ros-kinetic-ainstein-radar-drivers (3.0.1-1xenial) xenial; urgency=high



 -- Nick Rotella <nick.rotella@ainstein.ai>  Tue, 11 Feb 2020 06:00:00 -0000

ros-kinetic-ainstein-radar-drivers (3.0.0-1xenial) xenial; urgency=high

  * Merge branch 'master' of https://github.com/AinsteinAI/ainstein_radar
  * Minor, needed to negate speed for K79-3D using new SNR firmware
  * Add SNR to K79 and K79-3D output
    Added SNR output corresponding to the new fimrware which packs the SNR
    in the message in the expected place. SNR sppears to be from roughly
    140-200, with some targets at 0 (needs to be debugged).
  * Minor, update K79 specs to longer max range
  * Minor, add missing K79 specifications
  * Contributors: Nick Rotella

 -- Nick Rotella <nick.rotella@ainstein.ai>  Thu, 06 Feb 2020 06:00:00 -0000

ros-kinetic-ainstein-radar-drivers (2.0.2-1xenial) xenial; urgency=high

  * Minor, remove temporary file
  * Minor, fix SRD-D1 output data topic name
  * Contributors: Nick Rotella

 -- Nick Rotella <nick.rotella@ainstein.ai>  Tue, 19 Nov 2019 06:00:00 -0000

ros-kinetic-ainstein-radar-drivers (2.0.1-1xenial) xenial; urgency=high



 -- Nick Rotella <nick.rotella@ainstein.ai>  Tue, 12 Nov 2019 06:00:00 -0000

ros-kinetic-ainstein-radar-drivers (2.0.0-1xenial) xenial; urgency=high

  * Update RadarInfo msg, refactor for K79 and add T79
    Updated the RadarInfo message slightly. Also refactored the K79
    interface class to publish the RadarInfo message.
    Added publishing the RadarInfo message for T79 as well, needs testing.
  * Add latched publishing of RadarInfo msg for K79
    Added a latched publication of RadarInfo message for K79 in the K79
    interface class. This message is published once and stored for all
    future subscribers since the radar specifications never change (as of
    now).  The specifications used come from the preliminary datasheet
    and are likely to change. Any unknown specifications are left at zero.
  * Contributors: Nick Rotella

 -- Nick Rotella <nick.rotella@ainstein.ai>  Tue, 12 Nov 2019 06:00:00 -0000

ros-kinetic-ainstein-radar-drivers (1.1.0-1xenial) xenial; urgency=high

  * Minor fixes to package XML formatting
    Fixed the package XML file formatting and added missing content to
    conform to the suggested style guidelines.
  * Add simple T79 (ZOI) configuration GUI
    Added a simple Tk-based configuration GUI for the non-BSD T79 firmware
    (ZOI or Zone Of Interest firmware).  This GUI allows setting the
    "Nonvolatile Radar Parameters Command" which includes CAN ID, baudrate,
    and self start behavior.
  * Add K79-3D nodelet
    Added a nodelet for K79-3D to enable zero-copy message passing within
    the same nodelet manager.  Also added a launch file for testing this
    nodelet. Tested on hardware and working.
  * Add non-BSD T79 node for ZOI firmware/deprecate BSD
    Added a new interface and node for the new ZOI (Zone of Interest) T79
    firmware and deprecated the old T79 BSD interface and node by moving
    them as needed. Both tested and working, however nodelets are not yet
    available due to runtime issues involving the virtual base class.
    The new T79 node allows setting the zone of interest (min/max range,
    min/max azimuth angle) via ROS dynamic reconfigure GUI. The new node
    also supports up to 10 radars at once, specifying the CAN ID of each
    as a fixed node parameter. To set the CAN ID for a radar, currently
    this must be done outside ROS. A service call may implement this soon.
  * Bug fix in K79-3D interface, working in parking lot
    Fixed a few bugs in the parsing of K79-3D data packets which caused the
    data to be interpreted incorrectly resulting in nonphysical range and
    angles. Tested in the parking lot and seems to be working properly.
  * Contributors: Nick Rotella

 -- Nick Rotella <nick.rotella@ainstein.ai>  Tue, 29 Oct 2019 05:00:00 -0000

ros-kinetic-ainstein-radar-drivers (1.0.3-1xenial) xenial; urgency=high



 -- Nick Rotella <nick.rotella@ainstein.ai>  Thu, 03 Oct 2019 05:00:00 -0000

ros-kinetic-ainstein-radar-drivers (1.0.2-1xenial) xenial; urgency=high

  * Remove unused includes causing dependency issues
  * Contributors: Nick Rotella

