From 0d52bce1081e7ca358b71edd0e9655e905bbc7d0 Mon Sep 17 00:00:00 2001 From: RKJenamani Date: Tue, 22 Oct 2024 19:40:38 -0400 Subject: [PATCH] bug fixes + intermediate tests + code cleanup --- bite_acquisition/launch/franka.launch | 7 + bite_acquisition/launch/kinova.launch | 93 +++-- bite_acquisition/scripts/configs/default.rviz | 346 ++++++++++++++++ bite_acquisition/scripts/configs/feeding.yaml | 3 +- bite_acquisition/scripts/head_perception.py | 103 ++--- bite_acquisition/scripts/inference_class.py | 156 +------- bite_acquisition/scripts/pixel_selector.py | 5 +- .../__pycache__/base.cpython-310.pyc | Bin 0 -> 1089 bytes .../franka_controller.cpython-310.pyc | Bin 0 -> 5057 bytes .../kinova_controller.cpython-310.pyc | Bin 0 -> 2944 bytes .../robot_controller/franka_controller.py | 13 - .../robot_controller/kinova_controller.py | 44 ++- bite_acquisition/scripts/skill_library.py | 370 +++++------------- .../src/__pycache__/__init__.cpython-310.pyc | Bin 184 -> 172 bytes .../__pycache__/__init__.cpython-310.pyc | Bin 201 -> 189 bytes .../__pycache__/__init__.cpython-310.pyc | Bin 207 -> 195 bytes .../__pycache__/minispanet.cpython-310.pyc | Bin 1450 -> 1438 bytes .../model/__pycache__/resnet.cpython-310.pyc | Bin 6402 -> 6390 bytes .../resnet_dilated_multi.cpython-310.pyc | Bin 1863 -> 1851 bytes .../__pycache__/__init__.cpython-310.pyc | Bin 207 -> 195 bytes .../__pycache__/model.cpython-310.pyc | Bin 3761 -> 3749 bytes .../test/test_acq_skills_pixel_selection.py | 43 ++ .../scripts/test/test_calibration.py | 53 +-- .../scripts/test/test_robot_configs.py | 27 ++ .../scripts/test/test_skewering.py | 36 ++ bite_acquisition/scripts/test/test_speed.py | 87 ---- bite_acquisition/scripts/test/test_srvs.py | 56 --- .../scripts/test/test_transfer.py | 25 ++ .../scripts/test/test_wrist_configs.py | 32 ++ bite_acquisition/scripts/utils.py | 9 +- bite_acquisition/scripts/visualizer.py | 9 + bite_acquisition/scripts/wrist_controller.py | 30 +- .../arms/gen3/6dof/urdf/gen3_macro.xacro | 45 --- .../arms/gen3/7dof/urdf/gen3_macro.xacro | 38 -- .../robots/gen3_6dof_vision.urdf | 38 -- .../robots/gen3_6dof_vision_forque.urdf | 44 --- .../robots/gen3_6dof_vision_forque1.urdf | 38 -- .../robots/gen3_7dof_vision.urdf | 18 - .../tools/feeding_utensil/base_link.STL | Bin 7140084 -> 0 bytes .../{new_base_link.stl => base_link.stl} | Bin .../feeding_utensil/feeding_utensil.xacro | 18 +- .../feeding_utensil_archaic.xacro | 187 --------- .../feeding_utensil/feeding_utensil_old.xacro | 202 ---------- .../{pitch_link.STL => pitch_link.stl} | Bin .../tools/feeding_utensil/roll_link.STL | Bin 1214084 -> 0 bytes .../{roll_link_new.stl => roll_link.stl} | Bin .../tools/feeding_utensil/roll_link_new2.stl | Bin 523484 -> 0 bytes 47 files changed, 810 insertions(+), 1365 deletions(-) create mode 100644 bite_acquisition/scripts/configs/default.rviz create mode 100644 bite_acquisition/scripts/robot_controller/__pycache__/base.cpython-310.pyc create mode 100644 bite_acquisition/scripts/robot_controller/__pycache__/franka_controller.cpython-310.pyc create mode 100644 bite_acquisition/scripts/robot_controller/__pycache__/kinova_controller.cpython-310.pyc create mode 100644 bite_acquisition/scripts/test/test_acq_skills_pixel_selection.py create mode 100644 bite_acquisition/scripts/test/test_robot_configs.py create mode 100644 bite_acquisition/scripts/test/test_skewering.py delete mode 100644 bite_acquisition/scripts/test/test_speed.py delete mode 100644 bite_acquisition/scripts/test/test_srvs.py create mode 100644 bite_acquisition/scripts/test/test_transfer.py create mode 100644 bite_acquisition/scripts/test/test_wrist_configs.py delete mode 100644 kortex_description/tools/feeding_utensil/base_link.STL rename kortex_description/tools/feeding_utensil/{new_base_link.stl => base_link.stl} (100%) delete mode 100644 kortex_description/tools/feeding_utensil/feeding_utensil_archaic.xacro delete mode 100644 kortex_description/tools/feeding_utensil/feeding_utensil_old.xacro rename kortex_description/tools/feeding_utensil/{pitch_link.STL => pitch_link.stl} (100%) delete mode 100644 kortex_description/tools/feeding_utensil/roll_link.STL rename kortex_description/tools/feeding_utensil/{roll_link_new.stl => roll_link.stl} (100%) delete mode 100644 kortex_description/tools/feeding_utensil/roll_link_new2.stl diff --git a/bite_acquisition/launch/franka.launch b/bite_acquisition/launch/franka.launch index 118450a..26b03d0 100644 --- a/bite_acquisition/launch/franka.launch +++ b/bite_acquisition/launch/franka.launch @@ -1,7 +1,14 @@ + + + + + + + diff --git a/bite_acquisition/launch/kinova.launch b/bite_acquisition/launch/kinova.launch index 0c8d2b0..7dd9c9e 100644 --- a/bite_acquisition/launch/kinova.launch +++ b/bite_acquisition/launch/kinova.launch @@ -1,52 +1,47 @@ - - - - - - - - - - - - - - - - - - - - - - ["robot_joint_states", "wrist_joint_states"] - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + ["robot_joint_states", "wrist_joint_states"] + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/bite_acquisition/scripts/configs/default.rviz b/bite_acquisition/scripts/configs/default.rviz new file mode 100644 index 0000000..6bdc932 --- /dev/null +++ b/bite_acquisition/scripts/configs/default.rviz @@ -0,0 +1,346 @@ +Panels: + - Class: rviz/Displays + Help Height: 138 + Name: Displays + Property Tree Widget: + Expanded: + - /Global Options1 + - /Status1 + Splitter Ratio: 0.5 + Tree Height: 628 + - Class: rviz/Selection + Name: Selection + - Class: rviz/Tool Properties + Expanded: + - /2D Pose Estimate1 + - /2D Nav Goal1 + - /Publish Point1 + Name: Tool Properties + Splitter Ratio: 0.5886790156364441 + - Class: rviz/Views + Expanded: + - /Current View1 + Name: Views + Splitter Ratio: 0.5 + - Class: rviz/Time + Name: Time + SyncMode: 0 + SyncSource: Image +Preferences: + PromptSaveOnExit: true +Toolbars: + toolButtonStyle: 2 +Visualization Manager: + Class: "" + Displays: + - Alpha: 0.5 + Cell Size: 1 + Class: rviz/Grid + Color: 160; 160; 164 + Enabled: true + Line Style: + Line Width: 0.029999999329447746 + Value: Lines + Name: Grid + Normal Cell Count: 0 + Offset: + X: 0 + Y: 0 + Z: 0 + Plane: XY + Plane Cell Count: 10 + Reference Frame: + Value: true + - Alpha: 1 + Class: rviz/RobotModel + Collision Enabled: false + Enabled: true + Links: + All Links Enabled: true + Expand Joint Details: false + Expand Link Details: false + Expand Tree: false + Link Tree Style: Links in Alphabetic Order + base_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + bracelet_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + camera_color_frame: + Alpha: 1 + Show Axes: false + Show Trail: false + camera_depth_frame: + Alpha: 1 + Show Axes: false + Show Trail: false + camera_link: + Alpha: 1 + Show Axes: false + Show Trail: false + end_effector_link: + Alpha: 1 + Show Axes: false + Show Trail: false + feeding_utensil_tip: + Alpha: 1 + Show Axes: false + Show Trail: false + finger_tip: + Alpha: 1 + Show Axes: false + Show Trail: false + forearm_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + fork_tip: + Alpha: 1 + Show Axes: false + Show Trail: false + forkbase: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + forkpitch: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + forkroll: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + half_arm_1_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + half_arm_2_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + inertia_link: + Alpha: 1 + Show Axes: false + Show Trail: false + left_inner_finger: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + left_inner_finger_pad: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + left_inner_knuckle: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + left_outer_finger: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + left_outer_knuckle: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + right_inner_finger: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + right_inner_finger_pad: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + right_inner_knuckle: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + right_outer_finger: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + right_outer_knuckle: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + robotiq_arg2f_base_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + shoulder_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + spherical_wrist_1_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + spherical_wrist_2_link: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true + tool_frame: + Alpha: 1 + Show Axes: false + Show Trail: false + world: + Alpha: 1 + Show Axes: false + Show Trail: false + Name: RobotModel + Robot Description: robot_description + TF Prefix: "" + Update Interval: 0 + Value: true + Visual Enabled: true + - Class: rviz/Image + Enabled: true + Image Topic: /camera/color/image_raw + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: Image + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Min Color: 0; 0; 0 + Name: PointCloud2 + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Points + Topic: /camera/depth_registered/points + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Class: rviz/MarkerArray + Enabled: true + Marker Topic: /food_visualization_marker_array + Name: MarkerArray + Namespaces: + "": true + Queue Size: 100 + Value: true + - Alpha: 1 + Class: rviz/PointStamped + Color: 204; 41; 204 + Enabled: true + History Length: 1 + Name: PointStamped + Queue Size: 10 + Radius: 0.20000000298023224 + Topic: /clicked_point + Unreliable: false + Value: true + Enabled: true + Global Options: + Background Color: 48; 48; 48 + Default Light: true + Fixed Frame: map + Frame Rate: 30 + Name: root + Tools: + - Class: rviz/Interact + Hide Inactive Objects: true + - Class: rviz/MoveCamera + - Class: rviz/Select + - Class: rviz/FocusCamera + - Class: rviz/Measure + - Class: rviz/SetInitialPose + Theta std deviation: 0.2617993950843811 + Topic: /initialpose + X std deviation: 0.5 + Y std deviation: 0.5 + - Class: rviz/SetGoal + Topic: /move_base_simple/goal + - Class: rviz/PublishPoint + Single click: true + Topic: /clicked_point + Value: true + Views: + Current: + Class: rviz/Orbit + Distance: 1.0818663835525513 + Enable Stereo Rendering: + Stereo Eye Separation: 0.05999999865889549 + Stereo Focal Distance: 1 + Swap Stereo Eyes: false + Value: false + Field of View: 0.7853981852531433 + Focal Point: + X: 0.3084908425807953 + Y: -0.24151456356048584 + Z: 0.13513000309467316 + Focal Shape Fixed Size: true + Focal Shape Size: 0.05000000074505806 + Invert Z Axis: false + Name: Current View + Near Clip Distance: 0.009999999776482582 + Pitch: 0.6803981065750122 + Target Frame: + Yaw: 1.5453976392745972 + Saved: ~ +Window Geometry: + Displays: + collapsed: false + Height: 1568 + Hide Left Dock: false + Hide Right Dock: false + Image: + collapsed: false + QMainWindow State: 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 + Selection: + collapsed: false + Time: + collapsed: false + Tool Properties: + collapsed: false + Views: + collapsed: false + Width: 1917 + X: 679 + Y: 404 diff --git a/bite_acquisition/scripts/configs/feeding.yaml b/bite_acquisition/scripts/configs/feeding.yaml index 25dc204..3eadca7 100644 --- a/bite_acquisition/scripts/configs/feeding.yaml +++ b/bite_acquisition/scripts/configs/feeding.yaml @@ -1,4 +1,5 @@ -# controller_class: ZeroRPCClient +# Config for feeding with the franka arm + controller_class: PolyMetisController controller_kwargs: ip_address: 192.168.2.121 diff --git a/bite_acquisition/scripts/head_perception.py b/bite_acquisition/scripts/head_perception.py index 8d073b4..82d8cb1 100644 --- a/bite_acquisition/scripts/head_perception.py +++ b/bite_acquisition/scripts/head_perception.py @@ -1,77 +1,78 @@ -import face_alignment -from skimage import io - from rs_ros import RealSenseROS import utils import numpy as np import cv2 +import face_alignment + import rospy from geometry_msgs.msg import Point from std_msgs.msg import Bool -rospy.init_node('head_perception') +if __name__ == '__main__': + + rospy.init_node('head_perception') -fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._2D, flip_input=False) + fa = face_alignment.FaceAlignment(face_alignment.LandmarksType.TWO_D, flip_input=False) -mouth_center_publisher = rospy.Publisher('/mouth_center', Point, queue_size=10) -mouth_open_publisher = rospy.Publisher('/mouth_open', Bool, queue_size=10) + mouth_center_publisher = rospy.Publisher('/mouth_center', Point, queue_size=10) + mouth_open_publisher = rospy.Publisher('/mouth_open', Bool, queue_size=10) -camera = RealSenseROS() + camera = RealSenseROS() -while True: - camera_header, camera_color_data, camera_info_data, camera_depth_data = camera.get_camera_data() + while not rospy.is_shutdown(): + camera_header, camera_color_data, camera_info_data, camera_depth_data = camera.get_camera_data() - if camera_color_data is None or camera_info_data is None or camera_depth_data is None: - print("No data received") - continue + if camera_color_data is None or camera_info_data is None or camera_depth_data is None: + print("No data received") + continue - preds = fa.get_landmarks(camera_color_data) - if preds is None: - print("No face detected") - continue + preds = fa.get_landmarks(camera_color_data) + if preds is None: + print("No face detected") + continue - preds = preds[0] - print("Predicitions:", preds) - print("Number of landmarks:", preds.shape) + preds = preds[0] + print("Predicitions:", preds) + print("Number of landmarks:", preds.shape) - preds_3d = [] + preds_3d = [] - # visualize the landmarks - for pred in preds[48:68]: - validity, pred_3d = utils.pixel2World(camera_info_data, int(pred[0]), int(pred[1]), camera_depth_data, box_width=5) - if