The object_map Package

This package contains nodes to extract information from the LiDAR sensor and from ADAS Maps. The processed result is published as GridMaps (grid_map) and/or occupancy grids(nav_msgs).

Nodes in the Package

laserscan2costmap

This node uses 2D LaserScan messages to generate the OccupancyGrid.

Input topics

Default: /scan (sensor_msgs::LaserScan) from vscan.

Output topics

/ring_ogm (nav_msgs::OccupancyGrid) is the output OccupancyGrid with values ranging from 0-100.

How to launch

It can be launched as follows:

1. Using the Runtime Manager by clicking the laserscan2costmap checkbox under the Semantics section in the Computing tab.
2. From a sourced terminal by executing: roslaunch object_map laserscan2costmap.launch.

Parameters available in roslaunch and rosrun

• resolution defines the equivalent value of a cell in the grid in meters. Smaller values result in better accuracy at the expense of memory and computing cost (default value: 0.1).
• cell_width represents the width in meters of the OccupancyGrid around the origin of the PointCloud (default: 150).
• cell_height represents the height in meters of the OccupancyGrid around the origin of the PointCloud (default: 150).
• offset_x indicates if the center of the OccupancyGrid will be shifted by this distance, to the left(-) or right(+) (default: 25).
• offset_y indicates if the center of the OccupancyGrid will be shifted by this distance, to the back(-) or front(+) (default: 0).
• offset_z indicates if the center of the OccupancyGrid will be shifted by this distance, below(-) or above(+) (default: 0).
• scan_topic is the PointCloud topic source.

wayarea2grid

The ADAS Maps used in Autoware may contain the definition of the road areas, which is useful for computing whether a region is drivable or not. This node reads the data from an ADAS Map (VectorMap) and extracts the 3D positions of the road regions. It projects them into an OccupancyGrid and sets the value to 128 if the area is road and 255 if it is not. These values are used because this node uses 8-bit bitmaps (grid_map).

Input topics

/vector_map (vector_map_msgs::WayArea) from the VectorMap publisher. /tf to obtain the transform between the vector map(grid_frame) and the sensor(sensor_frame) .

Output topics

/grid_map_wayarea (grid_map::GridMap) is the resulting GridMap with values ranging from 0-255. /occupancy_wayarea (nav_msgs::OccupancyGrid) is the resulting OccupancyGrid with values ranging from 0-255.

How to launch

It can be launched as follows:

1. Using the Runtime Manager by clicking the wayarea2grid checkbox under the Semantics section in the Computing tab.
2. From a sourced terminal by executing: roslaunch object_map wayarea2grid.launch

Parameters available in roslaunch and rosrun

• sensor_frame defines the coordinate frame of the vehicle origin (default value: velodyne).
• grid_frame defines the coordinate frame of the map (default: map).
• grid_resolution defines the equivalent value of a cell in the grid in meters. Smaller values result in better accuracy at the expense of memory and computing cost (default: 0.2).
• grid_length_x represents the width in meters of the OccupancyGrid around the origin of the PointCloud (default: 25).
• grid_length_y represents the height in meters of the OccupancyGrid around the origin of the PointCloud (default: 0).
• grid_position_x indicates if the center of the OccupancyGrid will be shifted by this distance, left(-) or right(+) (default: 0).
• grid_position_y indicates if the center of the OccupancyGrid will be shifted by this distance, back(-) or front(+) (default: 0).

grid_map_filter

This node can combine sensor, map, and perception data as well as other OccupancyGrids. It generates OccupancyGrids with useful data for navigation purposes. It publishes three different layers. More details are provided in the output topics section below.

Input topics

/vector_map (vector_map_msgs::WayArea) from the VectorMap publisher. /tf to obtain the transform between the vector map (grid_frame) and the sensor (sensor_frame). /semantics/costmap_generator/occupancy_grid (nav_msgs::OccupancyGrid) calculated by costmap_generator package.

Output topics

/filtered_grid_map (grid_map::GridMap) which contains 3 layers and is also published as in regular OccupancyGrid messages. distance_transform (nav_msgs::OccupancyGrid) applies a distance transform to the OccupancyGrid obtained from the /realtime_cost_map, allowing us to obtain a gradient of probabilities surrounding the obstacles PointCloud. dist_wayarea (nav_msgs::OccupancyGrid) contains a combination of the distance transform and the road data, as described in the wayarea2grid node. circle (nav_msgs::OccupancyGrid) draws a circle surrounding the /realtime_cost_map.

The output topics are configured as described in the grid_map package, and the configuration file is inside the config folder of the package.

How to launch

It can be launched as follows:

1. Using the Runtime Manager by clicking the grid_map_filter checkbox under the Semantics section in the Computing tab.
2. From a sourced terminal by executing: roslaunch object_map grid_map_filter.launch.

Parameters available in roslaunch and rosrun

• map_frame defines the coordinate system of the realtime costmap (default value: map).
• map_topic defines the topic where the realtime costmap is being published (default: /realtime_cost_map).
• dist_transform_distance defines the maximum distance to calculate the distance transform, in meters (default: 2.0).
• use_wayarea indicates whether or not to use the road regions to filter the cost map (default: true).
• use_fill_circle enables or disables the generation of the circle layer (default: true).
• fill_circle_cost_threshold indicates the minimum cost value threshold value to decide if a circle will be drawn (default: 20)
• circle_radius defines the radius of the circle, in meters (default: 1.7).

Instruction Videos

grid_map_filter

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Changelog for package object_map

1.11.0 (2019-03-21)

• [Feature] costmap generator (#1774)
  • • Initial commit for visualization package

  • Removal of all visualization messages from perception nodes

  • Visualization dependency removal

  • Launch file modification

  • • Fixes to visualization

  • Error on Clustering CPU

  • Reduce verbosity on markers

  • Publish acceleration and velocity from ukf tracker

  • Remove hardcoded path

  • Updated README

  • updated prototype

  • Prototype update for header and usage

  • Removed unknown label from being reported

  • Updated publishing orientation to match develop

  • • Published all the trackers

  • Added valid field for visualization and future compatibility with ADAS ROI filtering

  • Add simple functions

  • • Reversed back UKF node to develop

  • Formatted speed

  • Refactor codes

  • Make tracking visualization work

  • Relay class info in tracker node

  • Remove dependency to jskbbox and rosmarker in ukf tracker

  • apply rosclang to ukf tracker

  • Refactor codes

  • Revert "apply rosclang to ukf tracker"

  • Revert "Remove dependency to jskbbox and rosmarker in ukf tracker"

  • Revert "Relay class info in tracker node"

  • delete dependency to jsk and remove pointcloud_frame

  • get direction nis

  • set velocity_reliable true in tracker node

  • Add divided function

  • add function

  • Sanity checks

  • Relay all the data from input DetectedObject

  • Divided function work both for immukf and sukf

  • Add comment

  • Refactor codes

  • Pass immukf test

  • make direction assisted tracking work

  • Visualization fixes

  • Refactor codes

  • Tracker Merging step added

  • Added launch file support for merging phase

  • lane assisted with sukf

  • • change only static objects

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