Satyandra K. Gupta - US grants

With support from the National Science Foundation's Innovation and Organizational Change Program and GOALI, this research focuses on the development of an intelligent product representation for evolvable designs that can determine when new innovation indicates that a change in a previous decision is warranted. Deciding when to redesign a product is one of the most important decisions made by any company. Incorrect redesign timing can lead to a variety of problems and poor market response. Current strategies for deciding when to redesign products are usually ad hoc in nature, and may result in a significant lag between the time a technological innovation occurs and the time when it is successfully incorporated into a product design.

The researchers are developing decision-making models that will work on intelligent product representations and generate suggestions for redesign These decision making models perform a detailed trade-off analysis whenever technological or business constraints change in the intelligent product representation. These models incorporate decision variables, design constraints, and evaluation criteria that have led to the decisions currently in use. The project will develop a multi-disciplinary course sequence that will incorporate the latest advances in the management of technology area into engineering and business curriculum.

EIA-9986012
Dana S. Nau
University of Maryland-College Park

CISE Research Instrumentation: A Specialized Computing Environment for Distributed and Virtual Design and Manufacturing.

The University of Maryland will create a specialized computing environment for distributed and virtual design and manufacturing. This facility will support research in computer and information science sand engineering. The University of Maryland will purchase two graphics workstations, two NT-based servers, and the necessary software for developing the facility. The computing environment will be dedicated to several on-going projects on distributed and virtual design and manufacturing. These projects will yield specific contributions in areas related to computing and information systems. With this facility, the investigators can install and integrate our approaches, share data across various projects effectively, and test our results more thoroughly. Thus we can study and solve the computational challenges that will occur as manufacturers develop advanced, information-based product realization processes

This Presidential Early Career Award for Scientists and Engineers (PECASE) grant supports an integrated research and education project in the area of automated design of multi-piece molds for manufacturing geometrically complex heterogeneous objects. Its goal is to develop underlying algorithms that will enable development of computer-aided design and manufacturing (CAD/CAM) systems for automatically designing multi-piece molds. The research effort will focus on: (1) characterization of the new design space enabled by multi-piece molds; (2) development of geometric reasoning algorithms for decomposing molds into manufacturable components; and (3) development of geometric reasoning algorithms for incorporating assembly features into mold components for facilitating mold assembly. The education effort will focus on: (1) introduction of rigorous algorithmic foundations into CAD/CAM courses; (2) familiarizing students with the challenges in the CAD/CAM system development; and (3) providing students an opportunity to develop prototype CAD/CAM systems for design and manufacturing of multi-piece molds. Outreach projects will be initiated to expose high school students to the CAD/CAM field and give them an opportunity to make a more informed career choice; and, allow industry to learn about new CAD/CAM and heterogeneous object manufacturing technologies.

If successful this project will have the following impacts. First, it will lead to the development of new geometric reasoning algorithms in manufacturability analysis and manufacturability-driven spatial partitioning areas. In addition to mold design, these algorithms will be useful in several other CAD/CAM applications. Second, it will provide a commercially viable method for making geometrically complex heterogeneous objects. The ability to manufacture geometrically complex heterogeneous objects economically will significantly expand the design space and will allow development of new products in many different areas. Finally, integration of geometric reasoning principles into the mechanical engineering curriculum will help in creating a new generation of engineers who will have exposure to geometric algorithms in addition to traditional mechanical engineering curriculum. This exposure is expected to help in preparing engineers for participating in the development of the next generation CAD/CAM systems.

0243803 Gupta

This award funds a five-year Research Experience for Undergraduates (REU) Site at the University of Maryland for fifteen students each summer for twelve weeks for research opportunities at the university's Institute for Systems Research. Students at colleges, universities, and community colleges will be recruited nationwide through a process involving efforts to reach students who would otherwise not have access to a research experience. The program incorporates activities that will involve participants in the following research directions of the institute: global communications systems, sensor-actuator networks, next-generation product realization systems, societal infrastructure systems, and cross-disciplinary systems education. Through the program students will be able to (1) establish a basis for systems thinking by conducting research and thus understand systems engineering as a discipline; (2) acquire broader and deeper understanding of both the research process and the practice of engineering and how new knowledge is created and communicated; (3) develop multicultural understanding and team competence and become aware of the societal implications of research; and (5) successfully seek admission in a four-year program and/or graduate school.