 -- Nick Rotella <nick.rotella@ainstein.ai>  Wed, 25 Sep 2019 05:00:00 -0000

ros-kinetic-ainstein-radar-drivers (1.0.1-1xenial) xenial; urgency=high

  * Refactor filters into separate subpkg, fix bug
    Created subpackage ainstein_radar_filters for radar filters and
    conversions, moved all filters from ainstein_radar_drivers into this
    subpkg and tested build and launch on rosbag data.
    Also fixed a small bug in the radar data range filter in which the
    dynamic reconfigure callback was not being registered, preventing the
    filter from working. Now, the filter compiles and works properly.
  * Fix CMake issue and move nodelets to plugins folder
    Added missing dependency to range filter nodelet which was setting up a
    build race condition in which the dynamic reconfigure header sometimes
    was built after the nodelet, causing the build to fail.
    Also created a plugins folder and moved all nodelet XML files there,
    and updated the package.xml to match.
  * Build fix, add radardata range filter nodelet xml
    Added the radardata_range_filter nodelet XML file to the package XML
    which fixes a build issue involving missing config for this nodelet.
  * Refactor K79 interface to break out pure C++ driver
    Refactored the K79 radar interface to break out a pure C/C++ driver
    class called RadarDriverK79 on which RadarInterfaceK79 now depends.
    Tested and working with K79-2D, would need to do the same for K79-3D
    as well as all other radars which have ROS-dependent drivers.
    The next step would be to move the pure C++ driver outside this pkg
    entirely and create an external dependency, allowing use of radars
    without needing ROS installed.
  * Merge branch 'master' of https://github.com/AinsteinAI/ainstein_radar
  * Add range filter dynamic reconfigure, needs testing
  * Rename all instances of usharp3d to srd_d1
    Renamed all instances of usharp3d to srd_d1 to follow new product
    naming. srd_d1 python node should be tested and cleaned up and drop
    support for old firmware going forward.
  * Minor, change topic naming for radar outputs
  * Minor, fix timestamps on radar data
  * Minor, remove sign flip from filter, was a hack
  * Merge branch 'nick-addK79-3D'
  * Add K79-3D node and fix azimuth K79-2D parser issue
    Added the K79 3D and verified the data, though additional testing may
    need to be done. Added the interface (which is very similar to K79-2D
    and should be combined later), node and launch file.
    Fixed an issue with azimuth parsing which caused targets to appear
    behind the sensor. This was due to the azimuth angle being read as
    a 16bit signed int when in fact it is only a single byte (unsigned).
    This change was also implemented to K79-3D.
  * Small fix to K79 speed so that away is +ve
  * Add K79-3D interface class and test node
    Added a new K79-3D interface class and node (and later, nodelet to be
    added).  This is very similar to the K79(-2D) class and node.
  * Merge branch 'nick-fixK79Parsing'
  * Merge branch 'master' of https://github.com/AinsteinAI/ainstein_radar
  * Refactor tracking filter to use dynamic reconfigure
    Refactored the radar target tracking filter to use dynamically
    reconfigurable parameters both for high-level target tracking and
    low-level individual Kalman Filters (all of which share the same
    per-target KF parameters).
  * Add native PCL point type for radar data conversion
    Added a new PCL point type based on pcl::PointXYZ with additional
    fields specific to radar data. This allows for visualizing targets
    based on range, speed, snr etc in RViz by color as can normally be
    done for x,y,z coloring which is useful for debugging.
    More importantly, this exposes radar-specific data to all PCL library
    functionality, for instance making easy to use any of the basic PCL
    filters wrapped in pcl_ros (http://wiki.ros.org/pcl_ros#ROS_nodelets)
    without adding any new implementations (though this will require
    nodelets which will be added next).
    This opens the posibility to do much more advanced filtering on radar
    data going forward.
  * Fix parsing of K79 data using casts
    Added static_cast's to fix the parsing of K79 data from the char buffer
  * Update usharp3d testing launch, fix bug in driver
    Updated the usharp3d testing launch file after outdoor testing.
    Fixed a time bug in the usharp3d python driver by switching to
    Time(0) which gets the latest message regardless of stamped time.
  * Add support for new uSharp3D version
    New uSharp3D version firmware was modified to change the data format
    bsed on feedback given to Beijing. The python ROS node was modified
    to support old and new firmware using a ROS param to specify which.
  * Add device and frame ID params to uSharp3D node
    The uSharp3D node is still the rough python node (yet to be re-
    written in c++) but optional frame_id and device_id parameters were
    added for modularity.  The defaults are "map" and "/dev/ttyUSB0",
    respectively.
  * Modify and tune tracking filter, add test launch
    Modified the tracking filter to only use a measurement for one
    filter, rather than allowing multiple filters to use the same target.
    This was necessary because there were cases in which multiple filters
    would split off from one due to an inconsistent but valid target, and
    then these duplicates would be corrected by future, more accurate
    measurements and ALL remain in the list because they were all able to
    update with the same measurement.
    Tuned the tracking filter on single and two target data from outdoors
