A Structured Approach for Modular Design in Robotics and Automation Environments

Elkady, Ayssam; Joy, Jovin; Sobh, Tarek M.; Valavanis, Kimon P.

doi:10.1007/s10846-012-9798-y

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…different strategies for obstacle avoidance, etc). Robotics software like Robot Operating System (ROS) [12], RISCWare framework [13], Player [14] propose a hardware abstraction layer to encapsulate the sensors that gather information about the environment and provide a set of predefined intefaces. These middlewares rely on a bottom up approach which consists on classifying the most used physical sensors (or actuators), analysing the potential data they are able to provide and then define interfaces.…”

Section: Results and Validationmentioning

confidence: 99%

A Top-Down Approach to Managing Variability in Robotics Algorithms

Kchir,

Ziadi,

Ziane

et al. 2013

Preprint

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One of the defining features of the field of robotics is its breadth and heterogeneity. Unfortunately, despite the availability of several robotics middleware services, robotics software still fails to smoothly handle at least two kinds of variability: algorithmic variability and lower-level variability. The consequence is that implementations of algorithms are hard to understand and impacted by changes to lower-level details such as the choice or configuration of sensors or actuators. Moreover, when several algorithms or algorithmic variants are available it is difficult to compare and combine them.In order to alleviate these problems we propose a top-down approach to express and implement robotics algorithms and families of algorithms so that they are both less dependent on lower-level details and easier to understand and combine. This approach goes top-down from the algorithms and shields them from lower-level details by introducing very high level abstractions atop the intermediate abstractions of robotics middleware. This approach is illustrated on 7 variants of the Bug family that were implemented using both laser and infrared sensors.

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Section: Results and Validationmentioning

confidence: 99%

A Top-Down Approach to Managing Variability in Robotics Algorithms

Kchir,

Ziadi,

Ziane

et al. 2013

Preprint

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“…This means that it may become very hard to isolate events that cause robot malfunctioning. Solid robot design would also imply modular robot system with automatical detection and configuration of new sensory systems, new functions and new platforms [4].…”

Section: Examples Of Complex Systemsmentioning

confidence: 99%

“…Imagine how your system will evolve in the future. 4. Discuss challenges that software organisation may face further evolving such system.…”

Section: Exercisesmentioning

confidence: 99%

The Role of Functional Programming in Management and Orchestration of Virtualized Network Resources Part I. System structure for Complex Systems and Design Principles

Grbac¹

2021

Preprint

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this part we explain the role of functional programming paradigm in the management of complex software systems, and how the functional programming concepts play important role in the designing such systems. Key prerequisite for implementing functional programming concepts is properly designed system structure following well defined design principles and rules. That is the main goal of this lecture to introduce students with proper system modeling. Furthermore, we also explain how new emerging technologies are designed in such a way that they enforce the development of systems that comply to the design rules inspired by the functional programming. This is extremely important in view of the current network evolution and virtualization concepts, which will require many functional programming concepts in the network services and functions, as will be discussed in part II of these lecture notes. These notes provide an introduction to the subject, with the goal of explaining the problems and the principles, methods and techniques used for their solution. The worked examples and exercises serve students as the teaching material, from which they can learn how to use design principles to model effective system structures. Here we focus on students understanding of importance of effective system structures for coordination of development and management processes that are driven by business goals and further evolution.

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“…(1) Collect Laser data; (2) Robot Pose Prediction; (3) Particle sampling according to Proposal distribution; (4) Scan matching for each particle; (5) Update of particle weight; (6) Compute effective particle number; (7) If need resampling (8) if need resampling (9) Particle resampling (10) End; (11) Posterior estimation (12) Get AST and section; (13) Obtain possible nodes; When the AST is built, the furthest node is chosen as the current node , = { } (14) Build HTM; = { , } The current node the current robot pose information and the AST information; Where, is the current robot pose; (15) …”

Section: Path Planningmentioning

confidence: 99%

“…Lu et al [7] built an intelligent home space for service robot based on multipattern information model and wireless sensor networks. In order to simplify the design process of assistance robotic system and increase reusability of robotic modules, distributed technology was introduced by [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Distributed Intelligent Assistance Robotic System with Sensor Networks Based on Robot Technology Middleware

Jia

Dong

et al. 2014

International Journal of Distributed Sensor Networks

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This paper proposes a distributed intelligent assistant robotic system in order to improve the quality of the elderly people's life in the population aging society. The system is composed of embedded distributed sensor networks and multirobot intelligent platform. In the proposed system, we use SP 2 ATM (simultaneous path planning and topological mapping) with RBPF (Rao-Blackwellized particle filter) for path planning and localization of mobile robots. In order to perform service tasks, an accurate and reliable 3D environment map is reconstructed by using an effective 3D reconstruction technique from multiview stereo. Besides, the system provides user human tracking services based on multifeature mean shift under the double-layer locating mechanism. To improve the feasibility and reliability of the system, this proposed system is developed based on distributed control technology RTM (robot technology middleware). This paper presents the architecture of the proposed system and the experimental results verify effectiveness of the approaches.

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A Structured Approach for Modular Design in Robotics and Automation Environments

Cited by 8 publications

References 7 publications

A Top-Down Approach to Managing Variability in Robotics Algorithms

A Top-Down Approach to Managing Variability in Robotics Algorithms

The Role of Functional Programming in Management and Orchestration of Virtualized Network Resources Part I. System structure for Complex Systems and Design Principles

Distributed Intelligent Assistance Robotic System with Sensor Networks Based on Robot Technology Middleware

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