Temporal Logic Robustness for General Signal Classes in Multi-Agent Systems
is coming at 01/28/2019 - 4:00pm

Weniger Hall 151
Mon, 01/28/2019 - 4:00pm

Houssam Abbas
Assistant Professor, Oregon State University

Abstract:
In multi-agent systems, robots transmit their planned trajectories to each
other or to a central controller, and each receiver plans its own actions by
maximizing a measure of mission satisfaction. For missions expressed in
temporal logic, the /robustness function/ plays the role of satisfaction
measure. It is not clear how the signal representation used to compress and
transmit the signal affects the robustness computation error at the receiver,
and the efficiency of computing it. An incorrect robustness value, or a
delayed computation result, can mean the difference between successful
control and a crash. Current practice uses simple Piece-Wise Linear
interpolation to reconstruct the transmitted signal, which has little
compressive ability. When communication capacity is at a premium, this is a
serious bottleneck.

In this talk, we study these questions on two case studies from quadrotor
flight and cardiac signal monitoring. We first show that the robustness
computation is significantly affected by how the continuous-time signal is
reconstructed from the received samples. We show that
monitoring spline-based reconstructions yields a smaller robustness error,
and that it can be done with the same time complexity as monitoring the
simpler piece-wise linear reconstructions. We provide a tight bound on the
robustness computation error, and leverage it to design a reconstruction
scheme with an even lower computation error than the spline-based schemes.
Thus classical signal processing techniques come to the rescue of fragile
controller synthesis.

Bio:

Read more:
http://eecs.oregonstate.edu/colloquium/temporal-logic-robustness-general... 
[1]


[1] 
http://eecs.oregonstate.edu/colloquium/temporal-logic-robustness-general-signal-classes-multi-agent-systems
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