Robots are expected to operate autonomously in dynamic environments.
Understanding the underlying dynamic characteristics of objects is a key
enabler for achieving this goal. In this paper, we propose a method for
pointwise semantic classification of 3D LiDAR data into three classes:
non-movable, movable and dynamic. We concentrate on understanding these
specific semantics because they characterize important information required for
an autonomous system. Non-movable points in the scene belong to unchanging
segments of the environment, whereas the remaining classes corresponds to the
changing parts of the scene. The difference between the movable and dynamic
class is their motion state. The dynamic points can be perceived as moving,
whereas movable objects can move, but are perceived as static. To learn the
distinction between movable and non-movable points in the environment, we
introduce an approach based on deep neural network and for detecting the
dynamic points, we estimate pointwise motion. We propose a Bayes filter
framework for combining the learned semantic cues with the motion cues to infer
the required semantic classification. In extensive experiments, we compare our
approach with other methods on a standard benchmark dataset and report
competitive results in comparison to the existing state-of-the-art.
Furthermore, we show an improvement in the classification of points by
combining the semantic cues retrieved from the neural network with the motion
cues.Comment: 8 pages to be published in IROS 201
RAFDA: A Policy-Aware Middleware Supporting the Flexible Separation of Application Logic from Distribution
Middleware technologies often limit the way in which object classes may be
used in distributed applications due to the fixed distribution policies that
they impose. These policies permeate applications developed using existing
middleware systems and force an unnatural encoding of application level
semantics. For example, the application programmer has no direct control over
inter-address-space parameter passing semantics. Semantics are fixed by the
distribution topology of the application, which is dictated early in the design
cycle. This creates applications that are brittle with respect to changes in
distribution. This paper explores technology that provides control over the
extent to which inter-address-space communication is exposed to programmers, in
order to aid the creation, maintenance and evolution of distributed
applications. The described system permits arbitrary objects in an application
to be dynamically exposed for remote access, allowing applications to be
written without concern for distribution. Programmers can conceal or expose the
distributed nature of applications as required, permitting object placement and
distribution boundaries to be decided late in the design cycle and even
dynamically. Inter-address-space parameter passing semantics may also be
decided independently of object implementation and at varying times in the
design cycle, again possibly as late as run-time. Furthermore, transmission
policy may be defined on a per-class, per-method or per-parameter basis,
maximizing plasticity. This flexibility is of utility in the development of new
distributed applications, and the creation of management and monitoring
infrastructures for existing applications.Comment: Submitted to EuroSys 200
Automating the transformation-based analysis of visual languages
The final publication is available at Springer via http://dx.doi.org/10.1007/s00165-009-0114-yWe present a novel approach for the automatic generation of model-to-model transformations given a description of the operational semantics of the source language in the form of graph transformation rules. The approach is geared to the generation of transformations from Domain-Specific Visual Languages (DSVLs) into semantic domains with an explicit notion of transition, like for example Petri nets. The generated transformation is expressed in the form of operational triple graph grammar rules that transform the static information (initial model) and the dynamics (source rules and their execution control structure). We illustrate these techniques with a DSVL in the domain of production systems, for which we generate a transformation into Petri nets. We also tackle the description of timing aspects in graph transformation rules, and its analysis through their automatic translation into Time Petri netsWork sponsored by the Spanish Ministry of Science and Innovation, project METEORIC (TIN2008-02081/TIN) and by the Canadian Natural Sciences and Engineering Research Council (NSERC)
Soundly Handling Static Fields: Issues, Semantics and Analysis
Although in most cases class initialization works as expected, some static
fields may be read before being initialized, despite being initialized in their
corresponding class initializer. We propose an analysis which compute, for each
program point, the set of static fields that must have been initialized and
discuss its soundness. We show that such an analysis can be directly applied to
identify the static fields that may be read before being initialized and to
improve the precision while preserving the soundness of a null-pointer
analysis.Comment: Proceedings of the Fourth Workshop on Bytecode Semantics,
Verification, Analysis and Transformation (BYTECODE 2009
A graph-based aspect interference detection approach for UML-based aspect-oriented models
Aspect Oriented Modeling (AOM) techniques facilitate separate modeling of concerns and allow for a more flexible composition of these than traditional modeling technique. While this improves the understandability of each submodel, in order to reason about the behavior of the composed system and to detect conflicts among submodels, automated tool support is required. Current techniques for conflict detection among aspects generally have at least one of the following weaknesses. They require to manually model the abstract semantics for each system; or they derive the system semantics from code assuming one specific aspect-oriented language. Defining an extra semantics model for verification bears the risk of inconsistencies between the actual and the verified design; verifying only at implementation level hinders fixng errors in earlier phases. We propose a technique for fully automatic detection of conflicts between aspects at the model level; more specifically, our approach works on UML models with an extension for modeling pointcuts and advice. As back-end we use a graph-based model checker, for which we have defined an operational semantics of UML diagrams, pointcuts and advice. In order to simulate the system, we automatically derive a graph model from the diagrams. The result is another graph, which represents all possible program executions, and which can be verified against a declarative specification of invariants.\ud
To demonstrate our approach, we discuss a UML-based AOM model of the "Crisis Management System" and a possible design and evolution scenario. The complexity of the system makes con°icts among composed aspects hard to detect: already in the case of two simulated aspects, the state space contains 623 di®erent states and 9 different execution paths. Nevertheless, in case the right pruning methods are used, the state-space only grows linearly with the number of aspects; therefore, the automatic analysis scales
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