Curriculum Enhancement to Introduce
Product Development with Bio-Inspired Concepts
Hugh Bruck, Satyandra Gupta, Edward Magrab, and Elisabeth Smela

Mechanical Engineering Department
University of Maryland, College Park, Maryland

Bio-inspired products and devices take their inspiration from nature. Current mechanical engineering curricula do not cover design concepts or manufacturing techniques needed to develop such products and devices. We propose to enhance the mechanical engineering undergraduate curriculum by integrating recent advances in the design, analysis, and manufacturing of bio-inspired products and devices through the following objectives:
1. Insert a new sequence of instructional materials on bio-inspired concepts into the mechanical
engineering curriculum.
2. Develop a new senior elective entitled Product Development Using Bio-inspired Concepts.
3. Revise two senior electives in micro-electromechanical systems area to include more complete
treatments of special manufacturing processes that can be used to realize bio-inspired products.
4. Assess the projects of the undergraduate mechanical engineering students in their capstone design
course to evaluate their retention and utilization of the new material.
5. Conduct one workshop to transfer the new materials and establish a feedback mechanism for
enhancing the curriculum.
6. Disseminate the materials developed for the new modules and the course notes for the new senior
elective through a dedicated web site.
7. Present a summary of our experiences at two conferences.

The result of the proposed curriculum enhancement will be a new generation of mechanical engineers who can develop products and conduct research for a wide variety of applications utilizing bio-inspired concepts. The proposed project will (1) integrate emerging manufacturing technologies and new design analyses based on biological principles into the Mechanical Engineering curriculum, (2) utilize multi-media technology for disseminating course content, and (3) train graduate students and faculty participating in its implementation in an emerging technology and thereby contribute to faculty development.

The objective of this research is to develop a novel multi-stage molding process for creating a new class of articulated devices that have mesoscopic features essential to the miniaturization of products in a cost-competitive manner. The approach that will be employed consists of several steps. First, interfacial adhesion phenomena encountered during the multi-stage molding process will be characterized and their relationship to process variables will be established. This knowledge will be utilized to explore alternative ways to limit adhesion at interfaces and hence create articulated joints by easily separating discrete components without breaking them. Second, viability of various cavity shape change methods and ejection mechanisms will be assessed for realizing mesoscopic joints using multi-stage molding. This knowledge will be utilized to optimize tooling configurations for making mesoscopic articulated devices. Finally, an improved understanding of the influence that process parameters for microscale electrical discharge machining have on the resulting surface characteristics and dimensional accuracies will be developed. This knowledge will be utilized to create mold inserts to be used in the new molding process that will be essential to defining the limitations on the size of the mesoscopic features.
The proposed project is expected to have the following broader impacts. First, for mesoscopic articulated devices that can be manufactured using the new molding process, the process can be easily scaled down in size and scaled up in production quantity. Hence, this research is expected to enable new possibilities for miniaturizing products. Second, the new molding process will significantly reduce assembly operations and make manufacturing significantly less labor-intensive. Therefore manufacturing of mesoscopic devices can be done quickly and easily inside the US in a cost-competitive manner. Therefore the proposed research effort will enhance the competitiveness of the US manufacturing sector. Finally, the research results will be integrated in the manufacturing curriculum to educate a new generation of engineers ready to exploit emerging manufacturing technologies to create new products.

The objective of this project is the creation of a comprehensive, multi-disciplinary approach to engineering informatics education. The team will use the domain of biologically-inspired robotic systems as a means of engaging engineering and computer science students in the creation of physically realized systems. These systems have been shown to have important applications in medicine, civil engineering, search and rescue, and homeland security. This project will also develop and deploy the novel cyber-infrastructure and software tools needed to advance the state-of-the-art in bio-inspired robotic systems and biologically-inspired robotics education. A repository of educational materials, designs and models will be made available over the Internet and provided for use by educators and researchers around the country.
In this way, this project aims to create mechanisms for education and training of multi-disciplinary engineers who are versed in the cyber-infrastructure tools and understand how they can use them to transform and harness collective human problem solving capabilities.

The project contributes to the transformation of engineering into an ``informatics'' discipline and tightens the interaction computer science and engineering. Ultimately, engineering informatics will become an instrumental part of undergraduate and graduate curricula in engineering and computer science. In addition, the bio-inspired robotics domain will prove to be a source of exciting and attractive materials and demonstrations. These materials and demonstrations will be used in outreach and secondary education activities to expose students to engineering and computer science concepts and increase the participation of under-represented groups in these professions. The team plans to leverage numerous ongoing outreach and training activities at the respective institutions to maximize the impact of the project.

