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Interface computing and the physical world into integrated Cyber-Physical Systems.
Prof. Rahul Mangharam's mission is to interface computing and the physical world into integrated Cyber-Physical Systems. Such systems will enable us to seamlessly communicate and control objects such as smart buildings, the human body and automobiles in the physical world. His research spans tiny wireless sensor networks to large-scale vehicle-to-vehicle wireless networks.
Metactronics: Metamaterial-Inspired Nanoelectronics, Circuits with Light at Nanoscale
We have developed the concept of new forms of optical circuitry in which a tapestry of subwavelength nanometer-scale metamaterial structures and nanoparticles may provide a mechanism for tailoring, patterning, and manipulating local optical electric fields and electric displacement vectors in a subwavelength domain, leading to possibility of optical information processing at the nanometer scale.
New robot-oriented undergraduate classes announced
The six-legged mobile robot, EduBot, will be used as the working platform for the new ESE classes: ESE 313 and ESE 112 are the new robot-oriented undergraduate classes.
Little Ben making history
On a historic day in November, 2007, not only for robotics but also for Penn Engineering. Little Ben has completed a total of 19 complex driving missions in 6 hours while obeying all California driving laws. Congratulations to Dan Lee and all members of the Little Ben team for this historic achievement! They have all made us all so proud.
News & Events
ESE Seminar Series: Spring 2008
"Correlating Wireless Mesh Routing Metrics to Capacity"
Marianna Carrera (Thomson Research)
Tuesday, August 26, 2008
11:00am - 12:00pm
307 Levine
Abstract:
In wireless mesh routing, a common approach is to use a periodic estimation of the link quality to identify high throughput paths. ETX and ETT are two typical metrics used to evaluate the quality of a wireless link. We measured these metrics and the corresponding link capacity in a wireless mesh testbed, and studied the correlation between each of these two metrics and the link capacity using a methodology based on linear regression. Measurements performed on many links established the existence of some correlation between those metrics and link capacity. However, they also showed (a) significant variations in the link metrics values while the link capacity remained stable, and (b) the inability of these metrics to accurately track link capacity variations over time. In order to understand the origin of these limitations, we modified the driver of wireless cards to store and provide detailed MAC layer information about the transmission of unicast probe packets, including the actual number of retransmissions and the actual transmission rates used. Moreover, using these information we define a new unicast metric and we compare its correlation with the link capacity to what is achieved with ETX and ETT. We show experimentally that the proposed unicast metric is more effective at tracking link capacity.
Prof. Nader Engheta
was selected as the 2008 recipient of the George H. Heilmeier Faculty Award for Excellence in Research. This prestigious award recognizes Prof. Engheta's extraordinary research career and his leadership in technical innovation and public service.
Click here to view The Almanac article.
Robotic Dance Recital
On Thursday, November 28, 2007, students of ESE 112 (Introduction to ESE) under the direction of Joel Weingarten, presented a Robotic Dance Recital. The recital, held in the Wu & Chen Auditorium in the Levine Building, showcased biologically inspired hexapedal robots performing fully autonomous dance. The students used their newly-acquired programming skills to choreograph dances set to contemporary music for the robots. To read details as presented in The Daily Pennsylvania click here. Continuing administrations of this course are presently taught by Diana Palsetia
Little Ben
Penn's Autonomous Car "Little Ben" Advances to the Finals of the DARPA Urban Chalenge -- Under the team leadership of Professor Daniel D. Lee, "Little Ben", the autonomous vehicle engineered by the University of Pennsylvania and Lehigh University faculty and students to drive itself, has advanced to the finals of the 2007 DARPA Urban Challenge. The finals will be broadcast live on Saturday, November 3, 2007 at 11 a.m. EST at www.grandchallenge.org. For further information on "Little Ben", visit http://www.upenn.edu/pennnews
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Student Work
Senior Design Projects 2007-2008
Polarizing Processing for Low Light Imaging
1st Prize (Demo Day), Berger Award, 3rd Prize from SEAS Competition
Authors:
Anujit Shastri Darren Wang
Advisor:
Van der Spiegel; Gruev; Yang
An important property of still picture cameras and video cameras is their ability to present an image that clearly depicts different objects. Normal cameras have the ability to discern between items in bright settings. When ambient light is very dim, pictures can be taken with a flash to illuminate the environment. However, there are many scenarios where there is little light and the use of a flash is either prohibited or can compromise a position. Additionally, video cameras do not even have the option, as a flash cannot be triggered for every frame. In these situations, normal cameras lack the necessary technology to distinguish one object from another ...
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Senior Design Projects 2007-2008
Personal Memory Assistant
2nd Prize (Demo Day), Honorable Mention from SEAS Competition
Authors:
Scott Kyle, Erika Sanchez, Meredith Skolnick
Advisor:
Laker
Facial recognition and speaker verification systems have been widely used in the security field. In this area the systems have to be very accurate to prevent unauthorized users from accessing classified information. The extensive list of possible uses of these technologies in the commercial world has not been taken advantage of yet. It is often difficult to remember the name of a person who is encountered out of context or infrequently. This situation can prove to be very embarrassing for the forgetful person. It can also be insulting to the person who is not remembered. The Personal Memory Assistant uses facial recognition and speaker identification to help avoid this situation ...
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Senior Design Projects 2007-2008
Automated Electric Guitar Tuner
3rd Prize (Demo Day), Honorable Mention from SEAS Competition
Authors:
Richard Prusak, Mike Kaplan, Abraham Dauhajre
Advisor:
Deliwala
In the music industry, there has been a recent trend of increased research and manufacturing with regard to self-tuning guitars. Although musicians can use devices such as chromatic tuners, which determine and display a string’s pitch using the guitar’s electrical output, these devices require the musician to manually tune the instrument. It was not until the release of Gibson’s Robot Guitar in late 2007 that a musician could own an automated tuning system for their electric guitar. However, it is currently only made in the style of Gibson Les Paul and SG guitars, leaving musicians with limited options if they wish to own a guitar where automated tuning is possible. The focus of this project was to find a way to create an automated tuning system that was accurate, affordable and external. In addition, there was an intricate balance between those parameters and the amount of work required on the part of the user ...
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Senior Design Projects 2007-2008
EduBot, Accelerometer Suite
Frederick Ketterer Award
Authors:
Hal Paver, Elisa Downey-Zayas
Advisor:
Komsuoglu
Researchers in legged robotic applications increasingly desire real time body pose knowledge about the robots they program. Body pose knowledge enables more efficient and extensive repertoires of behavior. A variety of methods have been developed for rigid body pose estimation, yet none are suited to legged machines such as the educational robot called Edubot. The implemented approach is a method of extracting body pose information from either single, or multiple, acceleration readings. One accelerometer located on the Edubot, capable of measuring acceleration in 3 degrees of freedom (DOF), enables static body pose estimation. Static body pose is estimated using the gravitational force of 1g towards the earth to determine how the relative forces on the X, Y, and Z axes of the accelerometer's Cartesian coordinate system relate to body pose. These estimates are based on the assumption that the static body position is independent of the velocity and thus only requires one set of readings . Dynamic body pose estimation is an extension of this concept; it takes into account the additional accelerations due to propulsion of the Edubot. In order to perform dynamic body pose estimation and fully describe the current acceleration of the entire body, the acceleration vectors of three or more distinct points are required ...
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Winners Senior Design Projects for 2006-07
1st Prize: Motion Tracking Camera
Wildland Firefighter Tracking System
Kate McArdle, Jareau Wade & Netta Doron (CSE)
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