SE PhD Final Oral Defense of Alphan Ulusoy

Starts:
1:00 pm on Wednesday, December 18, 2013
Ends:
3:00 pm on Wednesday, December 18, 2013
Location:
15 Saint Mary's Street, Rm 105
TITLE: Optimal Temporal Logic Control of
Autonomous Vehicles

ABSTRACT: Temporal logics, such as Linear Temporal Logic (LTL) and Computation Tree Logic (CTL), are
extensions of propositional logic that can capture temporal relations. Even though temporal logics have been
used in model checking of finite systems for quite some time, they have gained popularity as a means for
specifying complex mission requirements in path planning and control synthesis problems only recently. This
dissertation proposes and evaluates methods and algorithms for optimal path planning and control synthesis for
autonomous vehicles where a high-level mission specification expressed in LTL (or a fragment of LTL) must be
satisfied. In summary, after obtaining a discrete representation of the overall system, ideas and tools from formal
verification and graph theory are leveraged to synthesize provably correct and optimal control strategies.
The first part of this dissertation focuses on automatic planning of optimal paths for a group of robots that
must satisfy a common high level mission specification. The effect of slight deviations in traveling times on the
behavior of the team is analyzed and methods that are robust to bounded non-determinism in traveling times
are proposed. The second part focuses on the case where a controllable agent is required to satisfy a high-level
mission specification in the presence of other probabilistic agents that cannot be controlled. Efficient methods
to synthesize control policies that maximize the probability of satisfaction of the mission specification are
presented. The focus of the third part is the problem where an autonomous vehicle is required to satisfy a rich
mission specification over service requests occurring at the regions of a partitioned environment. A receding
horizon control strategy that makes use of the local information provided by the sensors on the vehicle in
addition to the a priori information about the environment is presented. For all of the automatic planning and
control synthesis problems that are considered, the proposed algorithms are implemented, evaluated, and
validated through experiments and/or simulations.

COMMITTEE: Advisor: Calin Belta, SE/ME; Christos G. Cassandras, SE/ECE; Ioannis Ch. Paschalidis, SE/ECE; Sean B. Andersson, SE/ME; Chair: John Baillieul, SE/ME