The objective of this award is to develop a mathematical theory and computational framework for the automatic generation of context-dependent simplified models to support interactive virtual assembly applications. Interactive virtual assembly is emerging as an important tool for evaluating ease-of assembly of proposed products, and training assembly operators. With the advent of low cost personal virtual environments, interactive virtual assembly holds the promise of replacing expensive, and time consuming, physical prototyping and training. However, real-time interactions in low-cost virtual environments can only be achieved through judicious model simplification. Through a fundamental understanding of the interplay between model simplification, computational speed and accuracy, a framework will be developed for optimizing model simplification for virtual assembly.

If successful, the results of this research will enable interactive virtual assembly with provable performance guarantee on low cost personal virtual environment, leading to a significant increase in the use of virtual assembly technology in design and training applications. The proposed work is expected to lead to: (1) reduction in training cost by eliminating one-on-one training, and reducing the use of physical prototypes, and (2) better assembly designs by ensuring ease-of-assembly. Efficient and effective training methods will lead to a more agile workforce that is capable of quickly adapting to the changing requirements of the manufacturing industry. In addition, the planned research and education integration activities and outreach activities will: (1) familiarize graduate, undergraduate, and high school students with the use of virtual assembly and model simplification technologies, and (2) increase awareness among industry about potential usage of virtual assembly on low cost personal virtual environments.

Assembling nanoscale components to make functional devices remains a grand challenge despite rapid advances in imaging, measurement, and fabrication at the nanoscale. While manipulation techniques for nanocomponents are finally emerging they currently lack automation. The lack of automation seriously limits the rate at which new nanocomponent-based devices can be invented. In order to develop automated real-time planning algorithms, we need to develop a fundamental understanding of the interaction of nanocomponents with trapping fields. Understanding different ways in which components can interact with the trap requires dense sampling of the planning parameter space using millions of computationally intensive simulation runs. The proposed project will focus on (1) development of GPU-based simulation infrastructure for simulating trap and nanocomponent interactions, (2) development of algorithms for automatically constructing simplified assembly process models from simulation data, (3) development of visualization tools for enhancing the understanding of the nanoscale assembly processes, (4) identification and characterization of real-time motion planning strategies for nanoscale assembly processes, and (5) integration of the proposed the research results with education and wider dissemination.

The proposed work will lead to a reliable, efficient, and automated assembly process for fabricating nanocomponent-based devices. We expect that this assembly process will enable nanotechnology researchers to explore new design possibilities in the area of nano electronics, nano photonics, and bio-inspired sensors. Automated assembly capability will also allow them to explore a large number of design options in a cost effective manner and hence accelerate discovery and invention. The proposed research will significantly reduce the need for manual assembly operations and will make nanomanipulation significantly less labor-intensive thereby facilitating the manufacturing of nanodevices in a cost-competitive manner. The proposed project will also create training and education materials in the areas of GPU-based simulations, interactive visualization at nanoscale, automated model construction, and real-time motion planning.

CPS: Small: Image Guided Autonomous Optical Manipulation of Cell Groups

The objective of this research is to create computational foundation, methods, and tools for efficient and autonomous optical micromanipulation using microsphere ensembles as grippers. The envisioned system will utilize a holographic optical tweezer, which uses multiple focused optical traps to position microspheres in three-dimensional space. The proposed approach will focus on the following areas. First, it will provide an experimentally validated optical-tweezers based workstation for concurrent manipulation of multiple cells. Second, it will provide algorithms for on-line monitoring of workspace to support autonomous manipulation. Finally, it will provide real-time image-guided motion planning strategies for transporting microspheres ensembles.

The proposed work will lead to a new way of autonomously manipulating difficult-to-trap or sensitive objects using microspheres ensembles as reconfigurable grippers. The proposed work will also lead to fundamental advances in several cyber physical systems areas by providing new approaches to micromanipulations, fast and accurate algorithms with known uncertainty bounds for on-line monitoring of moving microscale objects, and real-time motion planning algorithms to transport particle ensembles.

The ability to quickly and accurately manipulate individual cells with minimal training will enable researchers to conduct basic research at the cellular scale. Control over cell-cell interactions will enable unprecedented insights into cell signaling pathways and open up new avenues for medical diagnosis and treatment. The proposed integration of research with education will train students with a strong background in emerging robotics technologies and the inner workings of cells. These students will be in a unique position to rapidly develop and deploy specialized robotics technologies.

