8,971 research outputs found
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
Advanced Fluorescence Microscopy Techniques-FRAP, FLIP, FLAP, FRET and FLIM
Fluorescence microscopy provides an efficient and unique approach to study fixed and living cells because of its versatility, specificity, and high sensitivity. Fluorescence microscopes can both detect the fluorescence emitted from labeled molecules in biological samples as images or photometric data from which intensities and emission spectra can be deduced. By exploiting the characteristics of fluorescence, various techniques have been developed that enable the visualization and analysis of complex dynamic events in cells, organelles, and sub-organelle components within the biological specimen. The techniques described here are fluorescence recovery after photobleaching (FRAP), the related fluorescence loss in photobleaching (FLIP), fluorescence localization after photobleaching (FLAP), Forster or fluorescence resonance energy transfer (FRET) and the different ways how to measure FRET, such as acceptor bleaching, sensitized emission, polarization anisotropy, and fluorescence lifetime imaging microscopy (FLIM). First, a brief introduction into the mechanisms underlying fluorescence as a physical phenomenon and fluorescence, confocal, and multiphoton microscopy is given. Subsequently, these advanced microscopy techniques are introduced in more detail, with a description of how these techniques are performed, what needs to be considered, and what practical advantages they can bring to cell biological research
Reflection-Aware Sound Source Localization
We present a novel, reflection-aware method for 3D sound localization in
indoor environments. Unlike prior approaches, which are mainly based on
continuous sound signals from a stationary source, our formulation is designed
to localize the position instantaneously from signals within a single frame. We
consider direct sound and indirect sound signals that reach the microphones
after reflecting off surfaces such as ceilings or walls. We then generate and
trace direct and reflected acoustic paths using inverse acoustic ray tracing
and utilize these paths with Monte Carlo localization to estimate a 3D sound
source position. We have implemented our method on a robot with a cube-shaped
microphone array and tested it against different settings with continuous and
intermittent sound signals with a stationary or a mobile source. Across
different settings, our approach can localize the sound with an average
distance error of 0.8m tested in a room of 7m by 7m area with 3m height,
including a mobile and non-line-of-sight sound source. We also reveal that the
modeling of indirect rays increases the localization accuracy by 40% compared
to only using direct acoustic rays.Comment: Submitted to ICRA 2018. The working video is available at
(https://youtu.be/TkQ36lMEC-M
Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment
This paper presents a novel algorithm that utilizes a 2D floorplan to align
panorama RGBD scans. While effective panorama RGBD alignment techniques exist,
such a system requires extremely dense RGBD image sampling. Our approach can
significantly reduce the number of necessary scans with the aid of a floorplan
image. We formulate a novel Markov Random Field inference problem as a scan
placement over the floorplan, as opposed to the conventional scan-to-scan
alignment. The technical contributions lie in multi-modal image correspondence
cues (between scans and schematic floorplan) as well as a novel coverage
potential avoiding an inherent stacking bias. The proposed approach has been
evaluated on five challenging large indoor spaces. To the best of our
knowledge, we present the first effective system that utilizes a 2D floorplan
image for building-scale 3D pointcloud alignment. The source code and the data
will be shared with the community to further enhance indoor mapping research
Mapping Complex Marine Environments with Autonomous Surface Craft
This paper presents a novel marine mapping system using an Autonomous
Surface Craft (ASC). The platform includes an extensive sensor suite for mapping
environments both above and below the water surface. A relatively small hull size
and shallow draft permits operation in cluttered and shallow environments. We address the Simultaneous Mapping and Localization (SLAM) problem for concurrent
mapping above and below the water in large scale marine environments. Our key
algorithmic contributions include: (1) methods to account for degradation of GPS
in close proximity to bridges or foliage canopies and (2) scalable systems for management of large volumes of sensor data to allow for consistent online mapping
under limited physical memory. Experimental results are presented to demonstrate
the approach for mapping selected structures along the Charles River in Boston.United States. Office of Naval Research (N00014-06-10043)United States. Office of Naval Research (N00014-05-10244)United States. Office of Naval Research (N00014-07-11102)Massachusetts Institute of Technology. Sea Grant College Program (grant 2007-R/RCM-20
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