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- W2216759066 abstract "We present an algorithm for generating open-loop trajectories that solve the problem of rearrangement planning under uncertainty. We frame this as a selection problem where the goal is to choose the most robust trajectory from a finite set of candidates. We generate each candidate using a kinodynamic state space planner and evaluate it using noisy rollouts. Our key insight is we can formalize the selection problem as the “best arm” variant of the multi-armed bandit problem. We use the successive rejects algorithm to efficiently allocate rollouts between candidate trajectories given a rollout budget. We show that the successive rejects algorithm identifies the best candidate using fewer rollouts than a baseline algorithm in simulation. We also show that selecting a good candidate increases the likelihood of successful execution on a real robot." @default.
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- W2216759066 date "2015-09-01" @default.
- W2216759066 modified "2023-10-01" @default.
- W2216759066 title "Robust trajectory selection for rearrangement planning as a multi-armed bandit problem" @default.
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- W2216759066 doi "https://doi.org/10.1109/iros.2015.7353743" @default.
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