2018
DOI: 10.1142/s1793351x18400068
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Sequential Action Selection and Active Sensing for Budgeted Localization in Robot Navigation

Abstract: Recent years have seen a fast growth in the number of applications of Machine Learning algorithms from Computer Science to Robotics. Nevertheless, while most such attempts were successful in maximizing robot performance after a long learning phase, to our knowledge none of them explicitly takes into account the budget in the algorithm evaluation: e.g. budget limitation on the learning duration or on the maximum number of possible actions by the robot. In this paper, we introduce an algorithm for robot spatial … Show more

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Cited by 2 publications
(1 citation statement)
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“…When faced with the design of motion strategies for autonomous robotic systems, these sensors prove to be very convenient, and even fundamental [5,6]. When environments are dynamic (a typical problem for service robots) it is necessary for the robot to be able to identify nearby obstacles in real time [7,8].…”
Section: Introductionmentioning
confidence: 99%
“…When faced with the design of motion strategies for autonomous robotic systems, these sensors prove to be very convenient, and even fundamental [5,6]. When environments are dynamic (a typical problem for service robots) it is necessary for the robot to be able to identify nearby obstacles in real time [7,8].…”
Section: Introductionmentioning
confidence: 99%