Iterations version

ROSNavBench/marker_publisher.py

@@ -59,7 +59,7 @@ def main(args=None):
     marker.pose.orientation.z = 0.0
     marker.pose.orientation.w = 1.0
     if os.environ["controller"]!= None:
-       marker.text=os.environ["controller"]+"\n"+os.environ["planner"]
+       marker.text=os.environ["controller"]+"\n"+os.environ["planner"]+" "+os.environ["round_num"]
     else:
        marker.text='None'
     for i in range(4):

ROSNavBench/performace_analysis.py

@@ -15,9 +15,21 @@
 # success rate will be provided on seperate analysis   
 
 #Data will be recived as a table of data [[name of critera as in table],[1m,1,1,1,]]
+analysis_data=[[['Controller\ntype', 'Success\n rate\n (%)', 'Average \nexecution\ntime (sec)', 'CPU(%)', '', 'Memory usage(%)', 'Memory usage (%)', 'Average\nnumber of\nrecoveries', 'Average\n path\nlength(m)', 'Min\nproximity to\n obstacles(m)'], 
+  ['', '', '', 'Average', 'Max', 'Average', 'Max', '', '', ''], 
+  ['RPP', '100.0', '17.53', '21.21', '25.2', '10.56', '10.6', '0.00', '3.13', '0.58'], 
+  ['DWB', '100.0', '17.87', '20.36', '24.9', '10.60', '10.6', '0.00', '3.15', '0.58']], 
+  [['Controller\ntype', 'Success\n rate\n (%)', 'Average \nexecution\ntime (sec)', 'CPU(%)', '', 'Memory usage(%)', 'Memory usage (%)', 'Average\nnumber of\nrecoveries', 'Average\n path\nlength(m)', 'Min\nproximity to\n obstacles(m)'],
+    ['', '', '', 'Average', 'Max', 'Average', 'Max', '', '', ''], 
+    ['RPP', '100.0', '16.82', '18.93', '22.9', '10.60', '10.6', '0.00', '3.08', '0.53'], 
+    ['DWB', '100.0', '17.90', '19.75', '25.8', '10.68', '10.7', '0.00', '3.11', '0.52']]]
+criteria= ["Time", "Path Length", "CPU", "Memory", "Safety"]
+planner_type= ["NavFn", "smac_planner"]
+controller_type= ["RPP", "DWB"]
 
 def performance_analysis(criteria,data,weights,planner_type,controller_type):
     data,combinations,iterations_result=extract_data(criteria,data,planner_type,controller_type)
+    print(data)
     if weights=='None':
         #The user have not spceified weights
         normalized_weights=assign_weight(criteria)
@@ -47,7 +59,7 @@ def extract_data(criteria, data,planner_type,controller_type):
             iteration=len(controller_type)*i+j
             combinations[iteration]+=" "+planner_type[i]
 
-    iterations_results=[inner_list[1] for outer_list in data for inner_list in outer_list[2:]]
+    iterations_results=[float(inner_list[1]) for outer_list in data for inner_list in outer_list[2:]]
     for i in range(len(criteria)):
         if criteria[i]=="Time":
             arranged_data.append([float(inner_list[2]) for outer_list in data for inner_list in outer_list[2:]])
@@ -87,6 +99,7 @@ def assign_weight(criteria_order):
     # Normalize the weights
     total_weight = sum(weights.values())
     normalized_weights = {criterion: weight / total_weight for criterion, weight in weights.items()}
+    normalized_weights
 
     return normalized_weights
 
@@ -105,14 +118,14 @@ def normalizing_data(data):
 
