配置导航参数
前文(ROS机器人底盘(13)-move_base(1))讲了move_base的简单的基础,本文将详细分析下如何配置move_base参数
最简单的配置
再次引用该图
movebase
map_server和
amcl都是不必须的，我们就首先配置一个没有map的
move_base
fake_move_base_with_out_map.launch
robot.launch为Pibot的驱动，其他底盘可替换为自己的驱动move_base_with_out_map.launch.xml
- 配置文件详情
1.costmap_common_params_apollo.yaml
max_obstacle_height: 0.60 # assume something like an arm is mounted on top of the robot
# Obstacle Cost Shaping (http://wiki.ros.org/costmap_2d/hydro/inflation)
#robot_radius: 0.16 # distance a circular robot should be clear of the obstacle (kobuki: 0.18)
footprint: [[0.10, -0.07], [0.10, 0.18], [-0.10, 0.18], [-0.10, -0.07]]
# footprint: [[x0, y0], [x1, y1], ... [xn, yn]] # if the robot is not circular
map_type: voxel
obstacle_layer:
enabled: true
max_obstacle_height: 0.6
origin_z: 0.0
z_resolution: 0.2
z_voxels: 2
unknown_threshold: 15
mark_threshold: 0
combination_method: 1
track_unknown_space: true #true needed for disabling global path planning through unknown space
obstacle_range: 2.5
raytrace_range: 3.0
origin_z: 0.0
z_resolution: 0.2
z_voxels: 2
publish_voxel_map: false
observation_sources: scan
scan:
data_type: LaserScan
topic: scan
inf_is_valid: true
marking: true
clearing: true
min_obstacle_height: 0.05
max_obstacle_height: 0.35
#bump:
#data_type: PointCloud2
#topic: mobile_base/sensors/bumper_pointcloud
#marking: true
#clearing: false
#min_obstacle_height: 0.0
#max_obstacle_height: 0.15
# for debugging only, let's you see the entire voxel grid
#cost_scaling_factor and inflation_radius were now moved to the inflation_layer ns
inflation_layer:
cost_scaling_factor: 2.5 # exponential rate at which the obstacle cost drops off (default: 10)
inflation_radius: 1.2 # max. distance from an obstacle at which costs are incurred for planning paths.
static_layer:
enabled: false
2.local_costmap_params_withoutmap.yaml
local_costmap:
global_frame: /odom
robot_base_frame: /base_link
update_frequency: 1.0
publish_frequency: 2.0
static_map: false
rolling_window: true
width: 4
height: 4
resolution: 0.05
transform_tolerance: 0.5
plugins:
- {name: obstacle_layer, type: "costmap_2d::VoxelLayer"}
- {name: inflation_layer, type: "costmap_2d::InflationLayer"}
3.global_costmap_params_withoutmap.yaml
global_costmap:
global_frame: /map
robot_base_frame: /base_link
update_frequency: 1.0
publish_frequency: 0.5
static_map: false
rolling_window: true
width: 12
height: 12
resolution: 0.05
transform_tolerance: 0.5
plugins:
- {name: obstacle_layer, type: "costmap_2d::VoxelLayer"}
- {name: inflation_layer, type: "costmap_2d::InflationLayer"}
4.dwa_local_planner_params_apollo.yaml
DWAPlannerROS:
# Robot Configuration Parameters - Kobuki
max_vel_x: 0.25
min_vel_x: 0.05
max_vel_y: 0
min_vel_y: 0
max_trans_vel: 0.35 # choose slightly less than the base's capability
min_trans_vel: 0.001 # this is the min trans velocity when there is negligible rotational velocity
trans_stopped_vel: 0.05
# Warning!
# do not set min_trans_vel to 0.0 otherwise dwa will always think translational velocities
# are non-negligible and small in place rotational velocities will be created.
max_rot_vel: 0.6 # choose slightly less than the base's capability
min_rot_vel: 0.4 # this is the min angular velocity when there is negligible translational velocity
rot_stopped_vel: 0.1
acc_lim_x: 1 # maximum is theoretically 2.0, but we
acc_lim_theta: 1.5
acc_lim_y: 0 # diff drive robot
# Goal Tolerance Parameters
yaw_goal_tolerance: 0.2
xy_goal_tolerance: 0.15
latch_xy_goal_tolerance: false
# Forward Simulation Parameters
sim_time: 2.0 # 1.7
vx_samples: 10 # 3
vy_samples: 1 # diff drive robot, there is only one sample
vtheta_samples: 20 # 20
# Trajectory Scoring Parameters
path_distance_bias: 32.0 # 32.0 - weighting for how much it should stick to the global path plan
goal_distance_bias: 24.0 # 24.0 - wighting for how much it should attempt to reach its goal
occdist_scale: 0.4 # 0.01 - weighting for how much the controller should avoid obstacles
forward_point_distance: 0.325 # 0.325 - how far along to place an additional scoring point
stop_time_buffer: 0.2 # 0.2 - amount of time a robot must stop in before colliding for a valid traj.
scaling_speed: 0.25 # 0.25 - absolute velocity at which to start scaling the robot's footprint
max_scaling_factor: 0.2 # 0.2 - how much to scale the robot's footprint when at speed.
