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RobotTask.py
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from utils import rot_vec
from numpy import savetxt
import numpy as np
from scipy.spatial import distance
from scipy.spatial.transform import Rotation as R
import random
from enum import Enum
class Tasktype(Enum):
RANDOM = 0
EASY = 1
FRONTIER = 2
class RobotTask():
def __init__(self,default_task,):
super(RobotTask, self).__init__()
self.robot_translation = np.array(default_task['robot_pose']['translation']).astype(np.float)
self.robot_rotation = np.array(default_task['robot_pose']['rotation_yaw']).astype(np.float)
self.dolly_translation = np.array(default_task['dolly_pose']['translation']).astype(np.float)
self.dolly_rotation = np.array(default_task['dolly_pose']['rotation_yaw']).astype(np.float)
self.obstacle_translation = np.array(default_task['obstacle_pose']['translation']).astype(np.float)
self.obstacle_rotation = np.array(default_task['obstacle_pose']['rotation_yaw']).astype(np.float)
self.obstacle_1_translation = np.array(default_task['obstacle_1_pose']['translation']).astype(np.float)
self.obstacle_1_rotation = np.array(default_task['obstacle_1_pose']['rotation_yaw']).astype(np.float)
self.obstacle_2_translation = np.array(default_task['obstacle_2_pose']['translation']).astype(np.float)
self.obstacle_2_rotation = np.array(default_task['obstacle_2_pose']['rotation_yaw']).astype(np.float)
self.obstacle_3_translation = np.array(default_task['obstacle_3_pose']['translation']).astype(np.float)
self.obstacle_3_rotation = np.array(default_task['obstacle_3_pose']['rotation_yaw']).astype(np.float)
self.q_value = 0
self.task_type = Tasktype.RANDOM
def randomize_task(self, randomization_params):
"""
randomizes the current task settings according to the randomization parameters (as a json)
"""
num_obstacles = random.randint(0,randomization_params['num_obstacles'])
del_obstacle_translation = np.asarray(randomization_params['del_obstacle_translation'])
self.robot_rotation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['robot_randomization']['rotation_rnd']) )
self.dolly_rotation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['dolly_randomization']['rotation_rnd']) )
self.obstacle_rotation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['rotation_rnd']) )
self.obstacle_1_rotation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['rotation_rnd']) )
self.obstacle_2_rotation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['rotation_rnd']) )
self.obstacle_3_rotation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['rotation_rnd']) )
self.robot_translation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['robot_randomization']['translation_rnd_xyz']) )
#self.dolly_translation += ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['dolly_randomization']['translation_rnd_xyz']) )
min_dist_d_r = randomization_params['min_dist_dolly_robot']
max_dist_d_r = randomization_params['max_dist_dolly_robot']
dolly_pos_spline = randomization_params['dolly_pos_spline_angle']
dolly_distance = min_dist_d_r + np.random.uniform(0,1)*(max_dist_d_r-min_dist_d_r) #create a distance vector with min, max distance according to the config file
dolly_vector = np.array([1,0])*dolly_distance #create the final dolly position as the robot position+distance vector
dolly_pos_rot = ( (-0.5 + np.random.uniform(0,1))) * dolly_pos_spline #rotate it around the origin
dolly_vector = self.robot_translation + np.hstack((rot_vec(dolly_vector,dolly_pos_rot),np.zeros(1)))
self.dolly_translation = dolly_vector
min_dist_r_o = randomization_params['min_dist_robot_obs']
max_dist_r_o = randomization_params['max_dist_robot_obs']
min_dist_d_o = randomization_params['min_dist_dolly_obs']
max_dist_d_o = randomization_params['max_dist_dolly_obs']
obs_mean = randomization_params['obstacle_pos_spline_mean']
obstacle_vectors = []
for i in range(2):
