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OmniGibson
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Merge branch 'master' into igdsl2

This commit is contained in:
Chengshu Li 2020-12-14 20:00:40 -08:00
parent c858edd3ae 66263f48b1
commit 2a67f14046
7 changed files with 84 additions and 56 deletions
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8
docs/robots.md
View File

@ -65,19 +65,19 @@ def main():
p.loadMJCF(floor)
robots = []
config = parse_config('../configs/fetch_p2p_nav.yaml')
config = parse_config('../configs/fetch_reaching.yaml')
fetch = Fetch(config)
robots.append(fetch)
config = parse_config('../configs/jr_p2p_nav.yaml')
config = parse_config('../configs/jr_reaching.yaml')
jr = JR2_Kinova(config)
robots.append(jr)
config = parse_config('../configs/locobot_p2p_nav.yaml')
config = parse_config('../configs/locobot_point_nav.yaml')
locobot = Locobot(config)
robots.append(locobot)
config = parse_config('../configs/turtlebot_p2p_nav.yaml')
config = parse_config('../configs/turtlebot_point_nav.yaml')
turtlebot = Turtlebot(config)
robots.append(turtlebot)

63
examples/demo/ik_example.py
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@ -12,7 +12,7 @@ import numpy as np
def main():
config = parse_config('../configs/fetch_p2p_nav.yaml')
config = parse_config('../configs/fetch_reaching.yaml')
s = Simulator(mode='gui', physics_timestep=1 / 240.0)
scene = EmptyScene()
s.import_scene(scene)
@ -21,41 +21,44 @@ def main():
robot_id = fetch.robot_ids[0]
arm_joints = joints_from_names(robot_id, ['torso_lift_joint','shoulder_pan_joint', 'shoulder_lift_joint', 'upperarm_roll_joint',
'elbow_flex_joint', 'forearm_roll_joint', 'wrist_flex_joint', 'wrist_roll_joint'])
#finger_joints = joints_from_names(robot_id, ['l_gripper_finger_joint', 'r_gripper_finger_joint'])
arm_joints = joints_from_names(robot_id, [
'torso_lift_joint',
'shoulder_pan_joint',
'shoulder_lift_joint',
'upperarm_roll_joint',
'elbow_flex_joint',
'forearm_roll_joint',
'wrist_flex_joint',
'wrist_roll_joint'])
fetch.robot_body.reset_position([0, 0, 0])
fetch.robot_body.reset_orientation([0, 0, 1, 0])
x,y,z = fetch.get_end_effector_position()
#set_joint_positions(robot_id, finger_joints, [0.04,0.04])
print(x,y,z)
x, y, z = fetch.get_end_effector_position()
visual_marker = p.createVisualShape(p.GEOM_SPHERE, radius = 0.02)
marker = p.createMultiBody(baseVisualShapeIndex = visual_marker)
visual_marker = p.createVisualShape(p.GEOM_SPHERE, radius=0.02)
marker = p.createMultiBody(baseVisualShapeIndex=visual_marker)
#max_limits = [0,0] + get_max_limits(robot_id, arm_joints) + [0.05,0.05]
#min_limits = [0,0] + get_min_limits(robot_id, arm_joints) + [0,0]
#rest_position = [0,0] + list(get_joint_positions(robot_id, arm_joints)) + [0.04,0.04]
max_limits = [0,0] + get_max_limits(robot_id, arm_joints)
min_limits = [0,0] + get_min_limits(robot_id, arm_joints)
rest_position = [0,0] + list(get_joint_positions(robot_id, arm_joints))
max_limits = [0, 0] + get_max_limits(robot_id, arm_joints)
min_limits = [0, 0] + get_min_limits(robot_id, arm_joints)
rest_position = [0, 0] + list(get_joint_positions(robot_id, arm_joints))
joint_range = list(np.array(max_limits) - np.array(min_limits))
joint_range = [item + 1 for item in joint_range]
jd = [0.1 for item in joint_range]
print(max_limits)
print(min_limits)
def accurateCalculateInverseKinematics(robotid, endEffectorId, targetPos, threshold, maxIter):
sample_fn = get_sample_fn(robotid, arm_joints)
set_joint_positions(robotid, arm_joints, sample_fn())
it = 0
while it < maxIter:
jointPoses = p.calculateInverseKinematics(robotid, endEffectorId, targetPos,
lowerLimits = min_limits,
upperLimits = max_limits,
jointRanges = joint_range,
restPoses = rest_position,
jointDamping = jd)
jointPoses = p.calculateInverseKinematics(
robotid,
endEffectorId,
targetPos,
lowerLimits=min_limits,
upperLimits=max_limits,
jointRanges=joint_range,
restPoses=rest_position,
jointDamping=jd)
set_joint_positions(robotid, arm_joints, jointPoses[2:10])
ls = p.getLinkState(robotid, endEffectorId)
newPos = ls[4]
@ -66,7 +69,7 @@ def main():
it += 1
print ("Num iter: " + str(it) + ", threshold: " + str(dist))
print("Num iter: " + str(it) + ", residual: " + str(dist))
return jointPoses
while True:
@ -75,10 +78,13 @@ def main():
fetch.robot_body.reset_orientation([0, 0, 1, 0])
threshold = 0.01
maxIter = 100
joint_pos = accurateCalculateInverseKinematics(robot_id, fetch.parts['gripper_link'].body_part_index, [x, y, z],
threshold, maxIter)[2:10]
joint_pos = accurateCalculateInverseKinematics(
robot_id,
fetch.parts['gripper_link'].body_part_index,
[x, y, z],
threshold,
maxIter)[2:10]
#set_joint_positions(robot_id, finger_joints, [0.04, 0.04])
s.step()
keys = p.getKeyboardEvents()
for k, v in keys.items():
@ -94,11 +100,10 @@ def main():
z += 0.01
if (k == ord('x') and (v & p.KEY_IS_DOWN)):
z -= 0.01
p.resetBasePositionAndOrientation(marker, [x,y,z], [0,0,0,1])
p.resetBasePositionAndOrientation(marker, [x, y, z], [0, 0, 0, 1])
s.disconnect()
if __name__ == '__main__':
main()

