import numpy as np import pinocchio as pin from .utils import RobotLoader class HumanLoader(RobotLoader): path = "human_description" urdf_filename = "human.urdf" free_flyer = True ref_posture = "anatomical" # Enforced, unchangeable free-flyer orientation (90° about X, and Y↔Z swap) freeflyer_ori: np.ndarray = np.array( [ [1, 0, 0], [0, 0, -1], [0, 1, 0], ] ) def __init__( self, height: float | None = None, weight: float | None = None, gender: str = "m", verbose: bool = False, ): """ Initialize the robot loader with optional scaling and configuration parameters. The scaling of the model is based on Dumas 2007, except for the abdomen and thorax segments, which are scaled based de Leva 1996. Parameters: height (float, optional): The height to scale the robot model to. If None, uses the default height in the urdf of 1.80m. weight (float, optional): The weight to scale the robot model to. If None, uses the default weight in the urdf 75kg. gender (str, optional): The gender specification for scaling, default is 'm'. verbose (bool, optional): If True, enables verbose output. Default is False. Behavior: - Calls the base loader's initializer. - If height or weight is provided, scales the robot model accordingly. - The free-flyer is present, it enforces its orientation and reapplies joint limits. """ # call base loader super().__init__(verbose=verbose) if height is not None or weight is not None: self._scale_pin_model( self.robot.model, self.robot.visual_model, height, weight, gender ) # automatically apply the enforced free-flyer orientation if self.free_flyer: # get joint index j_id = self.robot.model.getJointId("root_joint") # assign enforced rotation self.robot.model.jointPlacements[j_id].rotation = self.freeflyer_ori # re-apply limits self.addFreeFlyerJointLimits() @staticmethod def get_dict_inertial_param( height: float, weight: float, gender: str = "m" ) -> dict: inertial_segment_names = [ "middle_pelvis", "left_upperleg", "left_lowerleg", "left_foot", "middle_abdomen", "middle_thorax", "middle_head", "left_upperarm", "left_lowerarm", "left_hand", "right_upperarm", "right_lowerarm", "right_hand", "right_upperleg", "right_lowerleg", "right_foot", ] sgt_lengths = {} dicts = [] # Ratios from Dumas 2007 and De Leva 1996 for abdomen and thorax for name in inertial_segment_names: dict_sgmt = {} if name == "middle_pelvis": length = (0.0634 if gender == "f" else 0.0505) * height sgt_lengths["middle_pelvis_0"] = length sgt_lengths["middle_pelvis_0_width"] = ( 0.1478 if gender == "f" else 0.1265 ) * height dict_sgmt["mass"] = np.round( (0.146 if gender == "f" else 0.142) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.009, -0.232, 0.002]) if gender == "f" else np.array([0.028, -0.28, -0.006]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.91) ** 2, -((length * 0.34) ** 2), -((length * 0.01) ** 2), (length * 1) ** 2, -((length * 0.01) ** 2), (length * 0.79) ** 2, ] ) if gender == "f" else np.array( [ (length * 1.01) ** 2, -((length * 0.25) ** 2), -((length * 0.12) ** 2), (length * 1.06) ** 2, -((length * 0.08) ** 2), (length * 0.95) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "left_upperleg": length = (0.2354 if gender == "f" else 0.2441) * height sgt_lengths["left_upperleg_0"] = length dict_sgmt["mass"] = np.round( (0.146 if gender == "f" else 0.123) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.077, -0.377, 0.009]) if gender == "f" else np.array([-0.041, -0.429, 0.033]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.31) ** 2, (length * 0.07) ** 2, -((length * 0.02) ** 2), (length * 0.19) ** 2, -((length * 0.07) ** 2), (length * 0.32) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.29) ** 