The objective of this three year REU Site program is to provide new and exciting summer research opportunities for undergraduate students in the field of miniature robotics. Miniature robots, defined as small robots with overall sizes between 1mm and 100mm have the potential to significantly enable or enhance capabilities in manufacturing, medicine, reconnaissance, exploration, food safety, and search and rescue. Because of their size, miniature robotics offer a truly interdisciplinary systems research challenge that encompasses materials, mechanical design, control, sensors and actuators, power, and electronics. The Maryland Robotics Center and the Institute for Systems Research at the University of Maryland (UMd)has the expertise and facilities needed to provide research opportunities to undergraduates in miniature robotics.

In this REU Site program approximately 50% of participants will be women and 30% will be underrepresented minorities. This REU Site program will focus on career and academic development of undergraduate students in addition to providing a new network of role models through a diverse mentoring pool. A more diverse group of highly educated researchers will create a larger workforce to solve the nations toughest environmental, technical, and national security challenges.

The objective of this award is to develop feature-based simplification of computer-aided-design models, specifically to accelerate and automate downstream finite-element-analysis. In particular, the research will create algorithmic foundations for learning conservative feature suppression rules from demonstrations performed by human experts. The effect of simplification on simulation accuracy will be formally characterized and this understanding will be used to create robust algorithms for feature suppression within computer-aided design models. Research findings will be integrated into graduate and undergraduate curriculum. The research will ultimately lead to a framework to automatically learn, validate, and apply context dependent model simplification rules that can be audited by human experts, and deployed to automate the model simplification task.

If successful, the research will significantly speed up model simplification, and enhance the automated use of engineering analysis tools in the design process. Potential applications include design of heat exchangers, aircraft structures, and semi-conductor equipment. The planned research and education integration activities and outreach activities will familiarize graduate, undergraduate, and high school students with the use of model simplification technologies in challenging engineering design projects. This project will also increase awareness among practicing engineers about the potential usage of automated model simplification in complex engineering design projects. Students working on this project will also participate in Badger Camp and Engineering Expo events at the University of Wisconsin campus and Maryland Day at the University of Maryland to enhance the public understanding of the science and technology.

Over the last ten years, substantial progress has been made in the development of small low-cost unmanned surface vehicles (USVs). There are a number of civilian applications where deploying a human-robot team consisting of several small USVs and one or more human supervisors can significantly reduce costs, improve safety, and increase operational efficiencies. Representative applications include remote/persistent ocean sensing, marine search and rescue, maritime operations in congested port environments, and industrial offshore supply and support. USVs face unique challenges that are not experienced by robots operating indoors, such as: the need to adhere to marine navigation rules (COLREGs); local current, wave and wind conditions that can severely reduce the dynamic range of sensors and actuators; frequent communication interruptions; and risk and urgency due to rapidly changing situations during outdoor on-water operations. This research aims to develop decision making foundations for enabling teams of humans and USVs to perform complex collaborative tasks. Advances in this area could be extremely important from both a regulatory and practical standpoint for the future deployment of USV systems. Results from this research will enable leveraging the tremendous potential of USVs by reducing the cost of deployment and operational risks in civilian applications. The integration of the research with graduate and undergraduate courses will enhance the robotics and ocean engineering curricula and enrich learning experiences of the participating students. Outreach activities will educate and inform K-12 students about career opportunities in marine robotics.

The overall goal of the proposed effort is to make advances in risk-informed decision making so that teams of USVs and human supervisors can work cooperatively on a wide variety of missions. The proposed work will develop a comprehensive distributed decision making approach by leveraging the latest advances in task coordination and assignment, planning, reactive behaviors, and control to enable the deployment of human-guided USV teams in civilian applications. Progress in these constituent components will be pursued to ensure that they are consistent with each other and to explicitly account for risk during decision making. This research will develop methodologies to model team missions to ensure that all phases of decision making will have the required information for making informed decisions. Decision making methodologies will be developed for sparse advisory control of USV teams to mitigate risks and for coordinating and assigning tasks to different USVs in the team. Algorithms will also be developed for risk-aware deliberative trajectory planning and generating and executing reactive behaviors for mitigating risks. The methods developed will be validated through on-water field experiments.