global_planner

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

move_base 中的base_global_planner配置为
base_global_planner: global_planner/GlobalPlanner

先看下global_planner的接口定义(前面讲过所有的实际的都是该接口的实现)

global_planner

• navfn/NavfnROS 使用Dijkstra’s算法代价最小的规划
• global_planner/GlobalPlanner 提供更多选项支持不同配置
• carrot_planner/CarrotPlanner

-allow unknown(true)

• use dijkstra(true)
• use quadratic(true)
• use grid path(false)
• old navfn behavior(false)
  这些设置默认参数即可
• default_tolerance 当目标点为障碍时，规划可以有一定的允许误差
• lethal_cost
• neutral_cost
• cost_factor
  

摘自【ROS Navigation Tuning Guide】

local_planner

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: true

# Forward Simulation Parameters
  sim_time: 2.0       # 1.7
  vx_samples: 10       # 3
  vy_samples: 1
  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

move_base 中的base_local_planner配置为
base_local_planner: "dwa_local_planner/DWAPlannerROS"

DWAPlannerROS

同样该类实现了base_local_planner的接口，我们看下接口

base_local_planner

• 计算速度

• 是否到达目标点

• 下发全局路径

• 初始化
  参数说明

• max_vel_x min_vel_x max_vel_y min_vel_y速度限定值

• max_trans_vel min_trans_vel 平移速度限定值

• trans_stopped_vel未使用

• max_rot_vel min_rot_vel 旋转的速度限定值

• rot_stopped_vel未使用

• acc_lim_x acc_lim_theta acc_lim_y 加速度限定值

• yaw_goal_tolerance xy_goal_tolerance 到达目标点的允许误差

• latch_xy_goal_tolerance 如果为true 当机器人到达目标点后通过旋转调整姿态（方向）后，偏离了目标点，也认为完成。这个实际应用中还是比较酷的

• sim_time 模拟机器人以采样速度行走的时间，太小(<2)会导致行走不流畅，特别在遇到障碍或狭窄的空间，因为没有足够多时间获取路径；太大(>5)会导致以僵硬的轨迹行走使得机器人不太灵活。如果太多会容易导致偏离全局的路径，特别启动的时候会转较大的半径，如果想启动的时候基本原地旋转摆正机器人的方向和全局路径的方向一致，那么就把模拟的时间设置短点。如果太小的仿真时间也不好，容易导致频繁的路径规划消耗资源，甚至也会出现震荡的可能。
  

• vx_samples vy_samples vtheta_samples采样速度个数, 一般vtheta_samples大于vx_samples
vy_samples怎么不是0?查看源码即可得到答案， 最小为1,即使设置<=0也会重新置1
  

• path_distance_bias goal_distance_bias occdist_scale
  轨迹代价计算
  

  cost
  • path_dist 规划最后一个点距离全局路径的距离，即决定local_plan多接近global_plan
  • goal_distance 规格最后一个点距离local目标距离，决定机器人接近目标
  • occdist_scale 路径中避障代价

另外还有

• sim_granularity 轨迹上的点的密集程度

在45.在ROS中实现global planner（1）我们实现了一个global planner的例子