Poor performance of base_local_planner - advice for parameter tuning?

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Hi All,

I am having some issues with object avoidance when using move_base. As you can see in this video I made the robot doesn't navigate the obstacles in a smooth manner. My suspicion is that my local_planner parameters need tuning. However I've spend hours playing with all the different parameters and am not seeing improved results. I have checked my odometry data and it's very accurate, so that's not the problem.

I'll attach my parameter configuration files below. I would really appreciate any tips, particularly from those who have success in tuning their robots to navigate smoothly around obstacles.

base_local_planner_params.yaml

controller_frequency: 2.0
recovery_behavior_enabled: false
clearing_rotation_allowed: false

TrajectoryPlannerROS:
   max_vel_x: 0.36
   min_vel_x: 0.2
   max_vel_y: 0.0  # zero for a differential drive robot
   min_vel_y: 0.0
   max_vel_theta: 0.7
   min_vel_theta: -0.7
   min_in_place_vel_theta: 0.5
   escape_vel: -0.15
   acc_lim_x: 0.3 # From test trials (0.304,0.285,0.26,0.365)
   acc_lim_y: 0.0 # zero for a differential drive robot
   acc_lim_theta: 1.0 #probably closer to 1.3 

   holonomic_robot: false
   yaw_goal_tolerance: 0.25 # about 12 degrees
   xy_goal_tolerance: 0.25  # 20 cm
   latch_xy_goal_tolerance: false
   pdist_scale: 0.6
   gdist_scale: 0.7
   meter_scoring: true

   heading_lookahead: 0.375

   heading_scoring: false
   heading_scoring_timestep: 0.8
   occdist_scale: 0.01
   oscillation_reset_dist: 0.05
   publish_cost_grid_pc: false
   prune_plan: true

   #sim_time: 4
   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: 4.0
raytrace_range: 5.0
inf_is_valid: false
robot_radius: 0.3 # - dont need a radius if we have a footprint.
inflation_radius: 0.3
# footprint: [[-15,0.26],[0.42,0.26],[0.42,-0.26],[-15,-0.26]] # Note Base_link is on top of the lidar and x axis is forwards


observation_sources: scan
scan:
  data_type: LaserScan
  topic: scan
  marking: true
  clearing: true    

map_type: costmap

global_costmap_params.yaml

global_costmap:
   global_frame: /map
   robot_base_frame: /base_footprint
   update_frequency: 1.0
   publish_frequency: 0.5
   static_map: true
   rolling_window: false
   resolution: 0.025
   transform_tolerance: 1.0
   map_type: costmap

local_costmap_params.yaml

local_costmap:
   global_frame: /odom
   robot_base_frame: /base_footprint
   update_frequency: 1
   publish_frequency: 2
   static_map: false
   rolling_window: true
   width: 5.0
   height: 5.0
   resolution: 0.025
   transform_tolerance: 1.0
   map_type: costmap

move_base_params.yaml

shutdown_costmaps: false

controller_frequency: 5.0 #before 5.0
controller_patience: 3.0


planner_frequency: 0.5
planner_patience: 5.0

oscillation_timeout: 10.0
oscillation_distance: 0.2

conservative_reset_dist: 0.10 #distance from an obstacle at which it will unstuck itself