Kress-Gazit, Hadas

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Now showing 1 - 4 of 4
  • Publication
    Hybrid Controllers for Path Planning: A Temporal Logic Approach
    (2005-01-01) Fainekos, Geogios E; Kress-Gazit, Hadas; Pappas, George J
    Robot motion planning algorithms have focused on low-level reachability goals taking into account robot kinematics, or on high level task planning while ignoring low-level dynamics. In this paper, we present an integrated approach to the design of closed–loop hybrid controllers that guarantee by construction that the resulting continuous robot trajectories satisfy sophisticated specifications expressed in the so–called Linear Temporal Logic. In addition, our framework ensures that the temporal logic specification is satisfied even in the presence of an adversary that may instantaneously reposition the robot within the environment a finite number of times. This is achieved by obtaining a Büchi automaton realization of the temporal logic specification, which supervises a finite family of continuous feedback controllers, ensuring consistency between the discrete plan and the continuous execution.
  • Publication
    Recycling controllers
    (2008-08-23) Kress-Gazit, Hadas; Ayanian, Nora; Pappas, George J; Kumar, Vijay
    The problem of designing control schemes for teams of robots to satisfy complex high-level tasks is a challenging problem which becomes more difficult when adding constraints on relative locations of robots. This paper presents a method for automatically creating hybrid controllers that ensure a team of heterogeneous robots satisfy some user specified high-level task while guaranteeing collision avoidance and predicting and reducing deadlock. The generated hybrid controller composes atomic controllers based on information the robots gather during runtime; thus these atomic controllers can be reused in different scenarios for multiple tasks. As a demonstration of this general approach we examine a task in which a group of robots sort different items to be recycled.
  • Publication
    Temporal Logic Motion Planning for Mobile Robots
    (2005-04-01) Fainekos, Geogios E; Kress-Gazit, Hadas; Pappas, George J
    In this paper, we consider the problem of robot motion planning in order to satisfy formulas expressible in temporal logics. Temporal logics naturally express traditional robot specifications such as reaching a goal or avoiding an obstacle, but also more sophisticated specifications such as sequencing, coverage, or temporal ordering of different tasks. In order to provide computational solutions to this problem, we first construct discrete abstractions of robot motion based on some environmental decomposition. We then generate discrete plans satisfying the temporal logic formula using powerful model checking tools, and finally translate the discrete plans to continuous trajectories using hybrid control. Critical to our approach is providing formal guarantees ensuring that if the discrete plan satisfies the temporal logic formula, then the continuous motion also satisfies the exact same formula.
  • Publication
    Automatically synthesizing a planning and control subsystem for the DARPA urban challenge
    (2008-08-23) Kress-Gazit, Hadas; Pappas, George J
    To incorporate robots into society, they must be able to perform complex tasks while interacting with the world around them in a safe and dependable manner. The recent DARPA 2007 Urban Challenge made a step towards that goal by testing how well robotic vehicles can interact in an urban environment while dealing with static and dynamic obstacles and other cars. This paper uses the Urban challenge to demonstrates a general approach for automatically synthesizing correct hybrid controllers from high level descriptions. Here we create a planning and control subsystem for the vehicle that, if the information gathered by the sensor is correct, satisfies the requirements of the challenge for different dynamic environments. This approach automatically produces a system that is guaranteed to behave according to the traffic laws while interacting with other vehicles. Furthermore, it allows systems to be changed rapidly and easily thus reducing design time and eliminating human error.