2, (length * 0.07) ** 2, -((length * 0.02) ** 2), (length * 0.15) ** 2, -((length * 0.07) ** 2), (length * 0.3) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "left_lowerleg": length = (0.2410 if gender == "f" else 0.2446) * height sgt_lengths["left_lowerleg_0"] = length dict_sgmt["mass"] = np.round( (0.045 if gender == "f" else 0.048) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.049, -0.404, 0.031]) if gender == "f" else np.array([-0.048, -0.41, 0.007]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.28) ** 2, (length * 0.02) ** 2, (length * 0.01) ** 2, (length * 0.1) ** 2, (length * 0.06) ** 2, (length * 0.28) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.28) ** 2, (length * 0.04) ** 2, (length * 0.02) ** 2, (length * 0.1) ** 2, (length * 0.05) ** 2, (length * 0.28) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "left_foot": length = (0.1447 if gender == "f" else 0.1497) * height sgt_lengths["left_foot_0"] = length dict_sgmt["mass"] = np.round( (0.01 if gender == "f" else 0.012) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([0.27, -0.218, 0.039]) if gender == "f" else np.array([0.382, -0.151, 0.026]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.17) ** 2, -((length * 0.10) ** 2), (length * 0.06) ** 2, (length * 0.36) ** 2, -((length * 0.04) ** 2), (length * 0.35) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.17) ** 2, (length * 0.13) ** 2, -((length * 0.08) ** 2), (length * 0.37) ** 2, (length * 0) ** 2, (length * 0.36) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "middle_abdomen": length = (0.1183 if gender == "f" else 0.1237) * height sgt_lengths["middle_abdomen_0"] = length dict_sgmt["mass"] = np.round( (0.1465 if gender == "f" else 0.1633) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.016, -0.4512, -0.006]) if gender == "f" else np.array([-0.036, 0.4502, -0.002]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.29) ** 2, (length * 0.22) ** 2, (length * 0.05) ** 2, (length * 0.27) ** 2, -((length * 0.05) ** 2), (length * 0.29) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.27) ** 2, (length * 0.18) ** 2, -((length * 0.02) ** 2), (length * 0.25) ** 2, -((length * 0.04) ** 2), (length * 0.28) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "middle_thorax": length = (0.1314 if gender == "f" else 0.1390) * height sgt_lengths["middle_thorax_0"] = length dict_sgmt["mass"] = np.round( (0.1545 if gender == "f" else 0.1596) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.016, 0.5050, -0.006]) if gender == "f" else np.array([-0.036, 0.5066, -0.002]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.29) ** 2, (length * 0.22) ** 2, (length * 0.05) ** 2, (length * 0.27) ** 2, -((length * 0.05) ** 2), (length * 0.29) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.27) ** 2, (length * 0.18) ** 2, -((length * 0.02) ** 2), (length * 0.25) ** 2, -((length * 0.04) ** 2), (length * 0.28) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "middle_head": length = (0.1308 if gender == "f" else 0.1310) * height sgt_lengths["middle_head_0"] = length dict_sgmt["mass"] = np.round( 0.067 * weight, 2 ) # same for male and female dict_sgmt["com"] = np.round( ( np.array([-0.07, 0.597, 0]) if gender == "f" else np.array([-0.062, 0.555, 0.001]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.32) ** 2, -((length * 0.06) ** 2), (length * 0.01) ** 2, (length * 0.27) ** 2, -((length * 0.01) ** 2), (length * 0.34) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.31) ** 2, -((length * 0.09) ** 2), -((length * 0.02) ** 2), (length * 0.25) ** 2, (length * 0.03) ** 2, (length * 