419 research outputs found

    Model-driven engineering approach to design and implementation of robot control system

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    In this paper we apply a model-driven engineering approach to designing domain-specific solutions for robot control system development. We present a case study of the complete process, including identification of the domain meta-model, graphical notation definition and source code generation for subsumption architecture -- a well-known example of robot control architecture. Our goal is to show that both the definition of the robot-control architecture and its supporting tools fits well into the typical workflow of model-driven engineering development.Comment: Presented at DSLRob 2011 (arXiv:cs/1212.3308

    Automated Image Interpretation for Science Autonomy in Robotic Planetary Exploration

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    Advances in the capabilities of robotic planetary exploration missions have increased the wealth of scientific data they produce, presenting challenges for mission science and operations imposed by the limits of interplanetary radio communications. These data budget pressures can be relieved by increased robotic autonomy, both for onboard operations tasks and for decision- making in response to science data. This thesis presents new techniques in automated image interpretation for natural scenes of relevance to planetary science and exploration, and elaborates autonomy scenarios under which they could be used to extend the reach and performance of exploration missions on planetary surfaces. Two computer vision techniques are presented. The first is an algorithm for autonomous classification and segmentation of geological scenes, allowing a photograph of a rock outcrop to be automatically divided into regions by rock type. This important task, currently performed by specialists on Earth, is a prerequisite to decisions about instrument pointing, data triage, and event-driven operations. The approach uses a novel technique to seek distinct visual regions in outcrop photographs. It first generates a feature space by extracting multiple types of visual information from the image. Then, in a training step using labeled exemplar scenes, it applies Mahalanobis distance metric learning (in particular, Multiclass Linear Discriminant Analysis) to discover the linear transformation of the feature space which best separates the geological classes. With the learned representation applied, a vector clustering technique is then used to segment new scenes. The second technique interrogates sequences of images of the sky to extract, from the motion of clouds, the wind vector at the condensation level — a measurement not normally available for Mars. To account for the deformation of clouds and the ephemerality of their fine-scale features, a template-matching technique (normalized cross-correlation) is used to mutually register images and compute the clouds’ motion. Both techniques are tested successfully on imagery from a variety of relevant analogue environments on Earth, and on data returned from missions to the planet Mars. For both, scenarios are elaborated for their use in autonomous science data interpretation, and to thereby automate certain steps in the process of robotic exploration

    Information and Communication Technologies for Integrated Operations of Ships

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    Over the past three decades, information and communication technologies have filled our daily life with great comfort and convenience. As the technology keeps evolving, user expectations for more challenging cases that can benefit from advanced information and communication technologies are increasing, e.g., the scenario of Integrated Operations (IO) for ships in the maritime domain. However, to realize integrated operations for ships is a complex task that involves addressing problems such as interoperability among heterogeneous operation applications and connectivity within harsh maritime communication environments. The common approach was to tackle these challenges separately by service integration and communication integration, respectively: each utilizes optimized and independent implementations. Separate solutions work fine within their own contexts, whereas conflicts and inconsistencies can be identified by integrating them together for specific maritime scenarios. Therefore, connection between separate solutions needs to be studied. In this dissertation, we first take a look at complex systems to obtain useful methodologies applied to integrated operations for ships. Then we study IO of ships from different perspectives and divide the complex task into sub-tasks. We explore separate approaches to these sub-tasks, examine the connection in between, resolve inconsistencies if there are any, and continue the exploration process till a compatible and integrated solution can be accomplished. In general, this journey represents our argument for an integration-oriented complex system development approach. In concrete, it shows the way on how to achieve IO of ships by both providing connectivity in harsh communication environments and allowing interoperability among heterogeneous operation applications, and most importantly by ensuring the synergy in between. This synergy also gives hints on the evolution towards a next generation network architecture for the future Internet
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