def simulate_demo_traj(sim_env, new_xyz, seg_info, full_trajs, ignore_infeasibility=True, animate=False, interactive=False):
sim_util.reset_arms_to_side(sim_env)
old_xyz = np.squeeze(seg_info["cloud_xyz"])
old_xyz = clouds.downsample(old_xyz, DS_SIZE)
new_xyz = clouds.downsample(new_xyz, DS_SIZE)
handles = []
if animate:
handles.append(sim_env.env.plot3(old_xyz,5, (1,0,0)))
handles.append(sim_env.env.plot3(new_xyz,5, (0,0,1)))
miniseg_starts, miniseg_ends, _ = sim_util.split_trajectory_by_gripper(seg_info, thresh = GRIPPER_ANGLE_THRESHOLD)
success = True
feasible = True
misgrasp = False
print colorize.colorize("mini segments:", "red"), miniseg_starts, miniseg_ends
for (i_miniseg, (i_start, i_end)) in enumerate(zip(miniseg_starts, miniseg_ends)):
if i_miniseg >= len(full_trajs): break
full_traj = full_trajs[i_miniseg]
for lr in 'lr':
gripper_open = sim_util.binarize_gripper(seg_info["%s_gripper_joint"%lr][i_start], GRIPPER_ANGLE_THRESHOLD)
prev_gripper_open = sim_util.binarize_gripper(seg_info["%s_gripper_joint"%lr][i_start-1], GRIPPER_ANGLE_THRESHOLD) if i_start != 0 else False
if not sim_util.set_gripper_maybesim(sim_env, lr, gripper_open, prev_gripper_open):
redprint("Grab %s failed" % lr)
misgrasp = True
success = False
if not success: break
if len(full_traj[0]) > 0:
if not eval_util.traj_is_safe(sim_env, full_traj, COLLISION_DIST_THRESHOLD):
redprint("Trajectory not feasible")
feasible = False
if feasible or ignore_infeasibility:
success &= sim_util.sim_full_traj_maybesim(sim_env, full_traj, animate=animate, interactive=interactive)
else:
success = False
if not success: break
sim_env.sim.settle(animate=animate)
sim_env.sim.release_rope('l')
sim_env.sim.release_rope('r')
sim_util.reset_arms_to_side(sim_env)
if animate:
sim_env.viewer.Step()
return success, feasible, misgrasp, full_trajs
def simulate_demo_traj(sim_env,
new_xyz,
seg_info,
full_trajs,
ignore_infeasibility=True,
animate=False,
interactive=False):
sim_util.reset_arms_to_side(sim_env)
old_xyz = np.squeeze(seg_info["cloud_xyz"])
old_xyz = clouds.downsample(old_xyz, DS_SIZE)
new_xyz = clouds.downsample(new_xyz, DS_SIZE)
handles = []
if animate:
handles.append(sim_env.env.plot3(old_xyz, 5, (1, 0, 0)))
handles.append(sim_env.env.plot3(new_xyz, 5, (0, 0, 1)))
miniseg_starts, miniseg_ends, _ = sim_util.split_trajectory_by_gripper(
seg_info, thresh=GRIPPER_ANGLE_THRESHOLD)
success = True
feasible = True
misgrasp = False
print colorize.colorize("mini segments:",
"red"), miniseg_starts, miniseg_ends
for (i_miniseg, (i_start,
i_end)) in enumerate(zip(miniseg_starts, miniseg_ends)):
if i_miniseg >= len(full_trajs): break