0.33) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "left_upperarm": length = (0.1510 if gender == "f" else 0.1531) * height sgt_lengths["left_upperarm_0"] = length dict_sgmt["mass"] = np.round( (0.022 if gender == "f" else 0.024) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.073, -0.454, -0.028]) if gender == "f" else np.array([0.017, -0.452, -0.026]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.33) ** 2, (length * 0.03) ** 2, -((length * 0.05) ** 2), (length * 0.17) ** 2, -((length * 0.14) ** 2), (length * 0.33) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.31) ** 2, (length * 0.06) ** 2, (length * 0.05) ** 2, (length * 0.14) ** 2, (length * 0.02) ** 2, (length * 0.32) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "left_lowerarm": length = (0.1534 if gender == "f" else 0.1593) * height sgt_lengths["left_lowerarm_0"] = length dict_sgmt["mass"] = np.round( (0.013 if gender == "f" else 0.017) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([0.021, -0.411, 0.019]) if gender == "f" else np.array([0.01, -0.417, 0.014]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.26) ** 2, (length * 0.1) ** 2, (length * 0.04) ** 2, (length * 0.14) ** 2, -((length * 0.13) ** 2), (length * 0.25) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.28) ** 2, (length * 0.03) ** 2, (length * 0.02) ** 2, (length * 0.11) ** 2, -((length * 0.08) ** 2), (length * 0.27) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "left_hand": length = (0.0989 if gender == "f" else 0.1014) * height sgt_lengths["left_hand_0"] = length dict_sgmt["mass"] = np.round( (0.005 if gender == "f" else 0.006) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([0.077, -0.768, 0.048]) if gender == "f" else np.array([0.082, -0.839, 0.074]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.63) ** 2, (length * 0.29) ** 2, (length * 0.23) ** 2, (length * 0.43) ** 2, -((length * 0.28) ** 2), (length * 0.58) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.61) ** 2, (length * 0.22) ** 2, (length * 0.15) ** 2, (length * 0.38) ** 2, -((length * 0.2) ** 2), (length * 0.56) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "right_upperarm": length = (0.1510 if gender == "f" else 0.1531) * height sgt_lengths["right_upperarm_0"] = length dict_sgmt["mass"] = np.round( (0.022 if gender == "f" else 0.024) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.073, -0.454, -0.028]) if gender == "f" else np.array([0.017, -0.452, -0.026]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.33) ** 2, (length * 0.03) ** 2, -((length * 0.05) ** 2), (length * 0.17) ** 2, -((length * 0.14) ** 2), (length * 0.33) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.31) ** 2, (length * 0.06) ** 2, (length * 0.05) ** 2, (length * 0.14) ** 2, (length * 0.02) ** 2, (length * 0.32) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "right_lowerarm": length = (0.1534 if gender == "f" else 0.1593) * height sgt_lengths["right_lowerarm_0"] = length dict_sgmt["mass"] = np.round( (0.013 if gender == "f" else 0.017) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([0.021, -0.411, 0.019]) if gender == "f" else np.array([0.01, -0.417, 0.014]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.26) ** 2, (length * 0.1) ** 2, (length * 0.04) ** 2, (length * 0.14) ** 2, -((length * 0.13) ** 2), (length * 0.25) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.28) ** 2, (length * 0.03) ** 2, (length * 0.02) ** 2, (length * 0.11) ** 2, -((length * 0.08) ** 2), (length * 0.27) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "right_hand": length = (0.0989 if gender == "f" else 0.1014) * height sgt_lengths["right_hand_0"] = length