Table of Contents. Page #'s Title Name Department Controlling Robots in Cluttered Environments Marc Killpack Mechanical Engineering

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1 Table of Contents Page #'s Title Name Department 2-12 Controlling Robots in Cluttered Environments Marc Killpack Mechanical Engineering Multidisciplinary Design Optimization of Aircraft and Wind Turbines Andrew Ning Mechanical Engineering Alternate Reality Games for STEM Learning Derek Hansen Information Technology Research on Permanent Digital Data Storage Barry Lunt Information Technology

2 Controlling Robots in Cluttered Environments Marc Killpack Mechanical Engineering (801) Areas of Interest: Haptic and proximity sensing; Variable impedance control; Real time optimal control; Human robot interaction

3 Controlling Robots in Cluttered Environments Marc D. Killpack Research interests: haptic and proximity sensing, variable impedance control, real time optimal control, human robot interaction

4 Industrial Robots Are. Fast Accurate Repeatable 3

5 Most Robots Are Not Reactive Compliant Aware 4

6 Manipulation in Clutter 5

7 Robot Reaching in Clutter 6

8 Robots with Compliance at the Joints

9 Robots with Compliance at the Joints

10 Controlling Robots with Compliance at the Joints

They are cheaper(10 times cheaper), lighter (10 times lighter), smaller (10 times smaller

11 Controlling Soft Robots They can provide significant benefits in terms of human assistance and collaboration, rugged terrain exploration, or equipment maintenance. They are cheaper(10 times cheaper), lighter (10 times lighter), smaller (10 times smaller packing volume). Platform could be useful in other areas such as search and rescue or disaster response.

12 Current Research Questions How can we improve trajectory following in free space for robot arms that have compliance in the links and joints? How can we modify joint impedance on the fly to mitigate effects from unexpected and uncertain contact locations? How can we model discontinuous contact mechanics in order to incorporate it in our controller formulations? Can we integrate both proximity and haptic sensing to improve time efficiency of robots operating in clutter? How do we improve the ability of humans to interact with these robots for search and rescue or in home assistance scenarios?

13 Multidisciplinary Design Optimization of Aircraft and Wind Turbines Andrew Ning Mechanical Engineering (801) Areas of Interest: Multidisciplinary Optimization; Aircraft Design; Wind Energy; Aerodynamics; Aeroelasticity; Uncertainty Quantification; Computational Methods

14 Aeronautics

15 Tailless Aircraft Design Optimization Uncertainty Quantification of Formation Flight Drag Savings

16 30 E 0 30 W 60 W 60 N 90 W Transonic Behavior of Formation Flight Formation Flight Route Optimization 30 N 120 W

17 Multifidelity Optimization Algorithm Development Online Parameter Estimation for Unmanned Aerial Vehicles y (m) x (m) relative alt. (m) u (m/s) time (s) time (s)

18 Wind Energy

19 New Solution Method to Blade Element Momentum Equations Different Objectives Used in Wind Turbine Optimization % change

20 High Tip speed Rotors Downwind Rotors

21 Offshore Foundation Design Wind Plant Layout Optimization

22 Alternate Reality Games for STEM Learning Areas of Interest: Derek Hansen Information Technology School of Technology (801) New Tools & Methods to Analyze Social Experience; Novel Designs of TMSP Interventions; Understanding and Designing Social Technologies for the Public Good

23 Alternate Reality Games for STEM Learning BYU Speed Networking Event Derek L. Hansen Associate Professor Information Technology, BYU

24 Alternate Reality Games Fictional narratives told using real world technologies with participation from players who work together to solve puzzles and contribute content.

25 Informal STEM Learning Deep time sciences ARG focused on teaching and using the process of scientific inquiry Historical ARG focused on computational thinking

26 Research on Permanent Digital Data Storage Barry Lunt Information Technology (801) Areas of Interest: Long term computer data storage; Teaching of computing and technology

27 Barry Lunt, Information Technology, School of Technology Matthew Linford, Chemistry Robert Davis, Physics Research on Permanent Digital Data Storage

28 Today s Storage Options: Flash Magnetic Tape Optical Discs Hard-Disk Drives

29 Today s Storage Options: Flash Magnetic Tape Optical Discs Hard-Disk Drives

30 Summary Storage Type Advertised LE Practical LE Magnetic Tape yrs 5 7 yrs Hard Disk Drive 5 7 yrs 1 3 yrs Flash Memory Not specified 8 10 yrs Recordable OD yrs 1 5 yrs Needed >1000 yrs >500 yrs

respectively Now developing solid-state (like flash)

31 Materials Approach There are materials which will last >1000 years M-Disc (DVD & now BD) tested to >1000, 500 yrs, respectively Now developing solid-state (like flash) permanent storage And permanent optical tape storage What are the implications?

32 7 years 6 journal papers 25 conference proceedings Some external funding Research Output

Radar and Wind Farms. Dr Laith Rashid Prof Anthony Brown. The University of Manchester

Radar and Wind Farms. Dr Laith Rashid Prof Anthony Brown. The University of Manchester Radar and Wind Farms Dr Laith Rashid Prof Anthony Brown The Microwave and Communication Systems Research Group School of Electrical and Electronic Engineering The University of Manchester Summary Introduction