         if not identical_element(data[i+1]):
             for j in range(len(data[i+1])):
-                if data[0][i]=="Safety": 
-                    data[i+1][j]=(data[i+1][j]-min_value[i])/(max_value[i]-min_value[i])
-                else: 
-                    data[i+1][j]=(max_value[i]-data[i+1][j])/(max_value[i]-min_value[i])
+                #if data[0][i]=="Safety": 
+                #    data[i+1][j]=(data[i+1][j]-min_value[i])/(max_value[i]-min_value[i])
+                #else: 
+                data[i+1][j]=(max_value[i]-data[i+1][j])/(max_value[i]-min_value[i])
         else:
             # if all values of a criterion are identical , set all of them to zero as they are not going to affect the final result
             data[i+1]=[0]*len(data[i+1])
-
+    print("metric data",data)
     return data
 
 def identical_element(array):
@@ -125,14 +138,18 @@ def identical_element(array):
 def rank(normailzed_data,weights,combinations,results):
     for i in range(len(normailzed_data[0])):
         for j in range(len(normailzed_data[i+1])):
-            normailzed_data[i+1][j]=round(normailzed_data[i+1][j]*weights[normailzed_data[0][i]],4)
-
+            if normailzed_data[0][i]=="Safety":
+
+                normailzed_data[i+1][j]=normailzed_data[i+1][j]*(-1)*weights[normailzed_data[0][i]]
+            else: 
+                normailzed_data[i+1][j]=normailzed_data[i+1][j]*weights[normailzed_data[0][i]]
+
+
     ranking=[]
     for j in range(len(normailzed_data[1])):
-        ranking.append(sum([sublist[j] for sublist in  normailzed_data[1:]])) 
-
+        ranking.append(round(sum([sublist[j] for sublist in  normailzed_data[1:]]),2)) 
     for i in range(len(results)-1,-1,-1):
-        if results[i]!='succeeded':
+        if results[i]==0.0:
             del combinations[i]
             del ranking[i]
     ranking=dict(zip(combinations,ranking))
@@ -164,7 +181,7 @@ def success_rate(result,controller_type,planner_type):
     controllers=[]
     planners=[] 
     for i in range(len(planner_type)):
-        planners.append("The success rate of "+planner_type[i]+" is "+str(round((result[i*len(controller_type):((i+1)*len(controller_type))].count('succeeded')/len(controller_type))*100,2))+" %")
+        planners.append("The success rate of "+planner_type[i]+" is "+str(round((sum(result[i*len(controller_type):((i+1)*len(controller_type))])/len(controller_type)),2))+" %")
     for i in range(len(controller_type)):   
         controllers.append([])
     for i in range(len(controller_type)):   
@@ -173,7 +190,9 @@ def success_rate(result,controller_type,planner_type):
             controllers[i].append(result[j*len(controller_type)+i])
 
     for i in range(len(controllers)):
-        controllers[i]="The success rate of "+controller_type[i]+" is "+str(round((controllers[i].count('succeeded')/len(planner_type))*100,2))+" %"
+        controllers[i]="The success rate of "+controller_type[i]+" is "+str(round((sum(controllers[i])/len(planner_type)),2))+" %"
     return planners,controllers
 
 
+ranking,planners_success_rate,controllers_success_rate=performance_analysis(criteria,analysis_data,'None',planner_type,controller_type)
+print(ranking)

config/circle_path_scenario.yaml

@@ -2,45 +2,46 @@
 experiment_name: "circular_path_scenario_two_controllers"
 
 #Save directory of results
-results_directory: "/home/riotu/ros2_ws2/src/ROSNavBench/results"
+results_directory: "/home/riotu/ros5_ws/src/ROSNavBench/results"
 
 #  Add the absolute path of the world
-world_path: "/home/riotu/ros2_ws2/src/ROSNavBench/simulations/worlds/scenario_world.world"
+world_path: "/home/riotu/industrial_warehouse.world"
 
 #  Add the absolute path of the map
-map_path: "/home/riotu/ros2_ws2/src/ROSNavBench/simulations/maps/map.yaml"
+map_path: "/home/riotu/ros5_ws/src/ROSNavBench/simulations/maps/warehouse_slam_toolbox.yaml"
 