full_traj = full_trajs[i_miniseg]
for lr in 'lr':
gripper_open = sim_util.binarize_gripper(
seg_info["%s_gripper_joint" % lr][i_start],
GRIPPER_ANGLE_THRESHOLD)
prev_gripper_open = sim_util.binarize_gripper(
seg_info["%s_gripper_joint" % lr][i_start - 1],
GRIPPER_ANGLE_THRESHOLD) if i_start != 0 else False
if not sim_util.set_gripper_maybesim(sim_env, lr, gripper_open,
prev_gripper_open):
redprint("Grab %s failed" % lr)
misgrasp = True
success = False
if not success: break
if len(full_traj[0]) > 0:
if not eval_util.traj_is_safe(sim_env, full_traj,
COLLISION_DIST_THRESHOLD):
redprint("Trajectory not feasible")
feasible = False
if feasible or ignore_infeasibility:
success &= sim_util.sim_full_traj_maybesim(
sim_env,
full_traj,
animate=animate,
interactive=interactive)
else:
success = False
if not success: break
sim_env.sim.settle(animate=animate)
sim_env.sim.release_rope('l')
sim_env.sim.release_rope('r')
sim_util.reset_arms_to_side(sim_env)
if animate:
sim_env.viewer.Step()
return success, feasible, misgrasp, full_trajs
def compute_trans_traj(sim_env,
new_xyz,
seg_info,
ignore_infeasibility=True,
animate=False,
interactive=False):
sim_util.reset_arms_to_side(sim_env)
redprint("Generating end-effector trajectory")
old_xyz = np.squeeze(seg_info["cloud_xyz"])
old_xyz = clouds.downsample(old_xyz, DS_SIZE)
new_xyz = clouds.downsample(new_xyz, DS_SIZE)
link_names = ["%s_gripper_tool_frame" % lr for lr in ('lr')]
hmat_list = [(lr, seg_info[ln]['hmat'])
for lr, ln in zip('lr', link_names)]
if GlobalVars.gripper_weighting:
interest_pts = get_closing_pts(seg_info)
else:
interest_pts = None
lr2eetraj, _, old_xyz_warped = warp_hmats_tfm(old_xyz, new_xyz, hmat_list,
interest_pts)
handles = []
if animate:
handles.append(sim_env.env.plot3(old_xyz, 5, (1, 0, 0)))
handles.append(sim_env.env.plot3(new_xyz, 5, (0, 0, 1)))
handles.append(sim_env.env.plot3(old_xyz_warped, 5, (0, 1, 0)))
miniseg_starts, miniseg_ends, _ = sim_util.split_trajectory_by_gripper(
seg_info, thresh=GRIPPER_ANGLE_THRESHOLD)
success = True
feasible = True
misgrasp = False
print colorize.colorize("mini segments:",
"red"), miniseg_starts, miniseg_ends
full_trajs = []
prev_vals = {lr: None for lr in 'lr'}
for (i_miniseg, (i_start,
i_end)) in enumerate(zip(miniseg_starts, miniseg_ends)):
################################
redprint("Generating joint trajectory for part %i" % (i_miniseg))
# figure out how we're gonna resample stuff
# Use inverse kinematics to get trajectory for initializing TrajOpt,
# since demonstrations library does not contain joint angle data for
# left and right arms
ee_hmats = {}
for lr in 'lr':
