<div dir="ltr">Looks very interesting! Thanks for supplying detailed documentation.<div><br></div><div>A major gap in the existing ROS localization solution (robot_pose_ekf) has been with respect to periodic absolute measurements, especially GPS fixes and data from mocap systems. Does robot_localization handle these cases at all, or provide for them to be handled with further development?</div>
<div><br></div><div>Thanks again for contributing this,</div><div><br></div><div>Mike</div><div class="gmail_extra"><br><br><div class="gmail_quote">On 22 April 2014 12:47, Tom Moore <span dir="ltr"><<a href="mailto:tmoore@cra.com" target="_blank">tmoore@cra.com</a>></span> wrote:<br>
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<p>All,<u></u><u></u></p>
<p><u></u> <u></u></p>
<p>I am pleased to announce the release of a new ROS package, robot_localization. The package estimates the state (3D pose and velocity) of a mobile robot through sensor fusion. Its features include:<u></u><u></u></p>
<p><u></u> <u></u></p>
<p>* Fusion of an arbitrary number of sensors: the nodes do not restrict the number of input sources. If, for example, your robot has multiple IMUs or multiple sources of odometry information, the nodes within robot_localization can support
all of them.<u></u><u></u></p>
<p>* Support for multiple ROS message types: all nodes in robot_localization can take in Odometry, Imu, PoseWithCovarianceStamped, or TwistWithCovarianceStamped messages.<u></u><u></u></p>
<p>* Per-sensor input customization: if a given sensor message contains data that you don't want to include in your state estimate, robot_localization's nodes allow you to exclude that data on a per-sensor basis.<u></u><u></u></p>
<p>* Continuous estimation: each node in robot_localization begins estimating the robot's state as soon as it receives a single measurement. If there is a holiday in the sensor data (i.e., a long period in which no data is received), the
filter will continue to estimate the robot's state via a 3D motion model.<u></u><u></u></p>
<p><u></u> <u></u></p>
<p>robot_localization currently contains only one node, ekf_localization, which, as the name implies, employs an extended Kalman filter. New nodes, such as an unscented Kalman filter node, will be added as they become available.<u></u><u></u></p>
<p><u></u> <u></u></p>
<p>robot_localization is currently available for ROS Groovy, Hydro, and Indigo. The package's wiki page at <a href="http://wiki.ros.org/robot_localization" target="_blank">http://wiki.ros.org/robot_localization</a> provides more details on how to integrate it with your robot<span>.
<u></u><u></u></span></p>
<p><u></u> <u></u></p>
<p>Development of this node was funded by Charles River Analytics, Inc.<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">-Tom<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">++++++++++++++++<u></u><u></u></p>
<p class="MsoNormal">Tom Moore<u></u><u></u></p>
<p class="MsoNormal">Software Engineer<u></u><u></u></p>
<p class="MsoNormal">Sensor Processing & Networking<u></u><u></u></p>
<p class="MsoNormal">Government Services<u></u><u></u></p>
<p class="MsoNormal">Charles River Analytics Inc.<u></u><u></u></p>
<p class="MsoNormal"><a href="tel:617.491.3474%20x521" value="+16174913474" target="_blank">617.491.3474 x521</a><u></u><u></u></p>
<p class="MsoNormal"><a href="http://www.cra.com" target="_blank">www.cra.com</a><u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
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