validity: - preds_3d.append(pred_3d) - cv2.circle(camera_color_data, (int(pred[0]), int(pred[1])), 2, (0, 255, 0), -1) + # visualize the landmarks + for pred in preds[48:68]: + validity, pred_3d = utils.pixel2World(camera_info_data, int(pred[0]), int(pred[1]), camera_depth_data, box_width=5) + if validity: + preds_3d.append(pred_3d) + cv2.circle(camera_color_data, (int(pred[0]), int(pred[1])), 2, (0, 255, 0), -1) - # visualize the landmarks - # cv2.imshow("Landmarks", camera_color_data) - # cv2.waitKey(1) - - if len(preds_3d) == 0: - print("No valid 3D landmarks") - continue + # visualize the landmarks + # cv2.imshow("Landmarks", camera_color_data) + # cv2.waitKey(1) + + if len(preds_3d) == 0: + print("No valid 3D landmarks") + continue - preds_3d = np.array(preds_3d) - mouth_center_3d = np.mean(preds_3d, axis=0) + preds_3d = np.array(preds_3d) + mouth_center_3d = np.mean(preds_3d, axis=0) - mouth_center_msg = Point() - mouth_center_msg.x = mouth_center_3d[0] - mouth_center_msg.y = mouth_center_3d[1] - mouth_center_msg.z = mouth_center_3d[2] + mouth_center_msg = Point() + mouth_center_msg.x = mouth_center_3d[0] + mouth_center_msg.y = mouth_center_3d[1] + mouth_center_msg.z = mouth_center_3d[2] - mouth_center_publisher.publish(mouth_center_msg) + mouth_center_publisher.publish(mouth_center_msg) - lipDist = np.sqrt( (preds[66][0] - preds[62][0]) ** 2 + (preds[66][1] - preds[62][1]) ** 2) + lipDist = np.sqrt( (preds[66][0] - preds[62][0]) ** 2 + (preds[66][1] - preds[62][1]) ** 2) - lipThickness = float(np.sqrt( (preds[51][0] - preds[62][0]) ** 2 + (preds[51][1] - preds[62][1]) ** 2)/2) + \ - float(np.sqrt( (preds[57][0] - preds[66][0]) ** 2 + (preds[57][1] - preds[66][1]) ** 2)/2) + lipThickness = float(np.sqrt( (preds[51][0] - preds[62][0]) ** 2 + (preds[51][1] - preds[62][1]) ** 2)/2) + \ + float(np.sqrt( (preds[57][0] - preds[66][0]) ** 2 + (preds[57][1] - preds[66][1]) ** 2)/2) - if lipDist >= 1.5 * lipThickness: - mouth_open_publisher.publish(True) - else: - mouth_open_publisher.publish(False) + if lipDist >= 1.5 * lipThickness: + mouth_open_publisher.publish(True) + else: + mouth_open_publisher.publish(False) - # add signal handler to stop the loop - if cv2.waitKey(1) & 0xFF == ord('q'): # press q to break - break \ No newline at end of file + # add signal handler to stop the loop + if cv2.waitKey(1) & 0xFF == ord('q'): # press q to break + break \ No newline at end of file diff --git a/bite_acquisition/scripts/inference_class.py b/bite_acquisition/scripts/inference_class.py index 1bd78a3..30ba654 100644 --- a/bite_acquisition/scripts/inference_class.py +++ b/bite_acquisition/scripts/inference_class.py @@ -12,9 +12,9 @@ from groundingdino.util.inference import Model from segment_anything import sam_model_registry, SamPredictor -from .vision_utils import detect_densest, new_detect_densest, detect_sparsest, detect_centroid, detect_angular_bbox, detect_convex_hull, detect_filling_push_noodles, detect_filling_push_semisolid, efficient_sam_box_prompt_segment, outpaint_masks, detect_blue, proj_pix2mask, cleanup_mask, visualize_keypoints, visualize_skewer, visualize_push, detect_plate, mask_weight, nearest_neighbor, nearest_point_to_mask, detect_furthest_unobstructed_boundary_point, calculate_heatmap_density, calculate_heatmap_entropy, resize_to_square, fill_enclosing_polygon, detect_fillings_in_mask, expanded_detect_furthest_unobstructed_boundary_point +from vision_utils import detect_densest, new_detect_densest, detect_sparsest, detect_centroid, detect_angular_bbox, detect_convex_hull, detect_filling_push_noodles, detect_filling_push_semisolid, efficient_sam_box_prompt_segment, outpaint_masks, detect_blue, proj_pix2mask, cleanup_mask, visualize_keypoints, visualize_skewer, visualize_push, detect_plate, mask_weight, nearest_neighbor, nearest_point_to_mask, detect_furthest_unobstructed_boundary_point, calculate_heatmap_density, calculate_heatmap_entropy, resize_to_square, fill_enclosing_polygon, detect_fillings_in_mask, expanded_detect_furthest_unobstructed_boundary_point -from .preference_planner import PreferencePlanner +from preference_planner import PreferencePlanner import os from openai import OpenAI @@ -26,13 +26,15 @@ import cmath import math -from .src.food_pos_ori_net.model.minispanet import MiniSPANet -from .src.spaghetti_segmentation.model import SegModel +import sys +sys.path.insert(0, "..") +from src.food_pos_ori_net.model.minispanet import MiniSPANet +from src.spaghetti_segmentation.model import SegModel import torchvision.transforms as transforms -PATH_TO_GROUNDED_SAM = '/home/rkjenamani/Grounded-Segment-Anything' -PATH_TO_DEPTH_ANYTHING = '/home/rkjenamani/Depth-Anything' -PATH_TO_SPAGHETTI_CHECKPOINTS = '/home/rkjenamani/flair_ws/src/bite_acquisition/spaghetti_checkpoints' +PATH_TO_GROUNDED_SAM = '/home/isacc/Grounded-Segment-Anything' +PATH_TO_DEPTH_ANYTHING = '/home/isacc/Depth-Anything' +PATH_TO_SPAGHETTI_CHECKPOINTS = '/home/isacc/deployment_ws/src/FLAIR/bite_acquisition/spaghetti_checkpoints' USE_EFFICIENT_SAM = False sys.path.append(PATH_TO_DEPTH_ANYTHING) @@ -1245,142 +1247,4 @@ def get_autonomous_action(self, annotated_image, image, masks, categories, label dip_idx = dip_labels.index(next_bite[1]) return next_actions[acquire_idx], dip_actions[dip_idx] else: - return None, None - -# if __name__ == '__main__': -# inference_server = BiteAcquisitionInference() - -# #items = inference_server.recognize_items(image) -# #inference_server.FOOD_CLASSES = items -# #clean_labels = inference_server.clean_labels(labels[:-1]) -# #inference_server.get_noodle_action(image, masks, labels, categories) -# #inference_server.get_manual_action(annotated_image, image, masks, labels, categories) -# #efficiencies = inference_server.plan_efficient_bites(image, labels, categories) -# #print(efficiencies) - -# #EVAL_DIR = 'filling_noodles' -# EVAL_DIR = 'mashed_potatoes' -# SOURCE_IMAGE_DIR = '%s/images'%EVAL_DIR -# OUTPUT_DIR = 'outputs' - -# if not os.path.exists(OUTPUT_DIR): -# os.mkdir(OUTPUT_DIR) - -# with open(os.path.join(EVAL_DIR, 'priya_labels.txt'), 'r') as f: -# gt_actions = [l.strip() for l in f.readlines()] - -# total_count = 0 -# correct_count = 0 - -# for i, fn in enumerate(os.listdir(SOURCE_IMAGE_DIR)): -# print(i) -# SOURCE_IMAGE_PATH = os.path.join(SOURCE_IMAGE_DIR, '%d.jpg'%(i+1)) -# image = cv2.imread(SOURCE_IMAGE_PATH) -# image = image[0:550, 400:950] -# image = resize_to_square(image, 480) - -# # cv2.imshow('img', image) -# # cv2.waitKey(0) - -# annotated_image, masks, portion_weights, labels = inference_server.detect_items(image, log_path = OUTPUT_DIR + '/' + str(i) + '_') -# #for j in range(len(masks)): -# # if 'blue' == labels[j]: -# # cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_%s.jpg'%(i,labels[j])), masks[j]) - -# categories = inference_server.categorize_items(labels) -# #cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_all.jpg'%(i)), annotated_image) - -# #result = inference_server.get_noodle_action(image, masks, labels, categories) -# result = inference_server.get_scoop_action(image, masks, labels, categories) - -# valid_actions_vis = result[-3] -# heatmap = result[-2] -# action = result[-1] - -# gt_action = gt_actions[i] -# mapping = {'Acquire': 'Scoop', 'Push Filling': 'Push Filling', 'Group': 'Group'} -# action = mapping[action] -# if gt_action in action.lower(): -# correct_count += 1 -# total_count += 1 -# print('Accuracy', correct_count/total_count) - -# #cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_valid.jpg'%(i)), valid_actions_vis) -# cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_action.jpg'%(i)), np.hstack((image, heatmap))) - -if __name__ == "__main__": - - inference_server = BiteAcquisitionInference() - - ### Test for identifying food items - identification_test_dir = 'test_images/identification' - for filename in os.listdir(identification_test_dir): - image = cv2.imread(os.path.join(identification_test_dir, filename)) - items = inference_server.recognize_items(image) - print(items) - - ### Test for segmentation of food items - segmentation_test_dir = 'test_images/segmentation' - segmentation_output_dir = 'outputs/segmentation' - if not os.path.exists(segmentation_output_dir): - os.mkdir(segmentation_output_dir) - - for filename in os.listdir(segmentation_test_dir): - image = cv2.imread(os.path.join(segmentation_test_dir, filename)) - annotated_image, masks, portion_weights, labels = inference_server.detect_items(image, log_path = segmentation_output_dir + '/' + filename[:-4] + '_') - for j in range(len(masks)): - cv2.imwrite(os.path.join(segmentation_test_dir, '%s_%s.jpg'%(filename[:-4],labels[j])), masks[j]) - -# if __name__ == '__main__': -# inference_server = BiteAcquisitionInference() - -# EVAL_DIR = 'filling_noodles' -# SOURCE_IMAGE_DIR = '%s/images'%EVAL_DIR -# OUTPUT_DIR = 'outputs' - -# if not os.path.exists(OUTPUT_DIR): -# os.mkdir(OUTPUT_DIR) - -# with open(os.path.join(EVAL_DIR, 'rajat_labels.txt'), 'r') as f: -# gt_actions = [l.strip() for l in f.readlines()] - -# total_count = 0 -# correct_count = 0 - -# for i, fn in enumerate(os.listdir(SOURCE_IMAGE_DIR)): -# #for i in [11]: -# # try: -# SOURCE_IMAGE_PATH = os.path.join(SOURCE_IMAGE_DIR, '%d.jpg'%(i+1)) -# image = cv2.imread(SOURCE_IMAGE_PATH) -# image = resize_to_square(image, 480) - -# print("Detecting items ..") -# annotated_image, masks, portion_weights, labels = inference_server.detect_items(image, log_path = OUTPUT_DIR + '/' + str(i) + '_') -# #for j in range(len(masks)): -# # cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_%s.jpg'%(i,labels[j])), masks[j]) - -# categories = inference_server.categorize_items(labels) -# #cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_all.jpg'%(i)), annotated_image) - -# print("Categories: ", categories) - -# result = inference_server.get_noodle_action(image, masks, labels, categories) -# valid_actions_vis = result[-3] -# heatmap = result[-2] -# action = result[-1] -# gt_action = gt_actions[i] -# if gt_action in action.lower(): -# correct_count += 1 -# total_count += 1 -# print('Accuracy', correct_count/total_count) - -# #cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_valid.jpg'%(i)), valid_actions_vis) - -# #if 'Probably' not in gt_action: -# # if action in gt_action: -# # correct_count += 1 -# # total_count += 1 -# # print('Accuracy', correct_count/total_count) -# cv2.imwrite(os.path.join(OUTPUT_DIR, '%02d_noodles.jpg'%(i)), np.hstack((image, heatmap))) -# # except: -# # continue + return None, None \ No newline at end of file diff --git a/bite_acquisition/scripts/pixel_selector.py b/bite_acquisition/scripts/pixel_selector.py index eabd4b1..bf7d402 100644 --- a/bite_acquisition/scripts/pixel_selector.py +++ b/bite_acquisition/scripts/pixel_selector.py @@ -25,4 +25,7 @@ def run(self, img, num_clicks=1): break if len(self.clicks) >= num_clicks: break - 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-if __name__ == '__main__': - rospy.init_node('robot_controller', anonymous=True) - robot_controller = FrankaRobotController() - - input('Press enter to move to acquisition position...') - robot_controller.move_to_acq_pose() - - input('Press enter to move to transfer position...') - robot_controller.move_to_transfer_pose() - - input('Press enter to reset the robot...') - robot_controller.reset() \ No newline at end of file diff --git a/bite_acquisition/scripts/robot_controller/kinova_controller.py b/bite_acquisition/scripts/robot_controller/kinova_controller.py index 54c0bce..ad738bb 100644 --- a/bite_acquisition/scripts/robot_controller/kinova_controller.py +++ b/bite_acquisition/scripts/robot_controller/kinova_controller.py @@ -1,4 +1,6 @@ import rospy +from geometry_msgs.msg import Pose +from scipy.spatial.transform import Rotation as R from bite_acquisition.srv import PoseCommand, PoseCommandRequest, PoseCommandResponse from bite_acquisition.srv import JointCommand, JointCommandRequest, JointCommandResponse @@ -9,24 +11,43 @@ class KinovaRobotController(RobotController): def __init__(self): # Do nothing self.DEFAULT_FORCE_THRESHOLD = [30.0, 30.0, 30.0, 30.0, 30.0, 30.0] - self.acq_pos = [0.02961542490849557, 0.06645885626898033, 5.281153370174079, 3.1258331315231405, 2.04992230955969, 4.737864779372388] - self.transfer_pos = [0.3333664491938215, 1.4858324332736625, 1.5856359930210362, 0.8180422599332581, 1.5794872866962613, 4.604932028296647] + + self.robot_type = rospy.get_param('/robot_type') + + if self.robot_type == 'kinova_6dof': + self.acq_pos = [0.02961542490849557, 0.06645885626898033, 5.281153370174079, 3.1258331315231405, 2.04992230955969, 4.737864779372388] + self.transfer_pos = [0.3333664491938215, 1.4858324332736625, 1.5856359930210362, 0.8180422599332581, 1.5794872866962613, 4.604932028296647] + elif self.robot_type == 'kinova_7dof': + self.acq_pos = [0.00420759322479749, 6.1546478371669116, 3.1930894006403285, 4.395995056555025, 0.004538526880496712, 4.969687093309387, 1.6217796163872644] + self.transfer_pos = [5.712775616468747, 0.918896236993586, 2.5843991661045806, 4.561511849883995, 5.430918897235775, 4.673872214171092, 3.9507097286038144] def reset(self): self.move_to_acq_pose() def move_to_pose(self, pose): - print("Calling set_pose with pose: ", pose) + + target_pose = Pose() + target_pose.position.x = pose[0,3] + target_pose.position.y = pose[1,3] + target_pose.position.z = pose[2,3] + + quat = R.from_matrix(pose[:3,:3]).as_quat() + target_pose.orientation.x = quat[0] + target_pose.orientation.y = quat[1] + target_pose.orientation.z = quat[2] + target_pose.orientation.w = quat[3] + + # print("Calling set_pose with pose: ", target_pose) rospy.wait_for_service('set_pose') try: move_to_pose = rospy.ServiceProxy('set_pose', PoseCommand) - resp1 = move_to_pose(pose, self.DEFAULT_FORCE_THRESHOLD) + resp1 = move_to_pose(target_pose, self.DEFAULT_FORCE_THRESHOLD) return resp1.success except rospy.ServiceException as e: print("Service call failed: %s"%e) def set_joint_position(self, joint_position, mode = "POSITION"): - print("Calling set_joint_positions with joint_position: ", joint_position) + # print("Calling set_joint_positions with joint_position: ", joint_position) rospy.wait_for_service('set_joint_position') try: move_to_joint_position = rospy.ServiceProxy('set_joint_position', JointCommand) @@ -42,17 +63,4 @@ def move_to_acq_pose(self): def move_to_transfer_pose(self): print('Moving to transfer pose') self.set_joint_position(self.transfer_pos) - -if __name__ == '__main__': - rospy.init_node('robot_controller', anonymous=True) - robot_controller = KinovaRobotController() - - input('Press enter to move to acquisition position...') - robot_controller.move_to_acq_pose() - - input('Press enter to move to transfer position...') - robot_controller.move_to_transfer_pose() - - input('Press enter to reset the robot...') - robot_controller.reset() \ No newline at end of file diff --git a/bite_acquisition/scripts/skill_library.py b/bite_acquisition/scripts/skill_library.py index 68b55a5..d0a1bad 100644 --- a/bite_acquisition/scripts/skill_library.py +++ b/bite_acquisition/scripts/skill_library.py @@ -1,52 +1,49 @@ -import time import cv2 import numpy as np from scipy.spatial.transform import Rotation import math -import os -import time -import os -import pickle +import threading +import utils +import cmath +import yaml # ros imports import rospy -import tf2_ros from geometry_msgs.msg import Point from sensor_msgs.msg import JointState -from std_msgs.msg import String, Float64, Bool - -import threading -import utils -import cmath -import yaml -import argparse +from std_msgs.msg import Bool from rs_ros import RealSenseROS from pixel_selector import PixelSelector -from robot_controller.franka_controller import FrankaRobotController -from robot_controller.kinova_controller import KinovaRobotController from wrist_controller import WristController from visualizer import Visualizer -ROBOT = 'franka' # 'kinova' or 'franka' -PLATE_HEIGHT = 0.2 # 0.192 for scooping, 0.2 for skewering, 0.198 for pushing, twirling - class SkillLibrary: - def __init__(self, config): + def __init__(self): + + self.robot_type = rospy.get_param('/robot_type') + self.plate_height = rospy.get_param('/plate_height') + self.max_food_height = rospy.get_param('/max_food_height') + self.pixel_selector = PixelSelector() self.tf_utils = utils.TFUtils() self.visualizer = Visualizer() - if ROBOT == 'franka': + if self.robot_type == 'franka': + from robot_controller.franka_controller import FrankaRobotController + config_path = rospy.get_param('/robot_config') + with open(config_path, "r") as f: + config = yaml.load(f, Loader=yaml.Loader) self.robot_controller = FrankaRobotController(config) - elif ROBOT == 'kinova': + elif self.robot_type == 'kinova_6dof' or self.robot_type == 'kinova_7dof': + from robot_controller.kinova_controller import KinovaRobotController self.robot_controller = KinovaRobotController() self.wrist_controller = WristController() - self.beep_publisher = rospy.Publisher('/beep', String, queue_size=10) - print("Skill library initialized") def reset(self): + self.pixel_selector.cleanup() + self.visualizer.clear_visualizations() self.robot_controller.reset() self.wrist_controller.reset() @@ -60,8 +57,7 @@ def move_utensil_to_pose(self, tip_pose, tip_to_wrist = None): self.visualizer.visualize_fork(tip_pose) self.tf_utils.publishTransformationToTF('base_link', 'tool_frame_target', tool_frame_target) - - input("Press enter to actually move utensil.") + self.robot_controller.move_to_pose(tool_frame_target) def scooping_skill(self, color_image, depth_image, camera_info, keypoints = None): @@ -69,6 +65,7 @@ def scooping_skill(self, color_image, depth_image, camera_info, keypoints = None if keypoints is not None: start, end = keypoints else: + print("Click on start and end points for scooping in the pixel selector window.") clicks = self.pixel_selector.run(color_image, num_clicks=2) start = clicks[0] end = clicks[1] @@ -80,59 +77,47 @@ def scooping_skill(self, color_image, depth_image, camera_info, keypoints = None push_angle = utils.angle_between_pixels(np.array(start), np.array(end), color_image.shape[1], color_image.shape[0], orientation_symmetry = False) # push_angle = push_angle - 180 - print("Push angle: ", push_angle) validity, lowest_point = utils.pixel2World(camera_info, start[0], start[1], depth_image) if not validity: - print("Invalid lowest point") + print("ERROR: Scooping start point has invalid depth") return validity, center_point = utils.pixel2World(camera_info, end[0], end[1], depth_image) if not validity: - print("Invalid center point") + print("ERROR: Scooping end point has invalid depth") return fork_rotation_scoop = self.tf_utils.getTransformationFromTF('camera_color_optical_frame', 'fork_tip')[:3,:3] - print("Fork rotation: ", fork_rotation) wrist_rotation = np.linalg.inv(fork_rotation) @ fork_rotation_scoop - # print roll yaw and pitch of wrist rotation - print("Roll: ", Rotation.from_matrix(wrist_rotation).as_euler('xyz', degrees=True)[0]) - print("Yaw: ", Rotation.from_matrix(wrist_rotation).as_euler('xyz', degrees=True)[1]) - print("Pitch: ", Rotation.from_matrix(wrist_rotation).as_euler('xyz', degrees=True)[2]) - - # estimate roation of fork along x axis - scooping_start_pose = np.zeros((4,4)) scooping_start_pose[:3,:3] = Rotation.from_euler('xyz', [0,0,push_angle], degrees=True).as_matrix() @ wrist_rotation scooping_start_pose[:3,3] = lowest_point.reshape(1,3) scooping_start_pose[3,3] = 1 - scooping_start_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ scooping_start_pose - - scooping_start_pose[2,3] = PLATE_HEIGHT + scooping_start_pose[2,3] = self.plate_height scooping_end_pose = np.zeros((4,4)) scooping_end_pose[:3,:3] = Rotation.from_euler('xyz', [0,0,push_angle], degrees=True).as_matrix() @ wrist_rotation scooping_end_pose[:3,3] = center_point.reshape(1,3) scooping_end_pose[3,3] = 1 - scooping_end_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ scooping_end_pose + scooping_end_pose[2,3] = self.plate_height - scooping_end_pose[2,3] = PLATE_HEIGHT + print("Scooping points height: ", scooping_start_pose[2,3], scooping_end_pose[2,3]) - # visualize self.visualizer.visualize_food(scooping_start_pose, id = 0) self.visualizer.visualize_food(scooping_end_pose, id = 1) + input("Check visualized fork tip poses (red cubes) on rviz. If correct, press ENTER to execute action. Otherwise, press CTRL+C to exit.") + # action 2: move to above start position waypoint_1_tip = np.copy(scooping_start_pose) waypoint_1_tip[2,3] += 0.07 self.move_utensil_to_pose(waypoint_1_tip) - # input("Press