Hi,
It is an interesting setup. Is the Quanergy LiDAR gives a point cloud similar to Velodyne? If so, in your recording topics, you could record 3D point clouds instead of 2d laser scan if you want to keep all data. You have both wheel odometry and zed odom, you would have to use only one or combine both with
robot_localization package. For your questions:
1. RECORDING DATA
a.Given an offline map creation, am I still subjected to any quality/performances trade-off? It is possible to store raw data at maximum quality/precision/input rate?
Yes, it is possible. You have the choice to record a rosbag, which would give you the most flexibility if you want to try other ROS approaches, or record data in RTAB-Map's database format directly using
data_recorder.launch. When recorded in RTAB-Map's database format, we can reprocess with different parameters using rtabmap standalone (use recorded database as input source) or rtabmap-reprocess tool (which can be reprocessed faster than real-time). With the rosbag, it is like replaying online the experiment. For this reason, it is maybe most useful to record the rosbag with everything at first, so that you can test different rtabmap input configurations afterwards.
Note about
data_recorder.launch: If you want to use it, I suggest to use
rtabmap_ros/rgbd_sync nodelet to pre-synchronized depth/rgb images together before feeding it to recorder node. Example:
<launch>
<node pkg="nodelet" type="nodelet" name="rgbd_sync" args="standalone rtabmap_ros/rgbd_sync">
<remap from="rgb/image" to="/zed/rgb/image_rect_color"/>
<remap from="depth/image" to="/zed/depth/depth_registered"/>
<remap from="rgb/camera_info" to="/zed/rgb/camera_info"/>
<param name="approx_sync" value="false"/>
</node>
<include file="$(find rtabmap_ros)/launch/data_recorder.launch">
<arg name="subscribe_odometry" value="true"/>
<arg name="subscribe_scan_cloud" value="true"/>
<arg name="subscribe_depth" value="false"/>
<arg name="subscribe_rgbd" value="true"/>
<arg name="rgbd_topic" value="/rgbd_image" />
<arg name="scan_cloud_topic" value="/quanergy_cloud"/>
<arg name="odom_topic" value="/zed_vio_odom"/> <!-- other choices: /wheel_odom or /odom_combined (robot_localization) -->
<arg name="frame_id" value="base_link"/>
<arg name="max_rate" value="1"/> <!-- 0 = Record as fast as possible -->
</include>
</launch>
Note that a compatible odometry covariance with RTAB-Map is very important. To use arbitrarily fixed values, you would have to set "odom_frame_id" to use TF instead.
data_recorder.launch lacks of arguments to set the covariance value, you would have to edit the file to add under data_recorder node something like:
<arg name="odom_tf_linear_variance" default="0.01"/>
<arg name="odom_tf_angular_variance" default="0.005"/>
b.My intended pipeline is : Record ROS BAG file at maximum quality [RTABMAP OFF]> Process the bag by means of rtabmap-dataRecorder [OFFLINE] > Process the resulting database by means of rtabmap standalone and configure parameters offline. Is that feasible?
As discussed in previous point, doing "Record ROS BAG file at maximum quality [RTABMAP OFF]" is a good way to start. After processing one time with rtabmap, you will get a database. This database can be used as input in standalone app to tune parameters offline and replay the database at different frame rate (like faster than real-time for convenience).
c.Is there any threshold (regarding input rate, quality etc) above which, a raw data quality improvement would results in an useless overkill?
It is more a hard drive space issue. Recording all raw data at maximum frame rate can give you very big rosbags. If odometry is already computed, RTAB-Map by default requires only 1 Hz data. The recording approach using
data_recorder.launch would give a lot smaller files if rate is limited to 1 Hz for example.
2.PROCESSING THE DATABASE OFFLINE
Given the pipeline feasibility, I'm wondering if I'll be able to fully tune rtabmap parameters offline so to get the best accuracy I'd like to obtain. (Given a good odometry performance).
Yes, we can change all parameters offline.
3.LOCALIZATION MODE
I've aware about the integration of movbase within the rtabmap framework. I am wondering if it is possible to run rtabmap in localization mode during navigation within the created map while having multiple localization sources (e.g. lidar based montecarlo localization - appearance based rtabmap localization).
I'm interested in evaluating the performances of the different localization approaches.
If you are creating a 3D map, it could be possible to make rtabmap just publishing the OctoMap for a lidar-based localization approach using the OctoMap while disabling appearance based rtabmap localization (Kp/MaxFeatures=-1). For example, the other localization approach would publish /map -> /odom. Make sure to set publish_tf to false for rtabmap so that /map -> /odom is not published by multiple nodes. To use another appearance-based localization approach, we would need more info about the format that is used. For example, it is possible to export a visual map in
bundler format (see this
post) and use
ACG_localizer.
cheers,
Mathieu
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