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
接口很简单，总共只有三个还有个重载函数，看名字就知道，一个初始化，还有个是规划路径，可以的话你也可以实现这些接口完成你自己的global_planner，目前可以使用的有三种

• 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
接口也不算复杂，字面理解分别为：

• 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
  

  

• 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