This paper presents a functional modeling application, FunctionCAD, based on integrated functional and process modeling within the Function Design Framework. FunctionCAD provides for mixed, hierarchical models of environment, process and function with relationships represented via flows of material, energy and signal. This paper discusses the technical details of the FunctionCAD software including its two major components: (1) the library, libFCAD, for handling the internal representation of the model and (2) the GUI for user-based model manipulation and visualization. The application of FunctionCAD within a computational, function-based conceptual design process is discussed along with the plugin manager and interface that have been developed as a part of the FunctionCAD software to allow interconnectivity with existing conceptual design tools. And finally, a detailed description of model creation within the FunctionCAD environment is provided to illustrate software operability.

No abstract

An engineering design framework for an autonomous ground vehicle vision system is discussed. We present both the conceptual and physical design by following the design process, development and testing of an intelligent ground vehicle vision system constructed for the 2008 Intelligent Ground Vehicle Competition. During conceptual design, the requirements for the vision system are explored via functional and process analysis considering the flows into the vehicle and the transformations of those flows. The conceptual design phase concludes with a vision system design that is modular in both hardware and software and is based on a laser range finder and camera for visual perception. During physical design, prototypes are developed and tested independently, following the modular interfaces identified during conceptual design. Prototype models, once functional, are implemented into the final design. The final vision system design uses a ray-casting algorithm to process camera and laser range finder data and identify potential paths. The ray-casting algorithm is a single thread of the robot's multithreaded application. Other threads control motion, provide feedback, and process sensory data. Once integrated, both hardware and software testing are performed on the robot. We discuss the robot's performance and the lessons learned. Nagel et al.: Function-based design process for an intelligent ground vehicle vision system Robert L. Nagel is currently an assistant professor with the School of Engineering at James Madison University. Dr. Nagel received his PhD degree from Oregon State University, his MS degree from the University of Missouri-Rolla (known now as Missouri University of Science and Technology), and his BS degree from Tri-State University (known now as Trine University). He has been a member of the Design Engineering Lab, a researcher at General Motors in the Vehicle Development Research Lab, and has worked on contract projects with both the United States Army and United States Air Force. His research interests include understanding customer needs, functional and process modeling, failure analysis, design for sustainability, design of mechatronic systems, and systems integration. Kenneth L. Perry is currently the lead developer for Interdisciplinary Design Collaborative, LLC, in Rolla, Missouri. Perry is working toward his MS degree in the area of software compilers with the Computer Science Department at the Missouri University of Science and Technology, where he received his BS degree. Perry has been an undergraduate researcher with the Design Engineering Lab and has worked on several software development projects such as FunctionCAD (a functional modeling design tool), and the Intelligent Ground Vehicle Competition (IGVC) robot MAX. Nagel et al.: Function-based design process for an intelligent ground vehicle vision system Robert B. Stone is a professor with the School of Mechanical, Industrial and Manufacturing Engineering at Oregon State University. Dr. Stone's research interests include design theories an...

The development of a vision system for an autonomous ground vehicle designed and constructed for the Intelligent Ground Vehicle Competition (IGVC) is discussed. The requirements for the vision system of the autonomous vehicle are explored via functional analysis considering the flows (materials, energies and signals) into the vehicle and the changes required of each flow within the vehicle system. Functional analysis leads to a vision system based on a laser range finder (LIDAR) and a camera. Input from the vision system is processed via a ray-casting algorithm whereby the camera data and the LIDAR data are analyzed as a single array of points representing obstacle locations, which for the IGVC, consist of white lines on the horizontal plane and construction markers on the vertical plane. Functional analysis also leads to a multithreaded application where the ray-casting algorithm is a single thread of the vehicle's software, which consists of multiple threads controlling motion, providing feedback, and processing the data from the camera and LIDAR. LIDAR data is collected as distances and angles from the front of the vehicle to obstacles. Camera data is processed using an adaptive threshold algorithm to identify color changes within the collected image; the image is also corrected for camera angle distortion, adjusted to the global coordinate system, and processed using least-squares method to identify white boundary lines. Our IGVC robot, MAX, is utilized as the continuous example for all methods discussed in the paper. All testing and results provided are based on our IGVC robot, MAX, as well.