enter to continue") - # action 3: move down until you are at start position waypoint_2_tip = np.copy(scooping_start_pose) # waypoint_2_tip[2,3] += 0.02 @@ -161,17 +146,15 @@ def dipping_skill(self, color_image, depth_image, camera_info, keypoint = None): if keypoint is not None: (center_x, center_y) = keypoint else: + print("Click on the point to dip in the pixel selector window.") clicks = self.pixel_selector.run(color_image) (center_x, center_y) = clicks[0] - cv2.circle(color_image, (center_x, center_y), 5, (0, 0, 255), -1) - cv2.imshow('vis', color_image) - # get 3D point from depth image validity, point = utils.pixel2World(camera_info, center_x, center_y, depth_image) if not validity: - print("Invalid point") + print("ERROR: Point of dipping has invalid depth") return # action 1: Rotate scooping DoF to dip angle @@ -186,10 +169,12 @@ def dipping_skill(self, color_image, depth_image, camera_info, keypoint = None): point_base = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ point_transform - point_base[2,3] = PLATE_HEIGHT + 0.03 #0.045 + point_base[2,3] = self.plate_height + 0.03 #0.045 self.visualizer.visualize_food(point_base) + input("Check visualized fork tip poses (red cubes) on rviz. If correct, press ENTER to execute action. Otherwise, press CTRL+C to exit.") + # action 2: Move to above position waypoint_1_tip = np.copy(point_base) waypoint_1_tip[2,3] += 0.05 @@ -222,8 +207,9 @@ def cutting_skill(self, color_image, depth_image, camera_info, keypoint = None, # cv2.line(color_image_vis, (center_x-x2,center_y+y2), (cut_point[0]+x2,cut_point[1]-y2), (255,0,0), 2) cutting_angle = math.degrees(cutting_angle) - cutting_angle = cutting_angle + 180 # Rajat ToDo - remove this hack bruh + cutting_angle = cutting_angle + 180 else: + print("Click on the left and right points for cutting in the pixel selector window.") clicks = self.pixel_selector.run(color_image, num_clicks=2) (left_x, left_y) = clicks[0] (right_x, right_y) = clicks[1] @@ -236,18 +222,18 @@ def cutting_skill(self, color_image, depth_image, camera_info, keypoint = None, center_x, center_y = right_x, right_y cutting_angle = utils.angle_between_pixels(np.array(clicks[0]), np.array(clicks[1]), color_image.shape[1], color_image.shape[0], orientation_symmetry = False) - # visualize cutting point and line between left and right points - cv2.circle(color_image, (center_x, center_y), 5, (0, 0, 255), -1) - # cv2.line(color_image, (left_x, left_y), (right_x, right_y), (0, 0, 255), 2) + # # visualize cutting point and line between left and right points + # cv2.circle(color_image, (center_x, center_y), 5, (0, 0, 255), -1) + # # cv2.line(color_image, (left_x, left_y), (right_x, right_y), (0, 0, 255), 2) - cv2.imshow('vis', color_image) - cv2.waitKey(0) + # cv2.imshow('vis', color_image) + # cv2.waitKey(0) # get 3D point from depth image validity, point = utils.pixel2World(camera_info, center_x, center_y, depth_image) if not validity: - print("Invalid point") + print("ERROR: Point of cutting has invalid depth") return fork_rotation = self.tf_utils.getTransformationFromTF('camera_color_optical_frame', 'fork_tip')[:3,:3] @@ -259,7 +245,6 @@ def cutting_skill(self, color_image, depth_image, camera_info, keypoint = None, fork_rotation_cut = self.tf_utils.getTransformationFromTF('camera_color_optical_frame', 'fork_tip')[:3,:3] wrist_rotation = np.linalg.inv(fork_rotation) @ fork_rotation_cut - print('Cutting angle: ', cutting_angle) # update cutting angle to take into account incline of fork tines cutting_angle = cutting_angle + 25 @@ -270,19 +255,21 @@ def cutting_skill(self, color_image, depth_image, camera_info, keypoint = None, cutting_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ cutting_pose - cutting_pose[2,3] = max(cutting_pose[2,3], PLATE_HEIGHT) + cutting_pose[2,3] = max(cutting_pose[2,3], self.plate_height) self.visualizer.visualize_food(cutting_pose) waypoint_1_tip = np.copy(cutting_pose) waypoint_1_tip[2,3] += 0.03 + input("Check visualized fork tip poses (red cubes) on rviz. If correct, press ENTER to execute action. Otherwise, press CTRL+C to exit.") + self.move_utensil_to_pose(waypoint_1_tip) # action 2: Move down until tip touches the plate waypoint_2_tip = np.copy(cutting_pose) - waypoint_2_tip[2,3] = PLATE_HEIGHT - 0.009 + waypoint_2_tip[2,3] = self.plate_height - 0.009 self.move_utensil_to_pose(waypoint_2_tip) tip_to_wrist = self.tf_utils.getTransformationFromTF('fork_tip', 'tool_frame') @@ -292,7 +279,7 @@ def cutting_skill(self, color_image, depth_image, camera_info, keypoint = None, # action 3: Push orthogonal to the cutting angle, in direction of towards the robot (+y relative to the fork) waypoint_3_tip = np.copy(cutting_pose) - waypoint_3_tip[2,3] = PLATE_HEIGHT - 0.009 + waypoint_3_tip[2,3] = self.plate_height - 0.009 y_displacement = np.eye(4) y_displacement[1,3] = 0.02 waypoint_3_tip = waypoint_3_tip @ y_displacement @@ -305,52 +292,45 @@ def cutting_skill(self, color_image, depth_image, camera_info, keypoint = None, self.move_utensil_to_pose(waypoint_4_tip, tip_to_wrist) - def skewering_skill(self, color_image, depth_image, camera_info, keypoint=None, major_axis=None, action_index=0): + def skewering_skill(self, color_image, depth_image, camera_info, keypoint=None, major_axis=None): if keypoint is not None: (center_x, center_y) = keypoint major_axis = np.degrees(major_axis) else: + print("Click on the point to skewer in the pixel selector window.") clicks = self.pixel_selector.run(color_image) (center_x, center_y) = clicks[0] - major_axis = 0 + major_axis = -90 - print(f"Center x {center_x}, Center y {center_y}, Action index {action_index}") - # get 3D point from depth image validity, point = utils.pixel2World(camera_info, center_x, center_y, depth_image) if not validity: - print("Invalid point") + print("ERROR: Point of skewer has invalid depth") return - print("Getting transformation from base_link to camera_color_optical_frame") food_transform = np.eye(4) food_transform[:3,3] = point.reshape(1,3) food_base = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ food_transform - print("---- Height of skewer point: ", food_base[2,3]) + if food_base[2,3] > self.plate_height + self.max_food_height: + print("ERROR: Food detection height is outside max food height (probably because of faulty depth detection). Please try again.") + return - print("Food detection height: ", food_base[2,3]) - input("Press enter to continue") - food_base[2,3] = max(food_base[2,3] - 0.01, PLATE_HEIGHT) - print("---- Height of skewer point (after max): ", food_base[2,3]) + print("Skewering point height: ", food_base[2,3]) + food_base[2,3] = max(food_base[2,3] - 0.01, self.plate_height) food_base[:3,:3] = Rotation.from_euler('xyz', [0,0,0], degrees=True).as_matrix() skewer_axis = -major_axis - 90 - if action_index%2 == 0: # 0s are along major axis - print("-------- Rotating by 90 