ee_link_name = "%s_gripper_tool_frame" % lr
# TODO: Change # of timesteps for resampling?
ee_hmats[ee_link_name] = resampling.interp_hmats(
np.arange(i_end + 1 - i_start), np.arange(i_end + 1 - i_start),
lr2eetraj[lr][i_start:i_end + 1])
lr2oldtraj = get_old_joint_traj_ik(sim_env, ee_hmats, prev_vals,
i_start, i_end)
#lr2oldtraj = {}
#for lr in 'lr':
# manip_name = {"l":"leftarm", "r":"rightarm"}[lr]
# old_joint_traj = asarray(seg_info[manip_name][i_start:i_end+1])
# #print (old_joint_traj[1:] - old_joint_traj[:-1]).ptp(axis=0), i_start, i_end
# if sim_util.arm_moved(old_joint_traj):
# lr2oldtraj[lr] = old_joint_traj
if len(lr2oldtraj) > 0:
old_total_traj = np.concatenate(lr2oldtraj.values(), 1)
JOINT_LENGTH_PER_STEP = .1
_, timesteps_rs = sim_util.unif_resample(old_total_traj,
JOINT_LENGTH_PER_STEP)
####
### Generate fullbody traj
bodypart2traj = {}
for (lr, old_joint_traj) in lr2oldtraj.items():
manip_name = {"l": "leftarm", "r": "rightarm"}[lr]
old_joint_traj_rs = mu.interp2d(timesteps_rs,
np.arange(len(old_joint_traj)),
old_joint_traj)
ee_link_name = "%s_gripper_tool_frame" % lr
new_ee_traj = lr2eetraj[lr][i_start:i_end + 1]
new_ee_traj_rs = resampling.interp_hmats(
timesteps_rs, np.arange(len(new_ee_traj)), new_ee_traj)
print "planning trajectory following"
new_joint_traj, pose_errs = planning.plan_follow_traj(
sim_env.robot, manip_name, sim_env.robot.GetLink(ee_link_name),
new_ee_traj_rs, old_joint_traj_rs)
prev_vals[lr] = new_joint_traj[-1]
part_name = {"l": "larm", "r": "rarm"}[lr]
bodypart2traj[part_name] = new_joint_traj
################################
redprint("Executing joint trajectory for part %i using arms '%s'" %
(i_miniseg, bodypart2traj.keys()))
full_traj = sim_util.getFullTraj(sim_env, bodypart2traj)
full_trajs.append(full_traj)
for lr in 'lr':
gripper_open = sim_util.binarize_gripper(
seg_info["%s_gripper_joint" % lr][i_start],
GRIPPER_ANGLE_THRESHOLD)
prev_gripper_open = sim_util.binarize_gripper(
seg_info["%s_gripper_joint" % lr][i_start - 1],
GRIPPER_ANGLE_THRESHOLD) if i_start != 0 else False
if not sim_util.set_gripper_maybesim(sim_env, lr, gripper_open,
prev_gripper_open):
redprint("Grab %s failed" % lr)
misgrasp = True
success = False
if not success: break
if len(full_traj[0]) > 0:
if not eval_util.traj_is_safe(sim_env, full_traj,
COLLISION_DIST_THRESHOLD):
redprint("Trajectory not feasible")
feasible = False
if feasible or ignore_infeasibility:
success &= sim_util.sim_full_traj_maybesim(
sim_env,
full_traj,
animate=animate,
interactive=interactive)
else:
success = False
if not success: break
sim_env.sim.settle(animate=animate)
sim_env.sim.release_rope('l')
sim_env.sim.release_rope('r')
sim_util.reset_arms_to_side(sim_env)
if animate:
sim_env.viewer.Step()
return success, feasible, misgrasp, full_trajs
def compute_trans_traj(sim_env, new_xyz, seg_info, ignore_infeasibility=True, animate=False, interactive=False):
sim_util.reset_arms_to_side(sim_env)
redprint("Generating end-effector trajectory")
old_xyz = np.squeeze(seg_info["cloud_xyz"])
old_xyz = clouds.downsample(old_xyz, DS_SIZE)
new_xyz = clouds.downsample(new_xyz, DS_SIZE)
link_names = ["%s_gripper_tool_frame"%lr for lr in ('lr')]
hmat_list = [(lr, seg_info[ln]['hmat']) for lr, ln in zip('lr', link_names)]
if GlobalVars.gripper_weighting:
interest_pts = get_closing_pts(seg_info)
else:
interest_pts = None
lr2eetraj, _, old_xyz_warped = warp_hmats_tfm(old_xyz, new_xyz, hmat_list, interest_pts)
handles = []
if animate:
handles.append(sim_env.env.plot3(old_xyz,5, (1,0,0)))
handles.append(sim_env.env.plot3(new_xyz,5, (0,0,1)))
handles.append(sim_env.env.plot3(old_xyz_warped,5, (0,1,0)))
miniseg_starts, miniseg_ends, _ = sim_util.split_trajectory_by_gripper(seg_info, thresh = GRIPPER_ANGLE_THRESHOLD)
success = True
feasible = True
misgrasp = False
print colorize.colorize("mini segments:", "red"), miniseg_starts, miniseg_ends
full_trajs = []
prev_vals = {lr:None for lr in 'lr'}
for (i_miniseg, (i_start, i_end)) in enumerate(zip(miniseg_starts, miniseg_ends)):
################################
redprint("Generating joint trajectory for part %i"%(i_miniseg))
# figure out how we're gonna resample stuff
# Use inverse kinematics to get trajectory for initializing TrajOpt,
# since demonstrations library does not contain joint angle data for
# left and right arms
ee_hmats = {}
for lr in 'lr':
