Analogy Mining for Specific Design Needs

Finding analogical inspirations in distant domains is a powerful way of solving problems. However, as the number of inspirations that could be matched and the dimensions on which that matching could occur grow, it becomes challenging for designers to find inspirations relevant to their needs. Furthermore, designers are often interested in exploring specific aspects of a product-- for example, one designer might be interested in improving the brewing capability of an outdoor coffee maker, while another might wish to optimize for portability. In this paper we introduce a novel system for targeting analogical search for specific needs. Specifically, we contribute a novel analogical search engine for expressing and abstracting specific design needs that returns more distant yet relevant inspirations than alternate approaches

Online Deep Learning for Improved Trajectory Tracking of Unmanned Aerial Vehicles Using Expert Knowledge

This work presents an online learning-based control method for improved trajectory tracking of unmanned aerial vehicles using both deep learning and expert knowledge. The proposed method does not require the exact model of the system to be controlled, and it is robust against variations in system dynamics as well as operational uncertainties. The learning is divided into two phases: offline (pre-)training and online (post-)training. In the former, a conventional controller performs a set of trajectories and, based on the input-output dataset, the deep neural network (DNN)-based controller is trained. In the latter, the trained DNN, which mimics the conventional controller, controls the system. Unlike the existing papers in the literature, the network is still being trained for different sets of trajectories which are not used in the training phase of DNN. Thanks to the rule-base, which contains the expert knowledge, the proposed framework learns the system dynamics and operational uncertainties in real-time. The experimental results show that the proposed online learning-based approach gives better trajectory tracking performance when compared to the only offline trained network.Comment: corrected version accepted for ICRA 201

Knowledge Transfer Between Robots with Similar Dynamics for High-Accuracy Impromptu Trajectory Tracking

In this paper, we propose an online learning approach that enables the inverse dynamics model learned for a source robot to be transferred to a target robot (e.g., from one quadrotor to another quadrotor with different mass or aerodynamic properties). The goal is to leverage knowledge from the source robot such that the target robot achieves high-accuracy trajectory tracking on arbitrary trajectories from the first attempt with minimal data recollection and training. Most existing approaches for multi-robot knowledge transfer are based on post-analysis of datasets collected from both robots. In this work, we study the feasibility of impromptu transfer of models across robots by learning an error prediction module online. In particular, we analytically derive the form of the mapping to be learned by the online module for exact tracking, propose an approach for characterizing similarity between robots, and use these results to analyze the stability of the overall system. The proposed approach is illustrated in simulation and verified experimentally on two different quadrotors performing impromptu trajectory tracking tasks, where the quadrotors are required to accurately track arbitrary hand-drawn trajectories from the first attempt.Comment: European Control Conference (ECC) 201

Crossroads, Connections, and Creativity: Musselman Library Strategic Plan

The Musselman Library Strategic Plan grew out of two all-staff meetings held in January 2007. During the first, library staff identified areas of strength and weakness, as well as opportunities for improvement and growth. Maureen Sullivan, an organization development consultant for libraries, led the next meeting. Ms. Sullivan helped to deepen the analysis begun during the previous meeting and encouraged the staff to begin envisioning the future of the Library. In late January, Robin Wagner, Director of Library Services, formed the Strategic Planning Committee (see list of participants below). The committee’s initial tasks were to complete an environmental scan and to identify upcoming trends and best practices in library services, while formulating mission and vision statements for Musselman Library. These were presented to the rest of the staff for feedback during meetings in March and April. Also in April, the Strategic Planning Committee invited other library staff to serve on task forces charged with creating goals and action items for the plan’s four core issues (see Appendix C). Maureen Sullivan facilitated the launching of these task forces, and each group, led by a member of the Strategic Planning Committee, then met independently numerous times during the next few weeks. The final task force reports were completed in early May and shared with the entire library staff. On May 21, Maureen Sullivan led an all-staff meeting to discuss the task force recommendations. Ms. Sullivan then met with the Strategic Planning Committee and Robin Wagner to begin the process of revising, prioritizing, and incorporating the goals and action items into one cohesive strategic plan. Crossroads, Connections, and Creativity: Musselman Library Strategic Plan was submitted to Robin Wagner, on June 12, 2007. [excerpt

Friends of Musselman Library Newsletter Spring 2005

Table of Contents: From the Director: “Forever Free” Abraham Lincoln Exhibit (Robin Wagner, Christina Ericson Hansen ’92, Gabor Boritt); Fortenbaugh Internship Expands (Julia Grover ’06, Anne Kennedy ’05); Bontanicals Brighten Browsing Room (Jim Ramos); Asian Art Award Announced (Karen Drickamer); Apache Visions: Exhibit Features Skateboard Art; Barbara Holley Establishes Preservation Fund for Library (Barbara Holley ’54); Library News: Athletic Windfall, Reading Al Fresco, Library Tunes, Newspaper and Magazine Browsing, Majestic Theatre Exhibit, Civil War Manuscripts, Oral History, FoML Helps New Voters (Henry T. Bream ’24, Jack Bream ’57, Robert C. ’62, Marsha Parker ’62, Dr. William Sunderman Senior ’19, Jake Yingling ’52 and Genevieve Yingling); Student Projects Featured in Music Exhibition (Dr. William Sunderman Senior ’19, Tim Sestrick, Marta Robertson); In Her Own Words; Spring Lecture on Citron (Molly Hutton, Thomas Citron ’47, Virginia Eshbach Citron ’47); Second Spring Friends Lecture: “The Cyclorama Building and the Loss of Cultural Landscape at Gettysburg”; Focus on Philanthropy: Gift Supports Purchases of Nineteenth Century Documents (Dr. Bradley Hoch); Giving Students a Break (Meggan Emler Smith \u2704, Anne Kennedy, Sujita Kong); Spotlight on Collecting: Captivity Narritives (Edward Maharay, Janet Hancock Maharay ’39, Tim Shannon); Weird and Gross in the Librar

You\u27ve Gotta Read This: Summer Reading at Musselman Library (2004)

Each year Musselman Library asks Gettysburg College faculty, staff, and administrators to help create a suggested summer reading list to inspire students and the rest of our campus community to take time in the summer to sit back, relax, and read. These summer reading picks are guaranteed to offer much adventure, drama, and fun! The spring 2004 issue of You’ve Gotta Read This! expanded to include recommendations from Gettysburg College staff and administrators in addition to faculty. Popular titles for this year were A Short History of Nearly Everything by Bill Bryson and Dan Brown’s The Da Vinci Code.https://cupola.gettysburg.edu/summerreads/1009/thumbnail.jp

You\u27ve Gotta Read This: Summer Reading at Musselman Library (2007)

Each year Musselman Library asks Gettysburg College faculty, staff, and administrators to help create a suggested summer reading list to inspire students and the rest of our campus community to take time in the summer to sit back, relax, and read. These summer reading picks are guaranteed to offer much adventure, drama, and fun!https://cupola.gettysburg.edu/summerreads/1006/thumbnail.jp