dict_sgmt["mass"] = np.round( (0.005 if gender == "f" else 0.006) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([0.077, -0.768, 0.048]) if gender == "f" else np.array([0.082, -0.839, 0.074]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.63) ** 2, (length * 0.29) ** 2, (length * 0.23) ** 2, (length * 0.43) ** 2, -((length * 0.28) ** 2), (length * 0.58) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.61) ** 2, (length * 0.22) ** 2, (length * 0.15) ** 2, (length * 0.38) ** 2, -((length * 0.2) ** 2), (length * 0.56) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "right_upperleg": length = (0.2354 if gender == "f" else 0.2441) * height sgt_lengths["right_upperleg_0"] = length dict_sgmt["mass"] = np.round( (0.146 if gender == "f" else 0.123) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.077, -0.377, 0.009]) if gender == "f" else np.array([-0.041, -0.429, 0.033]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.31) ** 2, -((length * 0.07) ** 2), -((length * 0.02) ** 2), (length * 0.19) ** 2, -((length * 0.07) ** 2), (length * 0.32) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.29) ** 2, -((length * 0.07) ** 2), -((length * 0.02) ** 2), (length * 0.15) ** 2, -((length * 0.07) ** 2), (length * 0.3) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "right_lowerleg": length = (0.2410 if gender == "f" else 0.2446) * height sgt_lengths["right_lowerleg_0"] = length dict_sgmt["mass"] = np.round( (0.045 if gender == "f" else 0.048) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([-0.049, -0.404, 0.031]) if gender == "f" else np.array([-0.048, -0.41, 0.007]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.28) ** 2, (length * 0.02) ** 2, (length * 0.01) ** 2, (length * 0.1) ** 2, (length * 0.06) ** 2, (length * 0.28) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.28) ** 2, (length * 0.04) ** 2, (length * 0.02) ** 2, (length * 0.1) ** 2, (length * 0.05) ** 2, (length * 0.28) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) elif name == "right_foot": length = (0.1447 if gender == "f" else 0.1497) * height sgt_lengths["right_foot_0"] = length dict_sgmt["mass"] = np.round( (0.01 if gender == "f" else 0.012) * weight, 2 ) dict_sgmt["com"] = np.round( ( np.array([0.27, -0.218, 0.039]) if gender == "f" else np.array([0.382, -0.151, 0.026]) ) * length, 3, ) dict_sgmt["inertia"] = np.round( ( np.array( [ (length * 0.17) ** 2, -((length * 0.10) ** 2), (length * 0.06) ** 2, (length * 0.36) ** 2, -((length * 0.04) ** 2), (length * 0.35) ** 2, ] ) if gender == "f" else np.array( [ (length * 0.17) ** 2, (length * 0.13) ** 2, -((length * 0.08) ** 2), (length * 0.37) ** 2, (length * 0) ** 2, (length * 0.36) ** 2, ] ) ) * dict_sgmt["mass"], 5, ) dicts.append(dict_sgmt) return dict(zip(inertial_segment_names, dicts)), sgt_lengths @staticmethod def get_dict_joint_placements(height: float, gender: str = "m") -> dict: joint_names = [ "middle_thoracic_Z", "middle_cervical_Z", "left_clavicle_joint_X", "right_clavicle_joint_X", "left_shoulder_Z", "left_elbow_Z", "left_wrist_Z", "right_shoulder_Z", "right_elbow_Z", "right_wrist_Z", "left_hip_Z", "left_knee_Z", "left_ankle_Z", "right_hip_Z", "right_knee_Z", "right_ankle_Z", ] lengths_names = [ "L_abdomen", "L_thorax_cerv", "L_thorax_supr", "L_upperarm", "L_lowerarm", "L_upperleg", "L_lowerleg", ] ratios = np.array( [ 0.1183 if gender == "f" else 0.1237, # L_abdomen MPT from XYP to OMPH (De Leva 1996) 0.1314 if gender == "f" else 0.1390, # L_thorax UPT from CERV to XYPH (De Leva 1996) 0.0821 if gender == "f" else 0.0980, # from SUPR to XYPH (De Leva 1996) 0.1510 if gender == "f" else 0.1531, # L_upperarm (Dumas 2007) 0.1534 