 #  Add the absolute path of the map
-map_png_path: "/home/riotu/ros2_ws2/src/ROSNavBench/simulations/maps/map.pgm"
+map_png_path: "/home/riotu/ros5_ws/src/ROSNavBench/simulations/maps/warehouse_slam_toolbox.pgm"
 
 #  Add gazebo model path, if multiple path, please spereate them by a :
-models_path: "/opt/ros/humble/share/turtlebot3_gazebo/models:/home/riotu/ros2_ws2/src/ROSNavBench/simulations/models"
+models_path: "/opt/ros/humble/share/turtlebot3_gazebo/models:/home/riotu/ros5_ws/src/ROSNavBench/simulations/models"
 
 #  Choose a type of global local planners to be tested
-planner_type: ["NavFn", "smac_planner"]
+planner_type: ["NavFn"]
 #  Choose one of the following controllers, by adding its name to the controller type list
 #  Note that these are the avaible controllers for the provided example
 #  DWB
 #  RPP
 #  RPP_RSC
 #  DWB_RSC
-controller_type: ["RPP", "DWB", "MPPI"] #name of behaviour tree
+controller_type: ["RPP"] #name of behaviour tree
 
-#  This option is intended for testing the same controller several times
-#  if the user do not need this test, set it to zero
-trails_num: 0
+#  This option is intended for testing the same controller and planner combination several times
+#  Min value is one
+instances_num: 1
 
 #  Add the absolute path of the robot navigation configuration
-nav_config: "/home/riotu/perform_ws/src/ROSNavBench/example/turtlebot3/nav2_config/waffle.yaml"
+nav_config: "/home/riotu/ros5_ws/src/ROSNavBench/example/turtlebot3/nav2_config/waffle_pi.yaml"
 
 #  Add the directory of the behaviour tree
-behaviour_tree_directory: "/home/riotu/perform_ws/src/ROSNavBench/example/turtlebot3/behavior_trees"
+behaviour_tree_directory: "/home/riotu/ros5_ws/src/ROSNavBench/example/turtlebot3/behavior_trees"
 
 #  Add the absolute path of the urdf and model files inside single qoutes ''
-urdf_file: "/opt/ros/humble/share/turtlebot3_description/urdf/turtlebot3_waffle.urdf"
+urdf_file: "/opt/ros/humble/share/turtlebot3_description/urdf/turtlebot3_waffle_pi.urdf"
 
 #  If the robot is spawned by only urdf, then set the model_file to 'None'
-model_file: "/opt/ros/humble/share/turtlebot3_gazebo/models/turtlebot3_waffle/model.sdf"
+model_file: "/opt/ros/humble/share/turtlebot3_gazebo/models/turtlebot3_waffle_pi/model.sdf"
+
 #Citeria for performace analysis includes: "Time" ,"CPU", "Memory", "Path Length" , "Safety"
 criteria: ["Time", "Path Length", "CPU", "Memory", "Safety"]
 
@@ -49,13 +50,13 @@ criteria: ["Time", "Path Length", "CPU", "Memory", "Safety"]
 weights: "None"
 
 #  Provide the pose in a decimal form
-spawn_pose_x: 4.0
-spawn_pose_y: -3.0
+spawn_pose_x: -1.25
+spawn_pose_y: -2.40
 spawn_pose_yaw: -3.13 #radians
 
 #  Specify either to send one goal, specific trajectory, or several waypoints
 #  square, circle, several_waypoints, one_goal
 trajectory_type: "circle"
 
 #  Circule parameter, note that the place of spawn will be the center of the circle
-radius: 1.1
+radius: 2.0

config/narrow_path.yaml → config/differen_tunning_DWB.yaml

@@ -1,63 +1,64 @@
 #  Name the experiment. This name will be the name of the report
-experiment_name: "narrow_path_scenario_report"
+experiment_name: "DWB_tuning"
 
 #Save directory of results
-results_directory: "/home/riotu/perform_ws/src/ROSNavBench/results"
+results_directory: "/home/riotu/ros5_ws/src/ROSNavBench/results"
 
