Hi,
Which version do you want to try? Lidar SLAM or RGB-D SLAM or Stereo SLAM? If I take the
launch_lidar example, with
Long-Range Lidar S2M configuration (and RGB-D for loop closure detection) of Table 8 of this paper "
RTAB-Map as an Open-Source Lidar and Visual SLAM Library for Large-Scale and Long-Term Online Operation":
$ roslaunch rtabmap_ros rtabmap.launch \
args:="-d \
--Reg/Force3DoF true \
--Reg/Strategy 1 \
--RGBD/ProximityPathMaxNeighbors 10 \
--Mem/STMSize 30 \
--Mem/LaserScanVoxelSize 0.05 \
--Mem/LaserScanNormalK 5 \
--Mem/LaserScanNormalRadius 1 \
--Icp/Epsilon 0.001 \
--Icp/MaxTranslation 0.5 \
--Icp/PM true \
--Grid/RangeMax 0" \
odom_args:="\
--Icp/VoxelSize 0.05 \
--Icp/PointToPlaneRadius 1" \
rgbd_sync:=true \
subscribe_scan:=true \
frame_id:=base_footprint \
ground_truth_frame_id:=world \
ground_truth_base_frame_id:=scan_gt \
use_sim_time:=true \
odom_guess_frame_id:=odom_combined \
odom_guess_min_translation:=0.1 \
odom_guess_min_rotation:=0.1 \
odom_topic:=odom \
icp_odometry:=true \
visual_odometry:=false \
scan_topic:=/base_scan_t \
rgb_topic:=/camera/rgb/image_raw \
depth_topic:=/camera/depth/image_raw \
camera_info_topic:=/camera/rgb/camera_info
$ ./republish_scan.py _offset:=82.2
$ ./gt_tf_broadcaster.py _file:=./stata-mit/2012-01-25-12-14-25_part1_floor2.gt.laser.poses _frame_id:=scan_gt _fixed_frame_id:=world _offset_time:=82.2 _offset_x:=-0.275
$ rosbag play --clock --pause ./stata-mit/2012-01-25-12-14-25.bag
Note that rtabmap should be built with
libpointmatcher to get similar results than in the paper. I don't have the bag to test this right now, let me know if you have problems running it.
cheers,
Mathieu