degrees") - skewer_axis = skewer_axis + 90 - if skewer_axis > 90: - skewer_axis = skewer_axis - 180 - food_base[:3,:3] = Rotation.from_euler('xyz', [0,0,skewer_axis], degrees=True).as_matrix() - self.tf_utils.publishTransformationToTF('base_link', 'food_frame', food_base) self.visualizer.visualize_food(food_base) base_to_tip = self.tf_utils.getTransformationFromTF('base_link', 'fork_tip') food_base[:3,:3] = food_base[:3,:3] @ base_to_tip[:3,:3] + input("Check visualized fork tip poses (red cubes) on rviz. If correct, press ENTER to execute action. Otherwise, press CTRL+C to exit.") + # Action 1: Move to action start position waypoint_1_tip = np.copy(food_base) waypoint_1_tip[2,3] += 0.05 @@ -360,7 +340,7 @@ def skewering_skill(self, color_image, depth_image, camera_info, keypoint=None, waypoint_2_tip = np.copy(food_base) self.move_utensil_to_pose(waypoint_2_tip) - self.scooping_pickup() + self.scooping_pickup(hack=False) # self.move_utensil_to_pose(waypoint_1_tip) # move to home position @@ -369,118 +349,6 @@ def skewering_skill(self, color_image, depth_image, camera_info, keypoint=None, # reset wrist self.wrist_controller.reset() - def joint_state_callback(self, joint_name, msg): - if joint_name in msg.name: - index = msg.name.index(joint_name) - joint_position = msg.position[index] - return joint_position - return None - - def vertical_skewering_skill(self, color_image, depth_image, camera_info, keypoint=None, major_axis=None, action_index=0): - if keypoint is not None: - (center_x, center_y) = keypoint - major_axis = np.degrees(major_axis) - else: - clicks = self.pixel_selector.run(color_image) - (center_x, center_y) = clicks[0] - major_axis = 0 - - print(f"Center x {center_x}, Center y {center_y}, Action index {action_index}") - - # get 3D point from depth image - validity, point = utils.pixel2World(camera_info, center_x, center_y, depth_image) - - if not validity: - print("Invalid point") - return - - # Action 1: Adjust the wrist to the desired state - if action_index == 0 or action_index == 1: - self.wrist_controller.set_wrist_state(0.18 * math.pi,math.pi) - - print("Getting transformation from base_link to camera_color_optical_frame") - food_transform = np.eye(4) - food_transform[:3,3] = point.reshape(1,3) - print('------ Food transform: ', food_transform) - food_base = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ food_transform - print('------ Food base: ', food_base) - - print("---- Height of skewer point: ", food_base[2,3]) - - print("Food detection height: ", food_base[2,3]) - input("Press enter to continue") - food_base[2,3] = max(food_base[2,3] - 0.01, PLATE_HEIGHT) - print("---- Height of skewer point (after max): ", food_base[2,3]) - - food_base[:3,:3] = Rotation.from_euler('xyz', [0,0,0], degrees=True).as_matrix() - - skewer_axis = -major_axis - 90 - if action_index%2 == 0: # 0s are along major axis - print("-------- Rotating by 90 degrees") - skewer_axis = skewer_axis + 90 - if skewer_axis > 90: - skewer_axis = skewer_axis - 180 - - food_base[:3,:3] = Rotation.from_euler('xyz', [0,0,skewer_axis], degrees=True).as_matrix() - - print('------ Food base2: ', food_base) - - self.tf_utils.publishTransformationToTF('base_link', 'food_frame', food_base) - self.visualizer.visualize_food(food_base) - food_base[:3, 3] += [0.026, 0.01, 0] - # inital pose of the fork - init_base = np.copy(food_base) - - - print("Getting transformation from base_link to fork tip") - base_to_forkbase = self.tf_utils.getTransformationFromTF('base_link', 'forkbase') - forkpitch_joint_position = self.joint_state_callback('forkpitch_joint', rospy.wait_for_message('/wrist_joint_states', JointState)) - forkpitch_joint_matrix = np.eye(4) - forkpitch_joint_matrix[:3, :3] = Rotation.from_euler('xyz', [0,-forkpitch_joint_position,0], degrees=False).as_matrix() - forkpitch_joint_matrix[:3, 3] = [0.0375, 0.000, 0.000] - base_to_forkpitch_matrix = np.dot(base_to_forkbase, forkpitch_joint_matrix) - self.tf_utils.publishTransformationToTF('base_link', 'forkpitch', base_to_forkpitch_matrix) - - forkroll_joint_position = self.joint_state_callback('forkroll_joint', rospy.wait_for_message('/wrist_joint_states', JointState)) - forkroll_joint_matrix = np.eye(4) - forkroll_joint_matrix[:3, :3] = Rotation.from_euler('xyz', [forkroll_joint_position,0,0], degrees=False).as_matrix() - forkroll_joint_matrix[:3, 3] = [0.045083, 0.000, 0.000] # x translation as defined in the URDF - base_to_forkroll_matrix = np.dot(base_to_forkpitch_matrix, forkroll_joint_matrix) - self.tf_utils.publishTransformationToTF('base_link', 'forkroll', base_to_forkroll_matrix) - - # print("Forkpitch matrix: ", forkpitch_matrix) - # print("Forkroll matrix: ", forkroll_matrix) - - - base_to_tip = self.tf_utils.getTransformationFromTF('base_link', 'fork_tip') - food_base[:3,:3] = food_base[:3,:3] @ base_to_tip[:3,:3] - init_base[:3,:3] = init_base[:3,:3] @ base_to_tip[:3,:3] - - - - # Action 2: Move to action start position - waypoint_1_tip = np.copy(init_base) - waypoint_1_tip[2,3] += 0.05 - self.move_utensil_to_pose(waypoint_1_tip) - - # Action 3: Move inside food item - waypoint_2_tip = np.copy(food_base) - self.move_utensil_to_pose(waypoint_2_tip) - - # Action 4: Move up - waypoint_3_tip = np.copy(food_base) - waypoint_3_tip[2,3] += 0.05 - self.move_utensil_to_pose(waypoint_3_tip) - - # Action 5: Angle wrist - self.wrist_controller.set_wrist_state(0.4 * math.pi, 0.0) - - # move to home position - self.robot_controller.reset() - - # reset wrist - self.wrist_controller.reset() - def scooping_pickup(self, hack = True): forkpitch_to_tip = self.tf_utils.getTransformationFromTF('forkpitch', 'fork_tip') @@ -500,9 +368,6 @@ def scooping_pickup(self, hack = True): tool_frame_target = fork_base_target @ forkbase_to_tool_frame self.tf_utils.publishTransformationToTF('base_link', 'tool_frame_target', tool_frame_target) - - # print("Press enter to continue") - # input() if hack: scoop_thread = threading.Thread(target=self.wrist_controller.scoop_wrist_hack) @@ -521,55 +386,56 @@ def pushing_skill(self, color_image, depth_image, camera_info, keypoints = None) if keypoints is not None: start, end = keypoints else: + print("Click on the start and end points for pushing in the pixel selector window.") clicks = self.pixel_selector.run(color_image, num_clicks=2) start = clicks[0] end = clicks[1] - - validity, end_vec_3d = utils.pixel2World(camera_info, end[0], end[1], depth_image) - if not validity: - print("Invalid depth detected") - return push_angle = utils.angle_between_pixels(np.array(start), np.array(end), color_image.shape[1], color_image.shape[0], orientation_symmetry = False) validity, start_vec_3d = utils.pixel2World(camera_info, start[0], start[1], depth_image) if not validity: - print("Invalid depth detected") + print("ERROR: Pushing start point has invalid depth") return - print("Executing pushing