[pipeline]

app/app_new_mcts.py

@@ -0,0 +1,27 @@
+import hyperparameters as hp
+from rostok.graph_generators.environments.design_environment import (SubStringDesignEnvironment)
+from rostok.graph_generators.mcts_manager import MCTSManager
+from rostok.graph_generators.search_algorithms.mcts import MCTS
+
+from rostok.library.rule_sets.rulset_simple_fingers import create_rules
+from rostok.graph_grammar.node import GraphGrammar
+import hyperparameters as hp
+from tendon_graph_evaluators import evaluator_tendon_standart, evaluator_tendon_standart_parallel
+import tendon_driven_cfg
+
+if __name__ == "__main__":
+    rule_vocabulary = create_rules()
+
+    init_graph = GraphGrammar()
+    env = SubStringDesignEnvironment(rule_vocabulary, evaluator_tendon_standart_parallel,
+                                     hp.MAX_NUMBER_RULES, init_graph, 0)
+
+    mcts = MCTS(env, hp.MCTS_C)
+    name_directory = input("enter directory name: ")
+    mcts_manager = MCTSManager(mcts, name_directory, verbosity=2, use_date=True)
+    #mcts_manager.save_information_about_search(
+    #    hp, tendon_driven_cfg.default_grasp_objective.object_list)
+
+    for i in range(hp.FULL_LOOP_MCTS):
+        mcts_manager.run_search(hp.BASE_ITERATION_LIMIT_TENDON, 1, 1, 2)
+        mcts_manager.save_results()

app/hyperparameters.py

@@ -1,32 +1,33 @@
-MAX_NUMBER_RULES = 13
+MAX_NUMBER_RULES =  13
+
+BASE_ITERATION_LIMIT_TENDON = 10
+FULL_LOOP_MCTS = 10
+MCTS_C = 5
 
-BASE_ITERATION_LIMIT = 30
-BASE_ITERATION_LIMIT_GRAPH = 200
-BASE_ITERATION_LIMIT_TENDON = 100
 
 ITERATION_REDUCTION_TIME = 0.7
 
 TIME_CRITERION_WEIGHT = 3
-FORCE_CRITERION_WEIGHT = 1
+FORCE_CRITERION_WEIGHT = 0.5
 OBJECT_COG_CRITERION_WEIGHT = 1
 INSTANT_FORCE_CRITERION_WEIGHT = 1
-INSTANT_CONTACTING_LINK_CRITERION_WEIGHT = 1
+INSTANT_CONTACTING_LINK_CRITERION_WEIGHT = 2
 GRASP_TIME_CRITERION_WEIGHT = 1
 FINAL_POSITION_CRITERION_WEIGHT = 5
-REFERENCE_DISTANCE = 0.3
+REFERENCE_DISTANCE = 0.1
 
-CONTROL_OPTIMIZATION_BOUNDS = (3, 15)
+CONTROL_OPTIMIZATION_BOUNDS = (5, 15)
 CONTROL_OPTIMIZATION_BOUNDS_TENDON = (10, 20)
 CONTROL_OPTIMIZATION_ITERATION = 8
 CONTROL_OPTIMIZATION_ITERATION_TENDON = 20
 TENDON_CONST = -5
-TENDON_DISCRETE_FORCES = [10, 15, 20]
+TENDON_DISCRETE_FORCES = [10, 15, 20]  
 
-TIME_STEP_SIMULATION = 0.00001
-GRASP_TIME = 5
-FORCE_TEST_TIME = 5
-TIME_SIMULATION = 10
+TIME_STEP_SIMULATION = 0.0005
+GRASP_TIME = 1.5
+FORCE_TEST_TIME = 3
+TIME_SIMULATION = 4.5
 
-FLAG_TIME_NO_CONTACT = 2.5
-FLAG_TIME_SLIPOUT = 1
+FLAG_TIME_NO_CONTACT = 0.5
+FLAG_TIME_SLIPOUT = 0.4
 FLAG_FLYING_APART = 10

