A Rapid Prototyping Environment for Wireless Communication Embedded Systems

This paper introduces a rapid prototyping methodology which overcomes important barriers in the design and implementation of digital signal processing (DSP) algorithms and systems on embedded hardware platforms, such as cellular phones. This paper describes rapid prototyping in terms of a simulation/prototype bridge and in terms of appropriate language design. The simulation/prototype bridge combines the strengths of simulation and of prototyping, allowing the designer to develop and evaluate next-generation communications systems, partly in simulation on a host computer and partly as a prototype on embedded hardware. Appropriate language design allows designers to express a communications system as a block diagram, in which each block represents an algorithm specified by a set of equations. Software tools developed for this paper implement both concepts, and have been successfully used in the development of a next-generation code division multiple access (CDMA) cellular wireless communications system.NokiaTexas InstrumentsThe Texas Advanced Technology ProgramNational Science Foundatio

User engineering: A new look at system engineering

User Engineering is a new System Engineering perspective responsible for defining and maintaining the user view of the system. Its elements are a process to guide the project and customer, a multidisciplinary team including hard and soft sciences, rapid prototyping tools to build user interfaces quickly and modify them frequently at low cost, and a prototyping center for involving users and designers in an iterative way. The main consideration is reducing the risk that the end user will not or cannot effectively use the system. The process begins with user analysis to produce cognitive and work style models, and task analysis to produce user work functions and scenarios. These become major drivers of the human computer interface design which is presented and reviewed as an interactive prototype by users. Feedback is rapid and productive, and user effectiveness can be measured and observed before the system is built and fielded. Requirements are derived via the prototype and baselined early to serve as an input to the architecture and software design

Virtual assembly rapid prototyping of near net shapes

Virtual reality (VR) provides another dimension to many engineering applications. Its immersive and interactive nature allows an intuitive approach to study both cognitive activities and performance evaluation. Market competitiveness means having products meet form, fit and function quickly. Rapid Prototyping and Manufacturing (RP&M) technologies are increasingly being applied to produce functional prototypes and the direct manufacturing of small components. Despite its flexibility, these systems have common drawbacks such as slow build rates, a limited number of build axes (typically one) and the need for post processing. This paper presents a Virtual Assembly Rapid Prototyping (VARP) project which involves evaluating cognitive activities in assembly tasks based on the adoption of immersive virtual reality along with a novel non-layered rapid prototyping for near net shape (NNS) manufacturing of components. It is envisaged that this integrated project will facilitate a better understanding of design for manufacture and assembly by utilising equivalent scale digital and physical prototyping in one rapid prototyping system. The state of the art of the VARP project is also presented in this paper

PERTS: A Prototyping Environment for Real-Time Systems

PERTS is a prototyping environment for real-time systems. It is being built incrementally and will contain basic building blocks of operating systems for time-critical applications, tools, and performance models for the analysis, evaluation and measurement of real-time systems and a simulation/emulation environment. It is designed to support the use and evaluation of new design approaches, experimentations with alternative system building blocks, and the analysis and performance profiling of prototype real-time systems

The P3 platform: an approach and software system for developing diagrammatic model-based methods in design research

Many issues in design and design management have been explored by building models which capture the relationships between different aspects of the problem at hand. These models require computer support to construct and analyse. However, appropriate modelling tools can be time-consuming to develop in a research environment. Reflecting upon five design research projects, this paper proposes that such projects can be facilitated by recognising the iterative and tightly-coupled nature of research and tool development, and by attempting to minimise the effort of solution prototyping within this process. Our approach is enabled by a software platform which can be rapidly configured to implement many conceivable modelling approaches. This configurability is complemented by an emerging library of modelling and analysis approaches tailored to explore design process systems. The platform-based approach enables any mix of modelling concepts to be easily created. We propose it could thus help researchers to explore a wide range of questions without being constrained to existing conventions for modelling – or for model integration

An Octree-Based Approach towards Efficient Variational Range Data Fusion

Volume-based reconstruction is usually expensive both in terms of memory consumption and runtime. Especially for sparse geometric structures, volumetric representations produce a huge computational overhead. We present an efficient way to fuse range data via a variational Octree-based minimization approach by taking the actual range data geometry into account. We transform the data into Octree-based truncated signed distance fields and show how the optimization can be conducted on the newly created structures. The main challenge is to uphold speed and a low memory footprint without sacrificing the solutions' accuracy during optimization. We explain how to dynamically adjust the optimizer's geometric structure via joining/splitting of Octree nodes and how to define the operators. We evaluate on various datasets and outline the suitability in terms of performance and geometric accuracy.Comment: BMVC 201