movebase导航-白红宇

movebase导航

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发布时间：2019-06-21

本文共 4200 字，大约阅读时间需要 14 分钟。

利用turtlebot 的导航配置文件

由于movbase发的速度太不友好了所以使用了ros自带的滤波安装相应的包

apt-get install ros-indigo-yocs-velocity-smoother

我的配置文件 standalone.yaml

# Example configuration:# - velocity limits are around a 10% above the physical limits# - acceleration limits are just low enough to avoid jerking# Mandatory parametersspeed_lim_v: 0.8speed_lim_w: 5.4accel_lim_v: 0.3accel_lim_w: 3.5# Optional parametersfrequency: 20.0decel_factor: 1.0# Robot velocity feedback type:#  0 - none#  1 - odometry#  2 - end robot commandsrobot_feedback: 2

我机器人的启动文件

建图的启动文件：gmapping.launch


       
        //laser的topic名称，与自己的激光的topic相对应   
        //世界坐标  
      
          //启动slam的节点    
           
           
           
           
           
           
         //optimize机器人移动的初始值（距离）    
         //optimize机器人移动的初始值（角度）    
           //icp的迭代次数    
           
           
        //为0,表示所有的激光都处理，尽可能为零，如果计算压力过大，可以改成1    
           //以下四个参数是运动模型的噪声参数    
           
           
           
           //机器人移动linearUpdate距离，进行scanmatch    
          //机器人选装angularUpdate角度，进行scanmatch    
           
           
               //很重要，粒子个数
           
          //map初始化的大小

导航启动文件：tb_demo_amcl.launch

tb_move_base.launch

tb_amcl.launch

base_local_planner_params.yaml

controller_frequency: 3.0recovery_behavior_enabled: falseclearing_rotation_allowed: falseTrajectoryPlannerROS:   max_vel_x: 0.3   min_vel_x: 0.05   max_vel_y: 0.0  # zero for a differential drive robot   min_vel_y: 0.0   min_in_place_vel_theta: 0.5   escape_vel: -0.1   acc_lim_x: 2.5   acc_lim_y: 0.0 # zero for a differential drive robot   acc_lim_theta: 3.2   holonomic_robot: false   yaw_goal_tolerance: 0.1 # about 6 degrees   xy_goal_tolerance: 0.15  # 10 cm   latch_xy_goal_tolerance: false   pdist_scale: 0.8   gdist_scale: 0.6   meter_scoring: true   heading_lookahead: 0.325   heading_scoring: false   heading_scoring_timestep: 0.8   occdist_scale: 0.1   oscillation_reset_dist: 0.05   publish_cost_grid_pc: false   prune_plan: true   sim_time: 1.0   sim_granularity: 0.025   angular_sim_granularity: 0.025   vx_samples: 8   vy_samples: 0 # zero for a differential drive robot   vtheta_samples: 20   dwa: true   simple_attractor: false

costmap_common_params.yaml

obstacle_range: 2.5raytrace_range: 3.0robot_radius: 0.165inflation_radius: 0.3max_obstacle_height: 0.6min_obstacle_height: 0.0observation_sources: scanscan: {data_type: LaserScan, topic: /scan, marking: true, clearing: true, expected_update_rate: 0}

global_costmap_params.yaml

global_costmap:   global_frame: /map   robot_base_frame: /base_footprint   update_frequency: 1.0   publish_frequency: 0   static_map: true   rolling_window: false   resolution: 0.01   transform_tolerance: 1.0   map_type: costmap

local_costmap_params.yaml

local_costmap:   global_frame: /odom   robot_base_frame: /base_footprint   update_frequency: 5.0   publish_frequency: 1.0   static_map: false   rolling_window: true   width: 6.0   height: 6.0   resolution: 0.01   transform_tolerance: 1.0   map_type: costmap

把原先建好的图map.pgm map.yaml 放在功能包/maps/下

roslaunch odom_tf_package  start.launch 　　　　　　　　机器人启动文件roscat navigation_tutorials tb_demo_amcl.launch 　　　导航文件roslaunch navigation_tutorials rviz.launc            rviz启动文件