M. Ani Hsieh, Ph.D.

Congratulations to ScaLAR member Ariella Mansfield and GRASPees Rebecca Li and Michael Sobrepera on winning Penn Health-Tech’s Rothberg Catalyzer

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Ariella Mansfield, Rebecca Li, and Michael Soprepera won the Penn Health-Tech’s Rothberg Catalyzer, a two-day makerthon that challenges interdisciplinary student teams to prototype and pitch medical devices that aim to address an unmet clinical need. The team took home the top prize of $10,000 for their project, an orthotic device that children with cerebral palsy can … Read more

Controlling stochastic switching

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Using control to shape stochastic escape and switching dynamics Dhanushka Kularatne, Eric Forgoston, and M. Ani Hsieh Abstract: We present a strategy to control the mean stochastic switching times of general dynamical systems with multiple equilibrium states subject to Gaussian white noise. The control can either enhance or abate the probability of escape from the … Read more

ScalAR Lab ACC2019 Presentation

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Don’t miss Cong Wei’s ACC 2019 presentation on “Low-Range Interaction Periodic Rendezvous Along Lagrangian Coherent Structures”. The presentation will be held on Friday, Jul 12, 2019 in the FrA03 Regular Session in Franklin 3. ACC 2019 will be held in Philadelphia, PA USA from Jul 10-12, 2019. For more information visit http://acc2019.a2c2.org/.

Come see the ScalAR Lab ICRA 2019 Presentations!

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Tahiya Salam will be presenting her RA-L paper entitled “Adaptive Sampling and Reduced Order Modeling of Dynamic Processes by Robot Teams” on Wednesday, May 22, from 11:30am-12:45pm in the WeBT1-03 Interactive Session in 220. Daniel Mox will be presenting his ICRA 2019 paper entitled “Evaluating the Effectiveness of Perspective Aware Planning with Panoramas” on Tuesday, … Read more

Collaborative Exploration by Human-Robot Teams

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This work focuses on developing collaborative exploration strategies that allow robots and humans to learn and co-adapt to exploit synergies within human-robot teams. Many existing collaborative strategies allocate tasks by leveraging each member’s strengths. By allowing robots to learn from their human teammates, humans can transfer some of their tasks to their robotic teammates enabling … Read more

Distributed Tracking of Spatio-temporal Processes with Multi-Robot Teams

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Being able to estimate and predict information about dynamic processes deepens our understanding of biological, chemical, and physical phenomena in the environment. Often, these dynamic processes exhibit complex, spatio-temporal behaviors. Mobile robots are particularly well-suited to monitor these processes because of their abilities to carry sensors and adapt their sensing locations. Robots can be used … Read more