action.") - - grouping_start_pose = np.zeros((4,4)) - grouping_start_pose[:3,:3] = Rotation.from_euler('xyz', [0,0,push_angle], degrees=True).as_matrix() - grouping_start_pose[:3,3] = start_vec_3d.reshape(1,3) - grouping_start_pose[3,3] = 1 - - grouping_start_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ grouping_start_pose - - #print('here', grouping_start_pose[2], 'z', grouping_start_pose[2,3]) - print("Pushing Depth: ", grouping_start_pose[2,3]) - grouping_start_pose[2,3] = max(PLATE_HEIGHT, grouping_start_pose[2,3]) - - grouping_end_pose = np.zeros((4,4)) - grouping_end_pose[:3,:3] = Rotation.from_euler('xyz', [0,0,push_angle], degrees=True).as_matrix() - grouping_end_pose[:3,3] = end_vec_3d.reshape(1,3) - grouping_end_pose[3,3] = 1 + validity, end_vec_3d = utils.pixel2World(camera_info, end[0], end[1], depth_image) + if not validity: + print("ERROR: Pushing end point has invalid depth") + return + + pushing_start_pose = np.zeros((4,4)) + pushing_start_pose[:3,:3] = Rotation.from_euler('xyz', [0,0,push_angle], degrees=True).as_matrix() + pushing_start_pose[:3,3] = start_vec_3d.reshape(1,3) + pushing_start_pose[3,3] = 1 + pushing_start_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ pushing_start_pose + pushing_start_pose[2,3] = self.plate_height + + pushing_end_pose = np.zeros((4,4)) + pushing_end_pose[:3,:3] = Rotation.from_euler('xyz', [0,0,push_angle], degrees=True).as_matrix() + pushing_end_pose[:3,3] = end_vec_3d.reshape(1,3) + pushing_end_pose[3,3] = 1 + pushing_end_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ pushing_end_pose + pushing_end_pose[2,3] = self.plate_height + + print("Pushing points height: ", pushing_start_pose[2,3], pushing_end_pose[2,3]) - grouping_end_pose = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") @ grouping_end_pose + # visualize + self.visualizer.visualize_food(pushing_start_pose, id = 0) + self.visualizer.visualize_food(pushing_end_pose, id = 1) - grouping_end_pose[2,3] = max(PLATE_HEIGHT, grouping_start_pose[2,3]) + input("Check visualized fork tip poses (red cubes) on rviz. If correct, press ENTER to execute action. Otherwise, press CTRL+C to exit.") # action 1: Move to above start position - waypoint_1 = np.copy(grouping_start_pose) + waypoint_1 = np.copy(pushing_start_pose) waypoint_1[2,3] += 0.05 self.move_utensil_to_pose(waypoint_1) # action 2: Move down until tip touches plate - waypoint_2 = np.copy(grouping_start_pose) + waypoint_2 = np.copy(pushing_start_pose) self.move_utensil_to_pose(waypoint_2) # action 3: Move to end position - waypoint_3 = np.copy(grouping_end_pose) + waypoint_3 = np.copy(pushing_end_pose) self.move_utensil_to_pose(waypoint_3) # action 4: Move a bite up @@ -580,20 +446,19 @@ def pushing_skill(self, color_image, depth_image, camera_info, keypoints = None) # action 5: Move to above start position self.robot_controller.reset() - return - def twirling_skill(self, color_image, depth_image, camera_info, keypoint = None, twirl_angle = None): if keypoint is not None: (center_x, center_y) = keypoint else: + print("Click on the point to twirl in the pixel selector window.") clicks = self.pixel_selector.run(color_image) (center_x, center_y) = clicks[0] twirl_angle = 90 validity, center_point = utils.pixel2World(camera_info, center_x, center_y, depth_image) if not validity: - print("Invalid center pixel") + print("ERROR: Twirl point has invalid depth") return twirl_angle = 90 + twirl_angle @@ -604,12 +469,15 @@ def twirling_skill(self, color_image, depth_image, camera_info, keypoint = None, base_to_camera = self.tf_utils.getTransformationFromTF("base_link", "camera_color_optical_frame") twirl_base_frame = base_to_camera @ twirl_camera_frame + twirl_base_frame[2,3] = self.plate_height - twirl_base_frame[2,3] = PLATE_HEIGHT - - self.visualizer.visualize_fork(twirl_base_frame) + self.visualizer.visualize_food(twirl_base_frame) self.tf_utils.publishTransformationToTF("base_link", "target_fork_tip", twirl_base_frame) + print("Twirl point height: ", twirl_base_frame[2,3]) + + input("Check visualized fork tip poses (red cubes) on rviz. If correct, press ENTER to execute action. Otherwise, press CTRL+C to exit.") + # action 1: Move to above position waypoint_1_tip = np.copy(twirl_base_frame) waypoint_1_tip[2,3] += 0.05 @@ -629,16 +497,12 @@ def twirling_skill(self, color_image, depth_image, camera_info, keypoint = None, # action 5: Move to above position self.robot_controller.reset() - return None - - def move_to_mouth(self, OFFSET = 0.1): - - # # ask to open mouth - # beep_msg = String() - # beep_msg.data = "O pen your mouth." - # self.beep_publisher.publish(beep_msg) + def transfer_to_mouth(self, OFFSET = 0.1): - input('Detect mouth center?') + self.robot_controller.move_to_transfer_pose() + inp = input('Detect mouth center? (y/n): ') + while inp != 'y': + inp = input('Detect mouth center? (y/n): ') # check if mouth is open while True: @@ -651,7 +515,7 @@ def move_to_mouth(self, OFFSET = 0.1): mouth_center_3d_msg = rospy.wait_for_message('/mouth_center', Point) mouth_center_3d = np.array([mouth_center_3d_msg.x, mouth_center_3d_msg.y, mouth_center_3d_msg.z]) - input('Execute transfer?') + input("Press ENTER to move in front of mouth.") base_to_fork_tip = self.tf_utils.getTransformationFromTF('base_link', 'tool_frame') @@ -675,32 +539,6 @@ def move_to_mouth(self, OFFSET = 0.1): self.tf_utils.publishTransformationToTF('base_link', 'transfer_target', transfer_target) self.move_utensil_to_pose(transfer_target) - -if __name__ == "__main__": - rospy.init_node('SkillLibrary') - - parser = argparse.ArgumentParser() - parser.add_argument("--config", type=str, default="/home/limbrepos/feeding_ws/src/franka_feeding/configs/feeding.yaml") - args = parser.parse_args() - - config_path = args.config - with open(config_path, "r") as f: - config = yaml.load(f, Loader=yaml.Loader) - - skill_library = SkillLibrary(config) - skill_library.reset() - - camera = RealSenseROS() - camera_header, camera_color_data, camera_info_data, camera_depth_data = camera.get_camera_data() - - skill_library.skewering_skill(camera_color_data, camera_depth_data, camera_info_data) - - # skill_library.scooping_skill(camera_color_data, camera_depth_data, camera_info_data) - - # skill_library.dipping_skill(camera_color_data, camera_depth_data, camera_info_data) - - # skill_library.pushing_skill(camera_color_data, camera_depth_data, camera_info_data) - - # skill_library.twirling_skill(camera_color_data, camera_depth_data, camera_info_data) - # skill_library.cutting_skill(camera_color_data, camera_depth_data, camera_info_data) \ No newline at end of file + input("Press ENTER to move back to before transfer pose.") + self.robot_controller.move_to_transfer_pose() \ No newline at end of file diff --git a/bite_acquisition/scripts/src/__pycache__/__init__.cpython-310.pyc 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