    testing of uSharp3D. This radar has particularly "jumpy" returns which
    require setting the confidence level and filter timeout lower to keep
    filters alive through measurement gaps. The process noise was decreased
    to keep the measurement covariance lower and prevent using bad targets.
    The measurement noise was increased to "smooth" jumps due to spotty
    targets, resulting in more of a low-pass tracking.
    Note: tuning was done by first filtering out distance targets using
    the range filter (>10m).
  * Add rosconsole configuration file for debugging
    Added a config/ folder containing a rosconsole configuration file
    which enables printing DEBUG-level messages.  To enable this from
    a launch file, load the rosconsole config into the environment with:
    <env name="ROSCONSOLE_CONFIG_FILE" value="$(find ainstein_radar_drivers)/config/debug_rosconsole.conf"/>
  * Add range filter for RadarTargetArray
    Added a range filter to remove targets from a RadarTargetArray which
    are outside specified parameter bounds for min/max range.  Added a node
    and nodelet based on this filter, with the intention being that other
    filters (for example, speed filter, angle filter, etc) can be run as
    nodelets and stacked for easy preprocessing of raw detections.
  * Rename defines, add val gate thresh param
    Renamed the noise-related KF parameter defines to STDEV to make it
    clear that these are standard deviations, not variances (they get
    squared in the noise matrices).
    Rescoped filter parameters to a /filter namespace and added a
    validation gate threshold to the filter which is set by the user based
    on desired confidence level from a Chi Squared distribution with 4
    DoFs (measurement dimension).  These can be looked up in a table for
    now, eg the table "Lower-tail critical values of chi-square distribution
    with ν degrees of freedom " on the page:
    https://www.itl.nist.gov/div898/handbook/eda/section3/eda3674.htm
    Also changed publisher to publish tracked targets even if list is
    empty (otherwise Rviz plugin always displays last message which makes
    debugging the filter difficult).  Maybe change this back later.
  * Move initial covariance from state to constructor
    Moved the initialization of the covariance for a filter from the
    state's constructor to being passed in from the filter. This is a
    step towards reading in KF parameters from rosparam.
  * Add launch file for testing tracking with uSharp3D
  * Add node for tracking targets based on raw detections
    Added a class which maintains a list of Kalman Filters instantiated
    from raw targets (detections).  The class adds a new filter for each
    detection and integrates the radar data to provide tracked targets at
    a fixed update rate, unlike raw detections which are can be sparse in
    time. Each time a RadarTargetArray is received, a callback passes the
    raw detection information to all tracked target filters for updating.
    Those detections which are unused by all filters cause a new filter to
    be spawned, while filters which have not been updated recently are
    pruned.
    Currently, only tested indoors. A number of low-level KF parameters
    are also fixed as constants, but should be exposed to the used for
    setting as ROS parameters. The node is functional but the interface
    will be improved.
  * Add Kalman Filter for tracked radar detections
    Added simple Kalman Filter and nested filter state classed for
    implementing tracked target filtering from raw radar returns, similar
    to the filtering performed on some Ainstein radars in firmware. This
    class will be used by a node which maintains a vector of filters for
    tracked target candidates, matches new detections to tracked targets
    and publishes stable detections.
  * Move nearest target filter into namespace
    Moved the nearest target filter class into the ainstein_radar namespace
    following convention, and updated the node.
  * Move nearest target filter into namespace
    Moved the nearest target filter class into the ainstein_radar namespace
    following convention, and updated the node.
  * Minor change to publisher in usharp3d node
    Changed the publisher for the usharp3d python node to only publish
    when there are valid targets (prevent spamming empty messages).
  * Fix radar stamped msg, add nearest target filter
    Fixed the RadarTargetStamped message to use the unstamped RadarTarget
    message rather than duplicating fields.
    Added a nearest target filter which extracts the nearest target (by
    range) within set min/max range bounds and optionally low-pass filters
    it before publishing as both a RadarTargetStamped and as an array with
    one message (called "tracked").  Will remove the array published after
    implementing a proper tracked target filter.
  * Add initial uSharp3D python node and launch file
    Added the uSharp3D python node based on Zhenyu's script, to be replaced
    with a C++ node taking parameters, remappings etc as needed.
    Also added a launch file for testing the radar - for now, it's very
    simple since there are no configurable parameters.
  * Refactor ainstein_radar_drivers using new message definitions
    The ainstein_radar_drivers subpkg now builds using the new radar msg
    definitions, however ainstein_rviz_plugins does not build.
  * Migrate old radar_ros_interface pkg to new ainstein_radar_drivers subpkg
  * Contributors: Nick Rotella

 -- Nick Rotella <nick.rotella@ainstein.ai>  Tue, 24 Sep 2019 05:00:00 -0000


