def setup_app():
app = Application(name="composite_atlas", modules=["composite"])
atlas = app.add("atlas").add(app.registry.isaac.composite.CompositeAtlas)
atlas.config["cask"] = "packages/composite/tests/waypoints"
pub_node = app.add("pub")
pub = pub_node.add(app.registry.isaac.composite.CompositePublisher,
name="CompositePublisher")
pub.config.tick_period = "20Hz"
pub.config.atlas = "atlas/CompositeAtlas"
pub.config.path = ["cart", "dolly"]
return app, pub
def setup_app():
app = Application(name="follow_path", modules=["composite"])
atlas = app.add("atlas").add(app.registry.isaac.composite.CompositeAtlas)
atlas.config["cask"] = "packages/composite/tests/waypoints"
pub_node = app.add("pub")
pub = pub_node.add(app.registry.isaac.composite.CompositePublisher, name="CompositePublisher")
pub.config.tick_period = "20Hz"
pub.config.atlas = "atlas/CompositeAtlas"
pub.config.path = ["cart", "dolly"]
follow_node = app.add("follow")
follow = follow_node.add(app.registry.isaac.composite.FollowPath)
follow.config.tick_period = "10Hz"
follow.config.wait_time = 0.05
follow_node.add(app.registry.isaac.composite.CompositeMetric)
app.connect(pub, "path", follow, "path")
app.connect(follow, "goal", follow, "state")
return app, follow_node
def main(args):
app = Application(name="detect_net_inference")
# Load subgraph and get interface node
app.load("packages/detect_net/apps/detect_net_inference.subgraph.json",
prefix="detect_net_inference")
detect_net_inferface = app.nodes["detect_net_inference.subgraph"]\
.components["interface"]
# Load configuration
app.load(args.config)
# Configure detection model
detection_model = app.nodes["detect_net_inference.tensor_r_t_inference"]\
.components["isaac.ml.TensorRTInference"]
if args.detection_model_file_path is not None:
detection_model.config.model_file_path = args.detection_model_file_path
if args.etlt_password is not None:
detection_model.config.etlt_password = args.etlt_password
# Configure detection decoder
decoder = app.nodes["detect_net_inference.detection_decoder"]\
.components["isaac.detect_net.DetectNetDecoder"]
decoder.config.output_scale = [args.rows, args.cols]
if args.confidence_threshold is not None:
decoder.config.confidence_threshold = args.confidence_threshold
if args.nms_threshold is not None:
decoder.config.non_maximum_suppression_threshold = args.nms_threshold
if args.mode == 'cask':
# Load replay subgraph and configure interface node
app.load("packages/record_replay/apps/replay.subgraph.json",
prefix="replay")
replay_interface = app.nodes["replay.interface"].components["output"]
replay_interface.config.cask_directory = args.cask_directory
# Connect the output of the replay subgraph to the detection subgraph
app.connect(replay_interface, "color", detect_net_inferface, "image")
elif args.mode == 'sim':
# Load simulation subgraph and get interface node
app.load("packages/navsim/apps/navsim_training.subgraph.json",\
prefix="simulation")
simulation_interface = app.nodes["simulation.interface"].components[
"output"]
# Connect the output of the simulation with user-specified channel to the detection subgraph
app.connect(simulation_interface, args.image_channel,
detect_net_inferface, "image")
elif args.mode == 'realsense':
app.load_module('realsense')
# Create and configure realsense camera codelet
camera = app.add("camera").add(app.registry.isaac.RealsenseCamera)
camera.config.rows = args.rows
camera.config.cols = args.cols
camera.config.color_framerate = args.fps
camera.config.depth_framerate = args.fps
camera.config.enable_ir_stereo = False
# Connect the output of the camera node to the detection subgraph
app.connect(camera, "color", detect_net_inferface, "image")
elif args.mode == 'v4l':
app.load_module('sensors:v4l2_camera')
# Create and configure V4L camera codelet
camera = app.add("camera").add(app.registry.isaac.V4L2Camera)
camera.config.device_id = 0
camera.config.rows = args.rows
camera.config.cols = args.cols
camera.config.rate_hz = args.fps
# Connect the output of the camera node to the detection subgraph
app.connect(camera, "frame", detect_net_inferface, "image")
elif args.mode == 'image':
app.load_module('message_generators')
# Create feeder node
feeder = app.add("feeder").add(
app.registry.isaac.message_generators.ImageLoader)
feeder.config.color_glob_pattern = args.image_directory
feeder.config.tick_period = "1Hz"
feeder.config.focal_length = [args.focal_length, args.focal_length]
feeder.config.optical_center = [
args.optical_center_rows, args.optical_center_cols
]
feeder.config.distortion_coefficients = [0.01, 0.01, 0.01, 0.01, 0.01]
# Connect the output of the image feeder node to the detection subgraph
app.connect(feeder, "color", detect_net_inferface, "image")
else:
raise ValueError('Not supported mode {}'.format(args.mode))
app.run()
and any modifications thereto. Any use, reproduction, disclosure or
distribution of this software and related documentation without an express
license agreement from NVIDIA CORPORATION is strictly prohibited.
