pybullet.calculateInverseKinematics2 memory leak?
Posted: Sat Feb 19, 2022 6:28 pm
Hi, I have a problem with the "pybullet.calculateInverseKinematics2" function. Whenever I call it, the memory usage on my PC increases a little bit. I call this method multiple times a second and the memory seems to keep increasing even after I've exited the function. I replaced the function with its single end effector alternative "pybullet.calculateInverseKinematics" and the memory issue is fixed (it no longer increases). The problem with using the regular "pybullet.calculateInverseKinematics" is that there is computational overhead because now I'm manually calculating each end effector in a for loop and that slows down the processing. Is there a way I can use the multi-end-effector IK function without the memory issue? Thanks.
Code: Select all
def calculateIK3(feet_positions, jointDamping):
pos_body = np.array(p.getBasePositionAndOrientation(hexapod_ID)[0])
orn_body = p.getBasePositionAndOrientation(hexapod_ID)[1]
rest_poses = []
target_pos = []
link_indexes = [x for x in range(3, 24, 4)]
for j in range(6):
rest_poses.append(pos_body + p.multiplyTransforms([0, 0, 0], orn_body, baseToEndEffectorConstVec[j], [0, 0, 0, 1])[0])
tp = p.multiplyTransforms(rest_poses[j], orn_body, feet_positions[j], [0, 0, 0, 1])
target_pos.append(tp[0])
ik2 = [0] * 18
# ik = p.calculateInverseKinematics2(
# hexapod_ID,
# [link_indexes[0]],
# [target_pos[0]],
# lowerLimits=ll,
# upperLimits=ul,
# jointRanges=jr,
# restPoses=rest_poses
# )
# print(ik, len(ik))
iks = []
for j in range(6):
temp_ik = p.calculateInverseKinematics(
hexapod_ID,
link_indexes[j],
target_pos[j]
)
temp_ik = list(temp_ik[(3 * j):3 + (3 * j)])
# print(len(temp_ik), temp_ik)
iks.extend(temp_ik)
# print(iks)
# iks = list(temp_ik[:3]) + [0] * 15
return iks