move base velocity commands [closed]
Update: switching from amcl to gmapping has no effect of current goal. The global path is direct to the goal but the current path to the goal is over over the place. Also turning off DWA had no effect.
Update: Here is a video of the odd behavor , note that the global path is fine but the local path can not be determined.
http://www.flickr.com/photos/107473518@N08/10625510473/
Update: Here are my setting I use for costmap and amcl. Can anyone see somthing in the setting to prevent the local plan.
TrajectoryPlannerROS:
# for details see: <a href="http://www.ros.org/wiki/base_local_planner">http://www.ros.org/wiki/base_local_planner</a>
controller_frequency: 20
escape_vel: 0.1 # no backing up
max_vel_x: .2
max_trans_vel: .2
min_vel_x: 0.05
min_trans_vel: 0..05
max_rotational_vel: 0.1 # 0.1 rad/sec = 5.7 degree/sec
min_in_place_rotational_vel: 0.05
acc_lim_th: 0.05
acc_lim_x: 0.05
acc_lim_y: 0
holonomic_robot: false
# goal tolerance parameters
yaw_goal_tolerance: 0.5
xy_goal_tolerance: 0.5
latch_xy_goal_tolerance: true
# Forward Simulation Paramet
sim_time: 100.0 # The amount of time to forward-simulate trajectories in seconds
sim_granularity: 0.02 # The step size, in meters, to take between points on a given trajectory
angular_sim_granularity: 0.02 # The step size, in radians, to take between angular samples on a given trajectory.
vx_samples: 20 # The number of samples to use when exploring the x velocity space
vtheta_samples: 20 # The number of samples to use when exploring the theta velocity space
# Trajectory Scoring Parameters
meter_scoring: true # If true, distances are expressed in meters; otherwise grid cells
#path_distance_bias: 32.2 # The weighting for how much the controller should stay close to the path it was given
#goal_distance_bias: 22.4 # The weighting for how much the controller should attempt to reach its local goal, also controls speed
occdist_scale: 0.1 # The weighting for how much the controller should attempt to avoid obstacles
publish_cost_grid: true
prune_plan: false
common costmap.yaml
obstacle_range: 2.5
raytrace_range: 3.0
footprint: [[0.25, 0.1], [0.25, -0.1], [-0.25,-0.1], [-0.25, 0.1]]
max_scaling_factor: 0.02 # The scalling factor for footprint defined in local costmap
inflation_radius: 0.02 # Propagating cost values out from occupied cells that decrease with distance.
map_type: costmap
track_unknown_space: true
observation_sources: laser_scan_sensor
laser_scan_sensor: {sensor_frame: hokuyo_frame, data_type: LaserScan, topic: /scan, marking: true, clearing: true}
resolution: 0.005
global_costmap:
global_frame: /map
robot_base_frame: /base_link
update_frequency: 30.0
publish_frequency: 30.0
static_map: true
width: 20.0
height: 20.0
origin_x: -10.0
origin_y: -10.0
local_costmap:
global_frame: /odom
robot_base_frame: /base_link
update_frequency: 10.0
publish_frequency: 10.0
static_map: false
rolling_window: true
width: 16.0
height: 16.0
origin_x: -8.0
origin_y: -8.0
amcl:
# Publish scans from best pose at a max of 10 Hz -->
odom_model_type : "diff"
odom_alpha5 : "0.1"
gui_publish_rate : "30.0"
laser_max_beams : "60"
laser_max_range : "12.0"
min_particles : "500"
max_particles : "2000"
kld_err : "0.05"
kld_z : "0.99"
odom_alpha1 : "0.2"
odom_alpha2 : "0.2"
# translation std dev, m -->
odom_alpha3 : "0.2"
odom_alpha4 : "0.2"
laser_z_hit : "0.5"
laser_z_short : "0.05"
laser_z_max : "0.05"
laser_z_rand ...