'''
from engine.pyalice import Application, Node
if __name__ == '__main__':
app = Application(name="svo_realsense",
modules=[
'perception:stereo_visual_odometry',
'realsense',
'utils',
"viewers",
])
camera = app.add('camera').add(app.registry.isaac.RealsenseCamera)
camera.config.align_to_color = False
camera.config.auto_exposure_priority = False
camera.config.enable_color = False
camera.config.cols = 640
camera.config.rows = 360
camera.config.enable_depth = False
camera.config.enable_depth_laser = False
camera.config.enable_ir_stereo = True
camera.config.ir_framerate = 30
splitter_left = app.add('camera_splitter_left').add(
app.registry.isaac.utils.ColorCameraProtoSplitter)
splitter_left.config.only_pinhole = False
splitter_right = app.add('camera_splitter_right').add(
default=3.0,
help='The framerate at which to record')
parser.add_argument('--rows',
dest='rows',
type=int,
default=720,
help='The vertical resolution of the camera images')
parser.add_argument('--cols',
dest='cols',
type=int,
default=1280,
help='The horizontal resolution of the camera images')
args, _ = parser.parse_known_args()
app = Application(name="record_dummy", modules=["message_generators"])
# Create recorder node
recorder = app.add("recorder").add(app.registry.isaac.alice.Recorder)
recorder.config.base_directory = args.base_directory
# Create dummy camera codelet
camera = app.add("cam").add(
app.registry.isaac.message_generators.CameraGenerator)
camera.config.rows = args.rows
camera.config.cols = args.cols
camera.config.tick_period = str(args.fps) + "Hz"
app.connect(camera, "color_left", recorder, "color")
app.connect(camera, "depth", recorder, "depth")
app.run()
app.load("packages/planner/apps/multi_joint_lqr_control.subgraph.json", prefix="lqr")
# load multi joint lqr control subgraph
lqr_interface = app.nodes["lqr.subgraph"]["interface"]
kinematic_tree = app.nodes["lqr.kinematic_tree"]["KinematicTree"]
lqr_planner = app.nodes["lqr.local_plan"]["MultiJointLqrPlanner"]
app.connect(behavior_interface, "joint_target", lqr_interface, "joint_target")
kinematic_tree.config.kinematic_file = kinematic_file
lqr_planner.config.speed_min = [-1.0] * len(joints)
lqr_planner.config.speed_max = [1.0] * len(joints)
lqr_planner.config.acceleration_min = [-1.0] * len(joints)
lqr_planner.config.acceleration_max = [1.0] * len(joints)
# load hardware subgraph
app.load_module("universal_robots")
arm = app.add("hardware").add(app.registry.isaac.universal_robots.UniversalRobots)
arm.config.robot_ip = "10.32.221.190"
arm.config.control_mode = "joint position"
arm.config.tick_period = '125Hz'
arm.config.kinematic_tree = "lqr.kinematic_tree"
arm.config.tool_digital_out_names = ["valve", "pump"]
arm.config.tool_digital_in_names = ["unknown", "gripper"]
app.connect(arm, "arm_state", lqr_interface, "joint_state")
app.connect(arm, "arm_state", behavior_interface, "joint_state")
app.connect(arm, "io_state", behavior_interface, "io_state")
app.connect(lqr_interface, "joint_command", arm, "arm_command")
app.connect(behavior_interface, "io_command", arm, "io_command")
# visualize IO in sight
widget_io = app.add("sight_widgets").add(app.registry.isaac.sight.SightWidget, "IO")
use_perception = True
app.load(
"packages/object_pose_estimation/apps/pose_cnn_decoder" \
"/detection_pose_estimation_cnn_inference.subgraph.json",
prefix="detection_pose_estimation")
perception_interface = app.nodes[
"detection_pose_estimation.interface"]["Subgraph"]
app.load(
"apps/samples/manipulation/shuffle_box_detection_pose_estimation.config.json"
)