8
examples/demo/robot_example.py
View File

@ -19,19 +19,19 @@ def main():
p.loadMJCF(floor)
robots = []
config = parse_config('../configs/fetch_p2p_nav.yaml')
config = parse_config('../configs/fetch_reaching.yaml')
fetch = Fetch(config)
robots.append(fetch)
config = parse_config('../configs/jr_p2p_nav.yaml')
config = parse_config('../configs/jr_reaching.yaml')
jr = JR2_Kinova(config)
robots.append(jr)
config = parse_config('../configs/locobot_p2p_nav.yaml')
config = parse_config('../configs/locobot_point_nav.yaml')
locobot = Locobot(config)
robots.append(locobot)
config = parse_config('../configs/turtlebot_p2p_nav.yaml')
config = parse_config('../configs/turtlebot_point_nav.yaml')
turtlebot = Turtlebot(config)
robots.append(turtlebot)

2
gibson2/scenes/scene_base.py
View File

@ -1,4 +1,4 @@
class Scene:
class Scene(object):
"""
Base class for all Scene objects
Contains the base functionalities and the functions that all derived classes need to implement

16
gibson2/simulator.py
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@ -7,6 +7,12 @@ from gibson2.render.mesh_renderer.instances import InstanceGroup, Instance, Robo
from gibson2.render.mesh_renderer.mesh_renderer_tensor import MeshRendererG2G
from gibson2.render.viewer import Viewer, ViewerVR, ViewerSimple
from gibson2.objects.articulated_object import ArticulatedObject, URDFObject
from gibson2.scenes.igibson_indoor_scene import InteractiveIndoorScene
from gibson2.scenes.scene_base import Scene
from gibson2.robots.robot_base import BaseRobot
from gibson2.objects.object_base import Object
import pybullet as p
import gibson2
import os
@ -200,7 +206,8 @@ class Simulator:
:param class_id: Class id for rendering semantic segmentation
:return: pybullet body ids from scene.load function
"""
assert isinstance(scene, Scene) and not isinstance(scene, InteractiveIndoorScene), \
'import_scene can only be called with Scene that is not InteractiveIndoorScene'
# Load the scene. Returns a list of pybullet ids of the objects loaded that we can use to
# load them in the renderer
new_object_pb_ids = scene.load()
@ -223,6 +230,8 @@ class Simulator:
:param scene: iGSDFScene instance
:return: pybullet body ids from scene.load function
"""
assert isinstance(scene, InteractiveIndoorScene), \
'import_ig_scene can only be called with InteractiveIndoorScene'
new_object_ids = scene.load()
self.objects += new_object_ids
if scene.texture_randomization:
@ -279,7 +288,8 @@ class Simulator:
:param use_pbr_mapping: Whether to use pbr mapping
:param shadow_caster: Whether to cast shadow
"""
assert isinstance(obj, Object), \
'import_object can only be called with Object'
# Load the object in pybullet. Returns a pybullet id that we can use to load it in the renderer
new_object_pb_id = obj.load()
self.objects += [new_object_pb_id]
@ -506,6 +516,8 @@ class Simulator:
:param class_id: Class id for rendering semantic segmentation
:return: pybullet id
"""