ee_link_name = "%s_gripper_tool_frame"%lr
# TODO: Change # of timesteps for resampling?
ee_hmats[ee_link_name] = resampling.interp_hmats(np.arange(i_end+1-i_start), np.arange(i_end+1-i_start), lr2eetraj[lr][i_start:i_end+1])
lr2oldtraj = get_old_joint_traj_ik(sim_env, ee_hmats, prev_vals, i_start, i_end)
#lr2oldtraj = {}
#for lr in 'lr':
# manip_name = {"l":"leftarm", "r":"rightarm"}[lr]
# old_joint_traj = asarray(seg_info[manip_name][i_start:i_end+1])
# #print (old_joint_traj[1:] - old_joint_traj[:-1]).ptp(axis=0), i_start, i_end
# if sim_util.arm_moved(old_joint_traj):
# lr2oldtraj[lr] = old_joint_traj
if len(lr2oldtraj) > 0:
old_total_traj = np.concatenate(lr2oldtraj.values(), 1)
JOINT_LENGTH_PER_STEP = .1
_, timesteps_rs = sim_util.unif_resample(old_total_traj, JOINT_LENGTH_PER_STEP)
####
### Generate fullbody traj
bodypart2traj = {}
for (lr,old_joint_traj) in lr2oldtraj.items():
manip_name = {"l":"leftarm", "r":"rightarm"}[lr]
old_joint_traj_rs = mu.interp2d(timesteps_rs, np.arange(len(old_joint_traj)), old_joint_traj)
ee_link_name = "%s_gripper_tool_frame"%lr
new_ee_traj = lr2eetraj[lr][i_start:i_end+1]
new_ee_traj_rs = resampling.interp_hmats(timesteps_rs, np.arange(len(new_ee_traj)), new_ee_traj)
print "planning trajectory following"
new_joint_traj, pose_errs = planning.plan_follow_traj(sim_env.robot, manip_name,
sim_env.robot.GetLink(ee_link_name), new_ee_traj_rs,old_joint_traj_rs)
prev_vals[lr] = new_joint_traj[-1]
part_name = {"l":"larm", "r":"rarm"}[lr]
bodypart2traj[part_name] = new_joint_traj
################################
redprint("Executing joint trajectory for part %i using arms '%s'"%(i_miniseg, bodypart2traj.keys()))
full_traj = sim_util.getFullTraj(sim_env, bodypart2traj)
full_trajs.append(full_traj)
for lr in 'lr':
gripper_open = sim_util.binarize_gripper(seg_info["%s_gripper_joint"%lr][i_start], GRIPPER_ANGLE_THRESHOLD)
prev_gripper_open = sim_util.binarize_gripper(seg_info["%s_gripper_joint"%lr][i_start-1], GRIPPER_ANGLE_THRESHOLD) if i_start != 0 else False
if not sim_util.set_gripper_maybesim(sim_env, lr, gripper_open, prev_gripper_open):
redprint("Grab %s failed" % lr)
misgrasp = True
success = False
if not success: break
if len(full_traj[0]) > 0:
if not eval_util.traj_is_safe(sim_env, full_traj, COLLISION_DIST_THRESHOLD):
redprint("Trajectory not feasible")
feasible = False
if feasible or ignore_infeasibility:
success &= sim_util.sim_full_traj_maybesim(sim_env, full_traj, animate=animate, interactive=interactive)
else:
success = False
if not success: break
sim_env.sim.settle(animate=animate)
sim_env.sim.release_rope('l')
sim_env.sim.release_rope('r')
sim_util.reset_arms_to_side(sim_env)
if animate:
sim_env.viewer.Step()
return success, feasible, misgrasp, full_trajs