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The Bayes Tree: Enabling Incremental Reordering and Fluid Relinearization for Online Mapping
(Georgia Institute of Technology, 2010-01-29)
In this paper we present a novel data structure, the Bayes tree, which exploits
the connections between graphical model inference and sparse linear algebra.
The proposed data structure provides a new perspective on an ...
Rapid Loop Updates
(Georgia Institute of Technology, 2012-09-11)
Attentional Landmark Selection for Visual SLAM
(Georgia Institute of Technology, 2006-10)
In this paper, we introduce a new method to
automatically detect useful landmarks for visual SLAM. A
biologically motivated attention system detects regions of interest
which “pop-out” automatically due to strong contrasts ...
SLAM-Based Spatial Memory for Behavior-Based Robots
(Georgia Institute of Technology, 2015)
Knowledge is essential for an autonomous robot to act intelligently when tasked with a mission. With recent leaps of progress, the paradigm of SLAM (Simultaneous Localization and Mapping) has emerged as an ideal source of ...
Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping
(Georgia Institute of Technology, 2015-09)
Recent work on simultaneous trajectory estimation
and mapping (STEAM) for mobile robots has found success
by representing the trajectory as a Gaussian process. Gaussian
processes can represent a continuous-time trajectory, ...
Applying domain knowledge to slam using virtual measurements
(Georgia Institute of Technology, 2010-05)
Simultaneous Localization and Mapping (SLAM)
aims to estimate the maximum likelihood map and robot
pose based on a robot’s control and sensor measurements.
In structured environments, such as human environments, we
might ...
Self-Contained Autonomous Indoor Flight with Ranging Sensor Navigation
(Georgia Institute of Technology, 2012-11)
This paper describes the design and flight test of a completely
self-contained autonomous indoor Miniature Unmanned Aerial System (M-UAS). Guidance, navigation, and control algorithms are presented, enabling the
M-UAS ...
iSAM: Incremental Smoothing and Mapping
(Georgia Institute of Technology, 2008)
We present incremental smoothing and mapping
(iSAM), a novel approach to the simultaneous localization and
mapping problem that is based on fast incremental matrix
factorization. iSAM provides an efficient and exact ...
Information-based Reduced Landmark SLAM
(Georgia Institute of Technology, 2015-05)
In this paper, we present an information-based
approach to select a reduced number of landmarks and poses
for a robot to localize itself and simultaneously build an
accurate map. We develop an information theoretic ...
Tables, Counters, and Shelves: Semantic Mapping of Surfaces in 3D
(Georgia Institute of Technology, 2010-10)
Semantic mapping aims to create maps that include meaningful features, both to robots and humans. We present an extension to our feature based mapping technique that includes information about the locations of horizontal ...