 #  Add the absolute path of the world
-world_path: "/home/riotu/perform_ws/src/ROSNavBench/simulations/worlds/new_dynamic.world"
+world_path: "/home/riotu/industrial_warehouse.world"
 
 #  Add the absolute path of the map
-map_path: "/home/riotu/perform_ws/src/ROSNavBench/simulations/maps/map.yaml"
+map_path: "/home/riotu/ros5_ws/src/ROSNavBench/simulations/maps/warehouse_slam_toolbox.yaml"
 
 #  Add the absolute path of the map
-map_png_path: "/home/riotu/perform_ws/src/ROSNavBench/simulations/maps/map.pgm"
+map_png_path: "/home/riotu/ros5_ws/src/ROSNavBench/simulations/maps/warehouse_slam_toolbox.pgm"
 
 #  Add gazebo model path, if multiple path, please spereate them by a :
-models_path: "/opt/ros/humble/share/turtlebot3_gazebo/models:/home/riotu/perform_ws/src/ROSNavBench/simulations/models"
+models_path: "/opt/ros/humble/share/turtlebot3_gazebo/models:/home/riotu/ros5_ws/src/ROSNavBench/simulations/models"
 
 #  Choose a type of global local planners to be tested
-planner_type: ["NavFn", "smac_planner"]
+planner_type: ["NavFn"]
 #  Choose one of the following controllers, by adding its name to the controller type list
 #  Note that these are the avaible controllers for the provided example
 #  DWB
 #  RPP
 #  RPP_RSC
 #  DWB_RSC
-controller_type: ["RPP", "DWB", "MPPI"] #name of behaviour tree
+controller_type: ["DWB","DWB_1","DWB_2"] #name of behaviour tree
 
-#  This option is intended for testing the same controller several times
-#  if the user do not need this test, set it to zero
-trails_num: 0
+#  This option is intended for testing the same controller and planner combination several times
+#  Min value is one
+instances_num: 1
 
 #  Add the absolute path of the robot navigation configuration
-nav_config: "/home/riotu/perform_ws/src/ROSNavBench/example/turtlebot3/nav2_config/waffle.yaml"
+nav_config: "/home/riotu/ros5_ws/src/ROSNavBench/example/turtlebot3/nav2_config/waffle_pi.yaml"
 
 #  Add the directory of the behaviour tree
-behaviour_tree_directory: "/home/riotu/perform_ws/src/ROSNavBench/example/turtlebot3/behavior_trees"
+behaviour_tree_directory: "/home/riotu/ros5_ws/src/ROSNavBench/example/turtlebot3/behavior_trees"
 
 #  Add the absolute path of the urdf and model files inside single qoutes ''
-urdf_file: "/opt/ros/humble/share/turtlebot3_description/urdf/turtlebot3_waffle.urdf"
+urdf_file: "/opt/ros/humble/share/turtlebot3_description/urdf/turtlebot3_waffle_pi.urdf"
 
 #  If the robot is spawned by only urdf, then set the model_file to 'None'
-model_file: "/opt/ros/humble/share/turtlebot3_gazebo/models/turtlebot3_waffle/model.sdf"
+model_file: "/opt/ros/humble/share/turtlebot3_gazebo/models/turtlebot3_waffle_pi/model.sdf"
+
 #Citeria for performace analysis includes: "Time" ,"CPU", "Memory", "Path Length" , "Safety"
-criteria: ["Time", "Path Length", "CPU", "Memory", "Safety"]
+criteria: ["Time", "CPU"]
+
 #Wieght for each criteria as a number from 1 to 9
 #Set None if the wieght to be set automatcally giving that the importance to the eariler criteria in the matrix
 weights: "None"
 
 #  Provide the pose in a decimal form
-spawn_pose_x: 7.67
-spawn_pose_y: 6.22
+spawn_pose_x: 1.57
+spawn_pose_y: 8.66
 spawn_pose_yaw: -3.13 #radians
 
