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Simplified phase period loading #8

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Simplified phase period loading #8

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20 changes: 11 additions & 9 deletions runtime/scripts/v2_rl_walk_mujoco.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,6 @@
from mini_bdx_runtime.onnx_infer import OnnxInfer

from mini_bdx_runtime.raw_imu import Imu
from mini_bdx_runtime.poly_reference_motion import PolyReferenceMotion
from mini_bdx_runtime.xbox_controller import XBoxController
from mini_bdx_runtime.feet_contacts import FeetContacts
from mini_bdx_runtime.eyes import Eyes
Expand Down Expand Up @@ -103,9 +102,12 @@ def __init__(
if self.commands:
self._try_connect_controller()

# Reference motion, but we only really need the length of one phase
# TODO
self.PRM = PolyReferenceMotion("./polynomial_coefficients.pkl")
# Load only the phase period from reference motion data
with open("./polynomial_coefficients.pkl", "rb") as f:
ref_data = pickle.load(f)
first_key = next(iter(ref_data))
self.nb_steps_in_period = int(ref_data[first_key]["period"] * ref_data[first_key]["fps"])

self.imitation_i = 0
self.imitation_phase = np.array([0, 0])
self.phase_frequency_factor = 1.0
Expand Down Expand Up @@ -316,14 +318,14 @@ def run(self):
self.imitation_i += 1 * (
self.phase_frequency_factor + self.phase_frequency_factor_offset
)
self.imitation_i = self.imitation_i % self.PRM.nb_steps_in_period
self.imitation_i = self.imitation_i % self.nb_steps_in_period
self.imitation_phase = np.array(
[
np.cos(
self.imitation_i / self.PRM.nb_steps_in_period * 2 * np.pi
),
np.sin(
self.imitation_i / self.PRM.nb_steps_in_period * 2 * np.pi
self.imitation_i / self.nb_steps_in_period * 2 * np.pi
),
np.cos(
self.imitation_i / self.nb_steps_in_period * 2 * np.pi
),
]
)
Expand Down
15 changes: 8 additions & 7 deletions training/playground/open_duck_mini_v2/mujoco_infer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@
import time
import argparse
from playground.common.onnx_infer import OnnxInfer
from playground.common.poly_reference_motion_numpy import PolyReferenceMotion
from playground.common.utils import LowPassActionFilter

from playground.open_duck_mini_v2.mujoco_infer_base import MJInferBase
Expand All @@ -33,7 +32,11 @@ def __init__(
self.action_filter = LowPassActionFilter(50, cutoff_frequency=37.5)

if not self.standing:
self.PRM = PolyReferenceMotion(reference_data)
# Load only the phase period from reference motion data
with open(reference_data, "rb") as f:
ref_data = pickle.load(f)
first_key = next(iter(ref_data))
self.nb_steps_in_period = int(ref_data[first_key]["period"] * ref_data[first_key]["fps"])

self.policy = OnnxInfer(onnx_model_path, awd=True)

Expand Down Expand Up @@ -174,21 +177,19 @@ def run(self):
if not self.standing:
self.imitation_i += 1.0 * self.phase_frequency_factor
self.imitation_i = (
self.imitation_i % self.PRM.nb_steps_in_period
self.imitation_i % self.nb_steps_in_period
)
# print(self.PRM.nb_steps_in_period)
# exit()
self.imitation_phase = np.array(
[
np.cos(
self.imitation_i
/ self.PRM.nb_steps_in_period
/ self.nb_steps_in_period
* 2
* np.pi
),
np.sin(
self.imitation_i
/ self.PRM.nb_steps_in_period
/ self.nb_steps_in_period
* 2
* np.pi
),
Expand Down