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    Control of noisy differential-drive vehicles from time-bounded temporal logic specifications

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    Date Issued
    2013-01-01
    Publisher Version
    10.1109/ICRA.2013.6630847
    Author(s)
    Cizelj, Igor
    Belta, Calin
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    Permanent Link
    https://hdl.handle.net/2144/29967
    Citation (published version)
    Igor Cizelj, Calin Belta. 2013. "Control of Noisy Differential-Drive Vehicles from Time-Bounded Temporal Logic Specifications." 2013 IEEE International Conference on Robotics and Automation (ICRA), pp. 2021 - 2026 (6).
    Abstract
    We address the problem of controlling a noisy differential drive mobile robot such that the probability of satisfying a specification given as a Bounded Linear Temporal Logic (BLTL) formula over a set of properties at the regions in the environment is maximized. We assume that the vehicle can precisely determine its initial position in a known map of the environment. However, inspired by practical limitations, we assume that the vehicle is equipped with noisy actuators and, during its motion in the environment, it can only measure the angular velocity of its wheels using limited accuracy incremental encoders. Assuming the duration of the motion is finite, we map the measurements to a Markov Decision Process (MDP). We use recent results in Statistical Model Checking (SMC) to obtain an MDP control policy that maximizes the probability of satisfaction. We translate this policy to a vehicle feedback control strategy and show that the probability that the vehicle satisfies the specification in the environment is bounded from below by the probability of satisfying the specification on the MDP. We illustrate our method with simulations and experimental results.
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