MEAM Seminar Series Summer 2015
For Spring 2015 Seminars, click here.
Seminars are held on Tuesday mornings, with coffee at 10:30 am in the Towne Building and the seminar beginning at 10:45 am in Towne Building, room 337 (unless otherwise noted).
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John Martin, PhD Candidate, University of Pennsylvania
Advisor: Robert Mauck
"Nanofibrous Disc-like Angle Ply Structures (DAPS) for Total Disc Replacement in a Small Animal Model"
The intervertebral discs are cartilaginous structures that impart multidirectional flexibility to the spine in support of routine physiologic loading. The discs of the lumbar spine are the largest avascular tissues in the body and, as a consequence, these discs predictably degenerate with age. Chronic low back pain is directly linked to intervertebral disc degeneration and is a significant socioeconomic burden, encompassing a yearly cost upwards of $100-$200 billion in the US.
My global hypothesis for this work is that cell-seeded synthetic discs can restore normal mechanical function to the spine after end-stage disc degeneration. To that end, our lab has developed what we call nanofibrous disc-like angle ply structures (DAPS) that replicate the natural structure, composition, and cellularity of the native intervertebral disc. In this talk, I will describe the optimization of the in vitro culture and fabrication processes of DAPS, the development of a small animal model of total disc replacement, and the evaluation of DAPS maturation and mechanical function in vivo.
Philip Dames, PhD Candidate, University of Pennsylvania
Advisor: Vijay Kumar
2:30 pm, Levine 307
"Multi-Robot Active Information Gathering Using Random Finite Sets"
Information gathering tasks are becoming increasingly important in the modern world, ranging from infrastructure inspection to environmental monitoring to search and rescue. Teams of mobile sensor platforms have the ability to automate these information gathering tasks, which are often too dull, dirty, or dangerous for humans to perform. Additionally, robots are able to gather information that humans simply cannot gather, either by using mobility (e.g., flying overhead or crawling through rubble) or advanced sensors (e.g., multi-spectral cameras). In all of these tasks, the robot team must detect and localize an unknown number of objects of interest within the environment.
This talk will describe a unified estimation, control, and communication framework for active information gathering for multi-robot teams. There are many sources of uncertainty in these scenarios: in the number of objects of interest within the environment, in the locations of the objects of interest, in the sensor readings (e.g., false positive and false negative detections and noisy measurements), etc. We use the Probability Hypothesis Density (PHD) filter to simultaneously estimate the number of objects in the environment and their locations while taking into account these uncertainties. Using sets of potential actions generated at multiple length scales for each robot, the team selects the joint action that maximizes the expected information gain over a finite time horizon. We demonstrate the real-world applicability of the proposed autonomous exploration strategy through hardware experiments, exploring an office environment with a team of ground robots. We also conduct a series of simulated experiments, varying the planning method, target cardinality, environment, and sensor modality.