Abstract:Range sensors are currently present in countless applications related to perception of the environment. In mobile robots, these devices constitute a key part of the sensory apparatus and enable essential operations, that are often addressed by applying methods grounded on probabilistic frameworks such as Bayesian filters. Unfortunately, modern mobile robots have to navigate within challenging environments from the perspective of their sensory devices, getting abnormal observations (e.g., biased, missing, etc.)… Show more
“…Commonly used probabilistic models for robot localisation are the recursive Bayesian filters (Castellano-Quero et al, 2020). These filters can be used to approximate the state of the robot (which can be its position and orientation) through a process of prediction and correction.…”
Section: Perception Models For Robot Localisation During Autonomous D...mentioning
“…Commonly used probabilistic models for robot localisation are the recursive Bayesian filters (Castellano-Quero et al, 2020). These filters can be used to approximate the state of the robot (which can be its position and orientation) through a process of prediction and correction.…”
Section: Perception Models For Robot Localisation During Autonomous D...mentioning
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