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UID:0-487@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20160504T163000

DTEND;TZID=Asia/Jerusalem:20160504T173000

DTSTAMP:20230603T191754Z

URL:https://aerospace.technion.ac.il/events/algorithmic-advances-in-planni
 ng-and-control-of-robotic-systems/

SUMMARY:Algorithmic Advances in Planning and Control of Robotic Systems
DESCRIPTION:Lecturer:Prof. Emilio Frazzoli\n Faculty:Department of Aeronaut
 ics and Astronautics & Laboratory for Information and Decision Systems\n I
 nstitute:Massachusetts Institute of Technology\n Location:Classroom 165\, 
 ground floor\, Library\, Aerospace Eng.\n Zoom: \n Abstract: \n Details: \
 n This talk addresses the problem of "anytime" control strategy synthesis 
 for dynamical systems\, proposing a general framework based on the increme
 ntal refinement of a finite "concretization" of the system. We focus on th
 e problem of designing a plan to fulfill a given task specification while 
 satisfying a set of safety rules\, and in particular to task specification
 s that become feasible only if a subset of the safety rules are violated. 
 The proposed algorithm then computes a control law\, that minimizes the le
 vel of unsafety for a trajectory that satisfies the given task specificati
 on. This problem is motivated by an autonomous car navigating an urban env
 ironment while following rules of the road such as “always travel in rig
 ht lane” and “do not change lanes frequently\,” or UAVs planning a m
 ission balancing mission objectives\, rules of engagements\, and environme
 ntal constraints.  Ideas behind sampling based motion-planning algorithms
 \, such as the Probabilistic Road Map (PRM) and Rapidly-exploring Random T
 ree (RRT)\, are employed to incrementally construct a finite concretizatio
 n of the dynamics as a durational Kripke structure. In conjunction with th
 is\, a finite automaton that captures the safety rules is used in order to
  find an optimal trajectory that minimizes the violation of safety rules. 
 It is shown that the proposed algorithm guarantees asymptotic optimality\,
  i.e.\, almost-sure convergence to optimal solutions. The algorithms are d
 emonstrated on an autonomous vehicle platform---showing perhaps for the fi
 rst time the applicability of formal methods to full-scale\, real-world ro
 botic systems.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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