 #  Specify either to send one goal, specific trajectory, or several waypoints
 #  square, circle, several_waypoints, one_goal
 trajectory_type: "one_goal"
-
 #  One goal parameter
-goal_pose_x: 4.00
-goal_pose_y: 6.22
-goal_pose_yaw: -3.13 #radians
+goal_pose_x: -3.86
+goal_pose_y: 4.29
+goal_pose_yaw: 2.58 #radians
 

config/params.yaml

@@ -2,19 +2,19 @@
 experiment_name: "param_guide"
 
 #Save directory of results
-results_directory: "/home/riotu/ros2_ws2/src/ROSNavBench/results"
+results_directory: "/home/riotu/ros_ws/src/ROSNavBench/results"
 
 #  Add the absolute path of the world
-world_path: "/home/riotu/ros2_ws2/src/ROSNavBench/simulations/worlds/scenario_world.world"
+world_path: "/home/riotu/ros_ws/src/ROSNavBench/simulations/worlds/scenario_world.world"
 
 #  Add the absolute path of the map
-map_path: "/home/riotu/ros2_ws2/src/ROSNavBench/simulations/maps/map.yaml"
+map_path: "/home/riotu/ros_ws/src/ROSNavBench/simulations/maps/map.yaml"
 
 #  Add the absolute path of the map
-map_png_path: "/home/riotu/ros2_ws2/src/ROSNavBench/simulations/maps/map.pgm"
+map_png_path: "/home/riotu/ros_ws/src/ROSNavBench/simulations/maps/map.pgm"
 
 #  Add gazebo model path, if multiple path, please spereate them by a :
-models_path: "/opt/ros/humble/share/turtlebot3_gazebo/models:/home/riotu/ros2_ws2/src/ROSNavBench/simulations/models"
+models_path: "/opt/ros/humble/share/turtlebot3_gazebo/models:/home/riotu/ros_ws/src/ROSNavBench/simulations/models"
 
 #  Choose a type of global local planners to be tested
 planner_type: ["NavFn", "smac_planner"]
@@ -26,21 +26,21 @@ planner_type: ["NavFn", "smac_planner"]
 #  DWB_RSC
 controller_type: ["RPP", "DWB", "MPPI"] #name of behaviour tree
 
-#  This option is intended for testing the same controller several times
-#  if the user do not need this test, set it to zero
-trails_num: 0
+#  This option is intended for testing the same controller and planner combination several times
+#  Min value is one
+instances_num: 1
 
 #  Add the absolute path of the robot navigation configuration
-nav_config: "/home/riotu/perform_ws/src/ROSNavBench/example/turtlebot3/nav2_config/waffle.yaml"
+nav_config: "/home/riotu/ros_ws/src/ROSNavBench/example/turtlebot3/nav2_config/waffle_pi.yaml"
 
 #  Add the directory of the behaviour tree
-behaviour_tree_directory: "/home/riotu/perform_ws/src/ROSNavBench/example/turtlebot3/behavior_trees"
+behaviour_tree_directory: "/home/riotu/ros_ws/src/ROSNavBench/example/turtlebot3/behavior_trees"
 
 #  Add the absolute path of the urdf and model files inside single qoutes ''
-urdf_file: "/opt/ros/humble/share/turtlebot3_description/urdf/turtlebot3_waffle.urdf"
+urdf_file: "/opt/ros/humble/share/turtlebot3_description/urdf/turtlebot3_waffle_pi.urdf"
 
 #  If the robot is spawned by only urdf, then set the model_file to 'None'
-model_file: "/opt/ros/humble/share/turtlebot3_gazebo/models/turtlebot3_waffle/model.sdf"
+model_file: "/opt/ros/humble/share/turtlebot3_gazebo/models/turtlebot3_waffle_pi/model.sdf"
 #Citeria for performace analysis includes: "Time" ,"CPU", "Memory", "Path Length" , "Safety"
 criteria: ["Time", "Path Length", "CPU", "Memory", "Safety"]