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Active Exploration and Mapping via Iterative Covariance Regulation over Continuous $SE(3)$ Trajectories

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 نشر من قبل Shumon Koga
 تاريخ النشر 2021
  مجال البحث الهندسة المعلوماتية
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This paper develops emph{iterative Covariance Regulation} (iCR), a novel method for active exploration and mapping for a mobile robot equipped with on-board sensors. The problem is posed as optimal control over the $SE(3)$ pose kinematics of the robot to minimize the differential entropy of the map conditioned the potential sensor observations. We introduce a differentiable field of view formulation, and derive iCR via the gradient descent method to iteratively update an open-loop control sequence in continuous space so that the covariance of the map estimate is minimized. We demonstrate autonomous exploration and uncertainty reduction in simulated occupancy grid environments.



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