Hello,SteveMacenski.
When I run the move_base navigation with spatio_temporal_voxel_layer,there is a issue that is map update timeout.
common costmap configuration:
`footprint: [[-0.205, -0.155], [-0.205, 0.155], [0.077, 0.155], [0.077, -0.155]]
robot_radius: 0.17
footprint_padding: 0.0
map_type: costmap
always_send_full_costmap: true
inflation_layer:
enabled: false
cost_scaling_factor: 1.0 # exponential rate at which the obstacle cost drops off (default:10) astar2.0 0.8 hybrid astar 1.0 0.1
inflation_radius: 0.1 # max. distance from an obstacle at which costs are incurred for planning paths.
static_layer:
enabled: false
map_topic: "/map"
rgbd_obstacle_layer:
enabled: true
voxel_decay: 15 # seconds if linear, e^n if exponential
decay_model: 0 # 0=linear, 1=exponential, -1=persistent
voxel_size: 0.05 # meters
track_unknown_space: true # default space is known
max_obstacle_height: 2.0 # meters
unknown_threshold: 15 # voxel height
mark_threshold: 0 # voxel height
update_footprint_enabled: true
combination_method: 1 # 1=max, 0=override
obstacle_range: 3.0 # meters
origin_z: 0.0 # meters
publish_voxel_map: false # default off
transform_tolerance: 0.5 # seconds
mapping_mode: false # default off, saves map not for navigation
map_save_duration: 60 # default 60s, how often to autosave
observation_sources: rgbd1_mark rgbd1_clear
rgbd1_mark:
data_type: PointCloud2
topic: camera_back/depth/color/points
marking: true
clearing: false
min_obstacle_height: 0.3 # default 0, meters
max_obstacle_height: 2.0 # default 3, meters
expected_update_rate: 0.0 # default 0, if not updating at this rate at least, remove from buffer
observation_persistence: 0.0 # default 0, use all measurements taken during now-value, 0=latest
inf_is_valid: false # default false, for laser scans
voxel_filter: false # default off, apply voxel filter to sensor, recommend on
voxel_min_points: 0 # default 0, minimum points per voxel for voxel filter
clear_after_reading: true # default false, clear the buffer after the layer gets readings from it
rgbd1_clear:
data_type: PointCloud2
topic: camera_back/depth/color/points
marking: false
clearing: true
max_z: 7.0 # default 0, meters
min_z: 0.1 # default 10, meters
vertical_fov_angle: 0.8745 # default 0.7, radians
horizontal_fov_angle: 1.048 # default 1.04, radians
decay_acceleration: 5.0 # default 0, 1/s^2. If laser scanner MUST be 0
model_type: 0 # default 0, model type for frustum. 0=depth camera, 1=3d lidar like VLP16 or similar
global costmap configuration: global_costmap:
global_frame: odom
robot_base_frame: base_link
update_frequency: 1 #5
publish_frequency: 1 #5.001
static_map: true
The error that appears is
[ WARN] [1628254008.675817270, 126.849000000]: Map update loop missed its desired rate of 1.0000Hz... the loop actually took 1.9340 seconds [ WARN] [1628254008.678563403, 126.851000000]: Failed to transform the goal pose from map into the odom frame: Lookup would require extrapolation into the past. Requested time 45.142000000 but the earliest data is at time 116.950000000, when looking up transform from frame [map] to frame [odom]
When I use the obstacle layer which is default layer in navigation,everything is ok,the problem occurs when using the spatio_temporal_voxel_layer, i think my configuration of the spatio_temporal_voxel_layer is Incorrect,how should I solved it ?
Please ask on ros answers. Please stop filing superfluous tickets on projects asking for configuration help. My answer is going to continue to be the same. Config questions belong on ros answers
Hello,SteveMacenski. When I run the move_base navigation with spatio_temporal_voxel_layer,there is a issue that is map update timeout. common costmap configuration: `footprint: [[-0.205, -0.155], [-0.205, 0.155], [0.077, 0.155], [0.077, -0.155]]
robot_radius: 0.17
footprint_padding: 0.0
map_type: costmap
always_send_full_costmap: true
inflation_layer: enabled: false cost_scaling_factor: 1.0 # exponential rate at which the obstacle cost drops off (default:10) astar2.0 0.8 hybrid astar 1.0 0.1 inflation_radius: 0.1 # max. distance from an obstacle at which costs are incurred for planning paths.
static_layer: enabled: false map_topic: "/map"
rgbd_obstacle_layer: enabled: true voxel_decay: 15 # seconds if linear, e^n if exponential decay_model: 0 # 0=linear, 1=exponential, -1=persistent voxel_size: 0.05 # meters track_unknown_space: true # default space is known max_obstacle_height: 2.0 # meters unknown_threshold: 15 # voxel height mark_threshold: 0 # voxel height update_footprint_enabled: true combination_method: 1 # 1=max, 0=override obstacle_range: 3.0 # meters origin_z: 0.0 # meters publish_voxel_map: false # default off transform_tolerance: 0.5 # seconds mapping_mode: false # default off, saves map not for navigation map_save_duration: 60 # default 60s, how often to autosave observation_sources: rgbd1_mark rgbd1_clear rgbd1_mark: data_type: PointCloud2 topic: camera_back/depth/color/points marking: true clearing: false min_obstacle_height: 0.3 # default 0, meters max_obstacle_height: 2.0 # default 3, meters expected_update_rate: 0.0 # default 0, if not updating at this rate at least, remove from buffer observation_persistence: 0.0 # default 0, use all measurements taken during now-value, 0=latest inf_is_valid: false # default false, for laser scans voxel_filter: false # default off, apply voxel filter to sensor, recommend on voxel_min_points: 0 # default 0, minimum points per voxel for voxel filter clear_after_reading: true # default false, clear the buffer after the layer gets readings from it rgbd1_clear: data_type: PointCloud2 topic: camera_back/depth/color/points marking: false clearing: true max_z: 7.0 # default 0, meters min_z: 0.1 # default 10, meters vertical_fov_angle: 0.8745 # default 0.7, radians horizontal_fov_angle: 1.048 # default 1.04, radians decay_acceleration: 5.0 # default 0, 1/s^2. If laser scanner MUST be 0 model_type: 0 # default 0, model type for frustum. 0=depth camera, 1=3d lidar like VLP16 or similar
global costmap configuration:
global_costmap: global_frame: odom robot_base_frame: base_link update_frequency: 1 #5 publish_frequency: 1 #5.001 static_map: truetransform_tolerance: 0.5 plugins:
local costpmap configuration: `local_costmap: global_frame: odom robot_base_frame: base_link update_frequency: 1.0 #10.0 publish_frequency: 1.0 #10.001 static_map: false rolling_window: true width: 7 height: 7 resolution: 0.1 transform_tolerance: 0.5
plugins:
{name: inflation_layer, type: "costmap_2d::InflationLayer"}`
The error that appears is
[ WARN] [1628254008.675817270, 126.849000000]: Map update loop missed its desired rate of 1.0000Hz... the loop actually took 1.9340 seconds [ WARN] [1628254008.678563403, 126.851000000]: Failed to transform the goal pose from map into the odom frame: Lookup would require extrapolation into the past. Requested time 45.142000000 but the earliest data is at time 116.950000000, when looking up transform from frame [map] to frame [odom]
When I use theobstacle layer
which is default layer in navigation,everything is ok,the problem occurs when using the spatio_temporal_voxel_layer, i think my configuration of the spatio_temporal_voxel_layer is Incorrect,how should I solved it ?