assert isinstance(robot, BaseRobot), \
'import_robot can only be called with BaseRobot'
ids = robot.load()
visual_objects = []
link_ids = []

2
gibson2/utils/data_utils/ext_scene/README.md
View File

@ -96,7 +96,7 @@ At the same time, real-world free-moving objects can have overlapping bounding b
- if two objects overlap with each other, we try to shrink the bounding boxes. We shrink by no more than 80%.
- we randomize the objects with our object assets, and try to come up with no-collision object configurations from overlapping bounding boxes.
We managed to provide no-collision URDFs for 2239 scenes. If the scene your are converting is among this set, the scene generation process will automatically retrieve the no-collision URDF. If not, **please use the scene at your own discretion**, since the objects might be penetrating with each other.
We managed to provide no-collision URDFs for 6049 scenes. If the scene your are converting is among this set, the scene generation process will automatically retrieve the no-collision URDF. If not, **please use the scene at your own discretion**, since the objects might be penetrating with each other.
### Examine generated scenes

41
test/test.yaml
View File

@ -1,25 +1,34 @@
# scene
scene: stadium
build_graph: false
load_texture: true
pybullet_load_texture: true
trav_map_type: no_obj
trav_map_resolution: 0.1
trav_map_erosion: 2
should_open_all_doors: true
# domain randomization
texture_randomization_freq: null
object_randomization_freq: null
# robot
robot: Turtlebot
velocity: 0.1
is_discrete: false
velocity: 1.0
# task, observation and action
task: pointgoal # pointgoal|objectgoal|areagoal|reaching
# task
task: point_nav_random
target_dist_min: 1.0
target_dist_max: 10.0
initial_pos_z_offset: 0.1
is_discrete: false
additional_states_dim: 4
goal_format: polar
task_obs_dim: 4
# reward
reward_type: l2
success_reward: 10.0
slack_reward: -0.01
potential_reward_weight: 1.0
collision_reward_weight: -0.1
collision_ignore_link_a_ids: [1, 2, 3, 4] # ignore collisions with these robot links
# discount factor
discount_factor: 0.99
@ -28,16 +37,19 @@ discount_factor: 0.99
dist_tol: 0.36 # body width
max_step: 500
max_collisions_allowed: 500
goal_format: polar
# misc config
initial_pos_z_offset: 0.1
collision_ignore_link_a_ids: [1, 2, 3, 4] # ignore collisions with these robot links
# sensor spec
output: [sensor, rgb, depth, scan]
output: [task_obs, rgb, depth, scan]
# image
# ASUS Xtion PRO LIVE
# https://www.asus.com/us/3D-Sensor/Xtion_PRO_LIVE
fisheye: false
image_width: 160
image_height: 120
image_width: 160
image_height: 120
vertical_fov: 45
# depth
depth_low: 0.8
@ -53,11 +65,10 @@ laser_angular_range: 240.0
min_laser_dist: 0.05
laser_link_name: scan_link
# sensor noise
# sensor noise
depth_noise_rate: 0.0
scan_noise_rate: 0.0
# visual objects
visual_object_at_initial_target_pos: true
target_visual_object_visible_to_agent: false
target_visual_object_visible_to_agent: false