app/tendon_driven_cfg.py

@@ -0,0 +1,59 @@
+from rostok.control_chrono.tendon_controller import TendonControllerParameters
+from rostok.library.obj_grasp.objects import get_object_parametrized_cuboctahedron, get_object_parametrized_dipyramid_3
+from rostok.pipeline.generate_grasper_cfgs import MCTSCfg, SimulationConfig, GraspObjective, BruteForceRewardCfg
+from rostok.simulation_chrono.simulation_scenario import GraspScenario
+import rostok.control_chrono.external_force as f_ext
+from rostok.trajectory_optimizer.control_optimizer import TendonForceOptiVar
+from rostok.utils.numeric_utils import Offset
+
+
+HARD_OBJECT_SET = [
+    get_object_parametrized_cuboctahedron(0.05, mass=0.100),
+    get_object_parametrized_dipyramid_3(0.05, mass=0.200)
+]
+HARD_OBJECT_SET_W = [1.0, 1.0]
+
+
+def get_random_force_with_null_grav(amp):
+    obj_forces = []
+    obj_forces.append(f_ext.NullGravity(0))
+    obj_forces.append(f_ext.RandomForces(amp, 100, 0))
+    obj_forces = f_ext.ExternalForces(obj_forces)
+    return obj_forces
+
+
+def get_default_tendon_params():
+    data = TendonControllerParameters()
+    data.amount_pulley_in_body = 2
+    data.pulley_parameters_for_body = {
+        0: [Offset(-0.14, True), Offset(0.005, False, True),
+            Offset(0, True)],
+        1: [Offset(-0.14, True), Offset(-0.005, False, True),
+            Offset(0, True)]
+    }
+    data.starting_point_parameters = [Offset(-0.02, False), Offset(0.025, False), Offset(0, True)]
+    data.tip_parameters = [Offset(-0.3, True), Offset(-0.005, False, True), Offset(0, True)]
+    return data
+
+
+rand_null_force = get_random_force_with_null_grav(10)
+default_simulation_config = SimulationConfig(0.0005, 4.5, GraspScenario, rand_null_force)
+default_grasp_objective = GraspObjective(
+    # Objects setup
+    HARD_OBJECT_SET,
+    HARD_OBJECT_SET_W,
+    # Event setup
+    event_time_no_contact_param=0.5,
+    event_flying_apart_time_param=10,
+    event_slipout_time_param=0.4,
+    event_grasp_time_param=1.5,
+    event_force_test_time_param=3,
+    # Weight setup
+    time_criterion_weight=3,
+    final_pos_criterion_weight=5,
+    # Object pos setup
+    refernece_distance=0.3)
+
+brute_force_opti_default_cfg = BruteForceRewardCfg([10, 15, 20])
+
+hyperparams_mcts_default = MCTSCfg()

app/tendon_graph_evaluators.py

@@ -0,0 +1,33 @@
+from copy import deepcopy
+from rostok.trajectory_optimizer.control_optimizer import TendonForceOptiVar
+import tendon_driven_cfg
+import rostok.pipeline.generate_grasper_cfgs as pipeline
+
+tendon_optivar_standart = TendonForceOptiVar(tendon_driven_cfg.get_default_tendon_params(),
+                                             params_start_pos=-45)
+
+evaluator_tendon_standart = pipeline.create_reward_calulator(
+    tendon_driven_cfg.default_simulation_config, tendon_driven_cfg.default_grasp_objective,
+    tendon_optivar_standart, tendon_driven_cfg.brute_force_opti_default_cfg)
+
+brute_force_opti_default_cfg_parallel = deepcopy(tendon_driven_cfg.brute_force_opti_default_cfg)
+brute_force_opti_default_cfg_parallel.num_cpu_workers = 6
+
+evaluator_tendon_standart_parallel = pipeline.create_reward_calulator(
+    tendon_driven_cfg.default_simulation_config, tendon_driven_cfg.default_grasp_objective,
+    tendon_optivar_standart, brute_force_opti_default_cfg_parallel)
+
+
+
+tendon_optivar_strong = TendonForceOptiVar(tendon_driven_cfg.get_default_tendon_params(),
+                                           params_start_pos=-60)
+brute_force_opti_strong = deepcopy(tendon_driven_cfg.brute_force_opti_default_cfg)
+brute_force_opti_strong.variants = [30, 40, 50]
+
+simulation_config_strong = deepcopy(tendon_driven_cfg.default_simulation_config)
+simulation_config_strong.obj_disturbance_forces = tendon_driven_cfg.get_random_force_with_null_grav(
+    150)
+
+evaluator_tendon_strong = pipeline.create_reward_calulator(
+    simulation_config_strong, tendon_driven_cfg.default_grasp_objective, tendon_optivar_strong,
+    brute_force_opti_strong)