# load sim tsubgraph for tcp connection.
app.load("packages/navsim/apps/navsim_tcp.subgraph.json", "simulation")
sim_in = app.nodes["simulation.interface"]["input"]
sim_out = app.nodes["simulation.interface"]["output"]
app.connect(sim_out, "joint_state", lqr_interface, "joint_state")
app.connect(sim_out, "joint_state", behavior_interface, "joint_state")
app.connect(sim_out, "io_state", behavior_interface, "io_state")
app.connect(lqr_interface, "joint_command", sim_in, "joint_position")
app.connect(behavior_interface, "io_command", sim_in, "io_command")
if use_perception:
app.connect(sim_out, "color", perception_interface, "color")
viewers = app.add("viewers")
depth_viewer = viewers.add(app.registry.isaac.viewers.DepthCameraViewer,
"DepthViewer")
app.connect(sim_out, "depth", depth_viewer, "depth_listener")
depth_viewer.config.max_visualization_depth = 3
# run app
app.run()
choices=['720p', '640x480'],
default='720p',
help='The resolution of the camera images')
args, _ = parser.parse_known_args()
app = Application(name="record_realsense", modules=["realsense"])
if args.mode == '720p':
rows = 720
cols = 1280
elif args.mode == '640x480':
rows = 640
cols = 480
else:
raise ValueError('Not supported camera resolution')
# Create recorder node
recorder = app.add("recorder").add(app.registry.isaac.alice.Recorder)
recorder.config.base_directory = args.base_directory
# Create realsense camera codelet
camera = app.add("cam").add(app.registry.isaac.RealsenseCamera)
camera.config.rows = rows
camera.config.cols = cols
camera.config.color_framerate = args.fps
camera.config.depth_framerate = args.fps
app.connect(camera, "color", recorder, "color")
app.connect(camera, "depth", recorder, "depth")
app.run()
type=int,
default=60,
help='Camera framerate')
parser.add_argument(
'--device_id', dest='device_id', action='store', type=int, help='Camera device id')
args = parser.parse_args()
# Create april_tag_python application
app = Application(
name="april_tags_python",
modules=[
"//packages/perception:april_tags", "realsense", "sensors:v4l2_camera", "viewers", "zed"
])
# Setup camera node
camera = None
if args.camera == "zed":
camera = app.add('input_images').add(app.registry.isaac.ZedCamera)
camera.config.resolution = args.resolution
camera.config.tick_period = '{tick_period}Hz'.format(tick_period=args.framerate)
camera_out_channel = "left_camera_rgb"
elif args.camera == "realsense":
camera = app.add('input_images').add(app.registry.isaac.RealsenseCamera)
camera.config.cols, camera.config.rows = tuple(
[int(arg) for arg in args.resolution.split('x')])
camera.config.color_framerate = args.framerate
camera_out_channel = "color"
elif args.camera == "v4l2":
camera = app.add('input_images').add(app.registry.isaac.V4L2Camera)
if args.device_id == None:
raise ValueError('Could not set None. Please provide device id')
camera.config.device_id = args.device_id
camera.config.cols, camera.config.rows = tuple(
from engine.pyalice import Application
app = Application(name = "mybot")
app.load_module('message_generators')
app.load_module('viewers')
app.load('packages/navsim/apps/navsim_tcp.subgraph.json', 'simulation')
node_view = app.add("viewer")
component_view = node_view.add(app.registry.isaac.viewers.ColorCameraViewer, 'ColorCameraViewer')
node_view = app.add("depth_viewer")
node_view.add(app.registry.isaac.viewers.DepthCameraViewer, 'DepthCameraViewer')
app.connect('simulation.interface/output', 'color', 'viewer/ColorCameraViewer', 'color_listener')
app.connect('simulation.interface/output', 'depth', 'depth_viewer/DepthCameraViewer', 'depth_listener')
app.run()