obstacle_distance = min_dist_r_o + np.random.uniform(0,1)*(max_dist_r_o-min_dist_r_o) #create a distance vector with min, max distance according to the config file
obstacle_pos_rot = 90 + np.random.uniform(-obs_mean/2,obs_mean/2)*90+(i*180) #rotate it around the origin
obstacle_vector = np.array([1,0])*obstacle_distance #create the final object position as the robot position+distance vector
obstacle_vector = self.robot_translation + np.hstack((rot_vec(obstacle_vector,obstacle_pos_rot),np.zeros(1)))
obstacle_vectors.append(obstacle_vector)
for i in range(2):
obstacle_distance = min_dist_d_o + np.random.uniform(0,1)*(max_dist_d_o-min_dist_d_o) #create a distance vector with min, max distance according to the config file
obstacle_pos_rot = 90 + np.random.uniform(-obs_mean/2,obs_mean/2)*90+(i*180) #rotate it around the origin
obstacle_vector = np.array([1,0])*obstacle_distance #create the final object position as the dolly position+distance vector
obstacle_vector = self.dolly_translation + np.hstack((rot_vec(obstacle_vector,obstacle_pos_rot),np.zeros(1)))
obstacle_vectors.append(obstacle_vector)
for remove_obj_idx in range(4-1, num_obstacles-1, -1):
obstacle_vectors[remove_obj_idx] = del_obstacle_translation
# now randomly assign the created obstacle vectors to the target translations
rnd_obstcl_indexes = np.random.permutation(np.array([0,1,2,3]))
self.obstacle_translation =obstacle_vectors[rnd_obstcl_indexes[0]] #+= ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['translation_rnd_xyz']) )
self.obstacle_1_translation =obstacle_vectors[rnd_obstcl_indexes[1]] #+= ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['translation_rnd_xyz']) )
self.obstacle_2_translation =obstacle_vectors[rnd_obstcl_indexes[2]] #+= ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['translation_rnd_xyz']) )
self.obstacle_3_translation =obstacle_vectors[rnd_obstcl_indexes[3]] #+= ( (-0.5 + np.random.uniform(0,1)) *np.array(randomization_params['obstacle_randomization']['translation_rnd_xyz']) )
def set_q_value(self, q_value):
self.q_value = q_value
def get_obstacle_translations_array(self):
return np.array([self.obstacle_translation, self.obstacle_1_translation, self.obstacle_2_translation, self.obstacle_3_translation])
def get_task_array(self):
"""
returns the task as a numpy array in the form: [[robo_trans_x,robo_trans_y,robo_trans_z,robo_yaw_angle],
[dolly_trans_x,dolly_trans_y,dolly_trans_z,dolly_yaw_angle],
[obstacle_trans_x,obstacletrans_y,obstacletrans_z,obobstacleyaw_angle]
[obstacle_1_trans_x,obstacle_1_trans_y,obstacle_1_trans_z,obobstacle_1_yaw_angle]
[obstacle_2_trans_x,obstacle_2_trans_y,obstacle_2_trans_z,obobstacle_2_yaw_angle]
[obstacle_3_trans_x,obstacle_3_trans_y,obstacle_3_trans_z,obobstacle_3_yaw_angle]]
"""
robot_part = np.hstack((self.robot_translation, self.robot_rotation))
dolly_part = np.hstack((self.dolly_translation, self.dolly_rotation))
obstacle_part = np.hstack((self.obstacle_translation, self.obstacle_rotation))
obstacle_1_part = np.hstack((self.obstacle_1_translation, self.obstacle_1_rotation))
obstacle_2_part = np.hstack((self.obstacle_2_translation, self.obstacle_2_rotation))
obstacle_3_part = np.hstack((self.obstacle_3_translation, self.obstacle_3_rotation))
task_array = np.array([robot_part,dolly_part,obstacle_part,obstacle_1_part,obstacle_2_part,obstacle_3_part])
return task_array
def from_task_array(self,task_array):
self.robot_translation = task_array[0,0:3]
self.robot_rotation = np.array([task_array[0][3]])
self.dolly_translation = task_array[1,0:3]
self.dolly_rotation = np.array([task_array[1][3]])
self.obstacle_translation = task_array[2,0:3]
self.obstacle_rotation = np.array([task_array[2][3]])
self.obstacle_1_translation = task_array[3,0:3]
self.obstacle_1_rotation = np.array([task_array[3][3]])
self.obstacle_2_translation = task_array[4,0:3]
self.obstacle_2_rotation = np.array([task_array[4][3]])
self.obstacle_3_translation = task_array[5,0:3]
self.obstacle_3_rotation = np.array([task_array[5][3]])
self.q_value = 0