# Oscillation Prevention Parameters
oscillation_reset_dist: 0.05 # 0.05 - how far to travel before resetting oscillation flags
# Debugging
publish_traj_pc : true
publish_cost_grid_pc: true
global_frame_id: odom
# Differential-drive robot configuration - necessary?
# holonomic_robot: false
5.move_base.yaml
# Move base node parameters. For full documentation of the parameters in this file, please see
#
# http://www.ros.org/wiki/move_base
#
shutdown_costmaps: false
controller_frequency: 5.0
controller_patience: 3.0
planner_frequency: 1.0
planner_patience: 5.0
oscillation_timeout: 10.0
oscillation_distance: 0.2
# local planner - default is trajectory rollout
base_local_planner: "dwa_local_planner/DWAPlannerROS"
base_global_planner: global_planner/GlobalPlanner #"navfn/NavfnROS" #alternatives: , carrot_planner/CarrotPlanner
6.global_planner_params.yaml
GlobalPlanner: # Also see: http://wiki.ros.org/global_planner
old_navfn_behavior: false # Exactly mirror behavior of navfn, use defaults for other boolean parameters, default false
use_quadratic: true # Use the quadratic approximation of the potential. Otherwise, use a simpler calculation, default true
use_dijkstra: true # Use dijkstra's algorithm. Otherwise, A*, default true
use_grid_path: false # Create a path that follows the grid boundaries. Otherwise, use a gradient descent method, default false
allow_unknown: true # Allow planner to plan through unknown space, default true
#Needs to have track_unknown_space: true in the obstacle / voxel layer (in costmap_commons_param) to work
planner_window_x: 0.0 # default 0.0
planner_window_y: 0.0 # default 0.0
default_tolerance: 0.5 # If goal in obstacle, plan to the closest point in radius default_tolerance, default 0.0
publish_scale: 100 # Scale by which the published potential gets multiplied, default 100
planner_costmap_publish_frequency: 0.0 # default 0.0
lethal_cost: 253 # default 253
neutral_cost: 66 # default 50
cost_factor: 0.55 # Factor to multiply each cost from costmap by, default 3.0
publish_potential: true # Publish Potential Costmap (this is not like the navfn pointcloud2 potential), default true
运行结果
运行roslaunch pibot_navigation fake_move_base_with_out_map.launch
roslaunch pibot_navigation view_nav_with_out_map.launch
选择2D Nav Goal导航可以看到
配置分析
可以看到move_base配置项较多，涉及到cost_map及planner,分别又包括local_cost_map、global_cost_map和local_planner、global_planner
首先看根配置(简单说就是没有前面的namespace的)，除了move_base.yaml,其他文件都是二级配置项
common_cost_map中在move_base_with_out_map.launch.xml都已经指定了namespace
move_base
根配置
-
shutdown_costmaps当move_base在不活动状态时，是不是要关掉move_base node的 costmap
查看源码可知move_base空闲时
shutdown_costmaps为true会关掉cost_map,激活是会重新开启
默认false
-
controller_frequency规划频率，太大会占用CPU 这里我们设置为3， 好点的处理器可以设置稍高 controller_patience
算了还是直接看源码吧
计算速度失败就判断有没有超时，超时就切换状态
planner_frequency
容易理解这个是全局路径规划的频率；如果为0即只规划一次
-
planner_patience容易理解，规划路径的最大容忍时间 -
oscillation_timeout&oscillation_distance
陷在方圆
oscillation_distance达oscillation_timeout之久，认定机器人在震荡，从而做异常处理（应该容易理解吧）
-
base_local_planner&base_global_planner
最为重要的2个参数，直接指定使用哪种局部规划和全局规划，
具体类分别继承与实现nav_core::BaseLocalPlanner和nav_core::BaseGlobalPlanner接口
rosrun rqt_reconfigure rqt_reconfigure查看move_base的参数
可以看到还有几个参数，一并看下
-
max_planning_retries最大规划路径的重试次数-1标识无限次 -
recovery_behavior_enabled是否启用恢复机制 -
clearing_rotation_allowed是否启用旋转的恢复，当然是在recovery_behavior_enabled为true的基础上的 -
recovery_behaviors一系列的恢复机制，同base_local_planner&base_global_planner具体类继承于nav_core::RecoveryBehavior -
conservative_reset_dist清除机制的参数， 决定清除多远外的障碍