Searched for: subject%3A%22Uncertainty%22
(1 - 5 of 5)
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Peters, L. (author), Bajcsy, Andrea (author), Chiu, Chih Yuan (author), Fridovich-Keil, David (author), Laine, Forrest (author), Ferranti, L. (author), Alonso-Mora, J. (author)
Contingency planning, wherein an agent generates a set of possible plans conditioned on the outcome of an uncertain event, is an increasingly popular way for robots to act under uncertainty. In this work we take a game-theoretic perspective on contingency planning, tailored to multi-agent scenarios in which a robot's actions impact the...
journal article 2024
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Mészáros, A. (author), Franzese, G. (author), Kober, J. (author)
This work investigates how the intricate task of a continuous pick & place (P&P) motion may be learned from humans based on demonstrations and corrections. Due to the complexity of the task, these demonstrations are often slow and even slightly flawed, particularly at moments when multiple aspects (i.e., end-effector movement,...
journal article 2022
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Dutta, Shamak (author), Wilde, N. (author), Smith, Stephen L. (author)
We present a new mixed integer formulation for the discrete informative path planning problem in random fields. The objective is to compute a budget constrained path while collecting measurements whose linear estimate results in minimum error over a finite set of prediction locations. The problem is known to be NP-hard. However, we strive to...
conference paper 2022
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Roy, Spandan (author), Baldi, S. (author), Li, Peng (author), Narayanan, Viswa (author)
Artificial-delay control is a method in which state and input measurements collected at an immediate past time instant (i.e. artificially delayed) are used to compensate the uncertain dynamics affecting the system at the current time. This work formulates an artificial-delay control method with adaptive gains in the presence of nonlinear ...
journal article 2021
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de Groot, O.M. (author), Ferreira de Brito, B.F. (author), Ferranti, L. (author), Gavrila, D. (author), Alonso-Mora, J. (author)
We present an optimization-based method to plan the motion of an autonomous robot under the uncertainties associated with dynamic obstacles, such as humans. Our method bounds the marginal risk of collisions at each point in time by incorporating chance constraints into the planning problem. This problem is not suitable for online optimization...
journal article 2021
Searched for: subject%3A%22Uncertainty%22
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