if gender == "f" else 0.1593, # L_lowerarm (Dumas 2007) 0.2354 if gender == "f" else 0.2441, # L_upperleg (Dumas 2007) 0.2410 if gender == "f" else 0.2446, # L_lowerleg (Dumas 2007) ] ) # Ratios from De Leva : HJC from Seidel # SJC Schnorenberg-style AC/H = 0.132 (F) or 0.0129 (M) SJ_thorax_X_r = 0.0043 if gender == "f" else 0.0046 SJ_thorax_Y_r = -0.0449 if gender == "f" else -0.0416 SJ_thorax_Z_r = 0.1108 if gender == "f" else 0.1164 HJ_pelvis_X_r = 0.0138 if gender == "f" else 0.0126 HJ_pelvis_Y_r = -0.0570 if gender == "f" else -0.0558 HJ_pelvis_Z_r = 0.0548 if gender == "f" else 0.0457 lengths = np.round(ratios * height, 3) # mm accuracy dict_lengths = dict(zip(lengths_names, lengths)) joint_placements = [] for j in joint_names: if j == "middle_thoracic_Z": joint_placements.append(np.array([0, dict_lengths["L_abdomen"], 0])) elif j == "middle_cervical_Z": joint_placements.append(np.array([0, dict_lengths["L_thorax_cerv"], 0])) elif j == "left_clavicle_joint_X": joint_placements.append(np.array([0, dict_lengths["L_thorax_supr"], 0])) elif j == "right_clavicle_joint_X": joint_placements.append(np.array([0, dict_lengths["L_thorax_supr"], 0])) elif j == "left_shoulder_Z": joint_placements.append( np.round( height * np.array([SJ_thorax_X_r, SJ_thorax_Y_r, -SJ_thorax_Z_r]), 3, ) ) elif j == "left_elbow_Z": joint_placements.append(np.array([0, -dict_lengths["L_upperarm"], 0])) elif j == "left_wrist_Z": joint_placements.append(np.array([0, -dict_lengths["L_lowerarm"], 0])) elif j == "right_shoulder_Z": joint_placements.append( np.round( height * np.array([SJ_thorax_X_r, SJ_thorax_Y_r, SJ_thorax_Z_r]), 3, ) ) elif j == "right_elbow_Z": joint_placements.append(np.array([0, -dict_lengths["L_upperarm"], 0])) elif j == "right_wrist_Z": joint_placements.append(np.array([0, -dict_lengths["L_lowerarm"], 0])) elif j == "left_hip_Z": joint_placements.append( np.round( height * np.array([HJ_pelvis_X_r, HJ_pelvis_Y_r, -HJ_pelvis_Z_r]), 3, ) ) elif j == "left_knee_Z": joint_placements.append(np.array([0, -dict_lengths["L_upperleg"], 0])) elif j == "left_ankle_Z": joint_placements.append(np.array([0, -dict_lengths["L_lowerleg"], 0])) elif j == "right_hip_Z": joint_placements.append( np.round( height * np.array([HJ_pelvis_X_r, HJ_pelvis_Y_r, HJ_pelvis_Z_r]), 3, ) ) elif j == "right_knee_Z": joint_placements.append(np.array([0, -dict_lengths["L_upperleg"], 0])) elif j == "right_ankle_Z": joint_placements.append(np.array([0, -dict_lengths["L_lowerleg"], 0])) return dict(zip(joint_names, joint_placements)) @staticmethod def get_dict_meshes_scale( height: float, sgt_lengths: dict, gender: str = "m" ) -> dict: meshes_names = [ "middle_pelvis_0", "left_upperleg_0", "left_lowerleg_0", "left_lowerleg_1", "left_foot_0", "middle_abdomen_0", "middle_thorax_0", "middle_head_0", "middle_head_1", "left_upperarm_0", "left_upperarm_1", "left_lowerarm_0", "left_lowerarm_1", "left_hand_0", "right_upperarm_0", "right_upperarm_1", "right_lowerarm_0", "right_lowerarm_1", "right_hand_0", "right_upperleg_0", "right_lowerleg_0", "right_lowerleg_1", "right_foot_0", ] scales = [] for name in meshes_names: if ( name == "middle_pelvis_0" ): # pelvis mesh size is : X = 37.050m, Y = 32.551m, Z = 39.252m scale = np.round( np.array( [ 1.09 * sgt_lengths["middle_pelvis_0_width"] / 39.252, sgt_lengths["middle_pelvis_0_width"] / 39.252, sgt_lengths["middle_pelvis_0_width"] / 39.252, ] ), 4, ) scales.append(scale) elif ( name == "left_upperleg_0" ): # upperleg mesh size is : X = 20.977m, Y = 68.524m, Z = 20.977m scale = np.round( np.array( [ 0.96 * sgt_lengths["left_upperleg_0"] / 68.524, sgt_lengths["left_upperleg_0"] / 68.524, 1.08 * sgt_lengths["left_upperleg_0"] / 68.524, ] ), 4, ) scales.append(scale) elif ( name == "left_lowerleg_0" ): # lowerleg mesh size is : X = 17.986m, Y = 67m, Z = 17.977m scale = np.round( np.array( [ 0.96 * sgt_lengths["left_lowerleg_0"] / 67, sgt_lengths["left_lowerleg_0"] / 67, 1.07 * sgt_lengths["left_lowerleg_0"] / 67, ] ), 4, ) scales.append(scale) elif name == "left_lowerleg_1": # knee mesh is a sphere of 12.5m scale = np.round( np.array( [ 0.7 * (0.053 * height if gender == "f" else 0.056 * height) / 12.5, 0.7 * (0.053 * height if gender == "f" else 0.056 * height) / 12.5, 0.7 * (0.053 * height if gender == "f" else 0.056 * height) / 12.5, ] ), 4, ) scales.append(scale) elif ( name == "left_foot_0" ): # foot mesh size is : X = 40.5m, Y = 16.5m, Z = 17.999m scale = np.round( np.array( [ sgt_lengths["left_foot_0"] / 40.5, sgt_lengths["left_foot_0"] / 40.5, sgt_lengths["left_foot_0"] / 40.5, ] ), 4, ) scales.append(scale) elif name == "middle_abdomen_0": # abdomen meshis a sphere of radius 30 m scale = np.round( np.array( [ sgt_lengths["middle_abdomen_0"] / 30, sgt_lengths["middle_abdomen_0"] / 30, sgt_lengths["middle_abdomen_0"] / 30, ] ), 4, ) scales.append(scale) elif ( name == "middle_thorax_0" ): # torso mesh size is : X = 36.991m, Y = 35m, Z = 40.029m scale = np.round( np.array( [ sgt_lengths["middle_thorax_0"] / 35, sgt_lengths["middle_thorax_0"] / 35, sgt_lengths["middle_thorax_0"] / 35, ] ), 4, ) scales.append(scale) elif ( name == "middle_head_0" ): # head mesh size is : X = 32.049m, Y = 42m, Z = 32.049m scale = np.round( np.array( [ sgt_lengths["middle_head_0"] / 42, sgt_lengths["middle_head_0"] / 42, sgt_lengths["middle_head_0"] / 42, ] ), 4, ) scales.append(scale) elif name == "middle_head_1": # neck mesh scale = np.round( np.array( [ (0.078 * height if gender == "f" else 0.086 * height) / 31.0, (0.078 * height if gender == "f" else 0.086 * height) / 31.0, (0.078 * height if gender == "f" else 0.086 * height) / 31.0, ] ), 4, ) scales.append(scale) elif name == "left_upperarm_0": # shoulder mesh is a shpere of radius 17.5 scale = np.round( np.array( [ (0.037 * height if gender == "f" else 0.038 * height) / 17.5, (0.037 * height if gender == "f" else 0.038 * height) / 17.5, (0.037 * height if gender == "f" else 0.038 * height) / 17.5, ] ), 4, ) scales.append(scale) elif ( name == "left_upperarm_1" ): # upperarm mesh is of size : X = 17.158m, Y = 46m, Z = 17.183m scale = np.round( np.array( [ 1.05 * sgt_lengths["left_upperarm_0"] / 46, sgt_lengths["left_upperarm_0"] / 46, 1.16 * sgt_lengths["left_upperarm_0"] / 46, ] ), 4, ) scales.append(scale) elif ( name == "left_lowerarm_0" ): # lowerarm mesh is of size : X = 15.547m, Y = 45m, Z = 15.541m scale = np.round( np.array( [ sgt_lengths["left_lowerarm_0"] / 45, sgt_lengths["left_lowerarm_0"] / 45, sgt_lengths["left_lowerarm_0"] / 45, ] ), 4, ) scales.append(scale) elif name == "left_lowerarm_1": # elbow mesh is a sphere of radius 12.5 scale = np.round( np.array( [ (0.037 * height if gender == "f" else 0.038 * height) / 12.5, (0.037 * height if gender == "f" else 0.038 * height) / 12.5, (0.037 * height if gender == "f" else 0.038 * height) / 12.5, ] ), 4, ) scales.append(scale) elif ( name == "left_hand_0" ): # hand mesh is of size : X = 12.055m, Y = 30m, Z = 16.646m scale = np.round( np.array( [ sgt_lengths["left_hand_0"] / 30, sgt_lengths["left_hand_0"] / 30, sgt_lengths["left_hand_0"] / 30, ] ), 4, ) scales.append(scale) elif name == "right_upperarm_0": # shoulder mesh scale = np.round( np.array( [ (0.037 * height if gender == "f" else 0.038 * height) / 17.5, (0.037 * height if gender == "f" else 0.038 * height) / 17.5, (0.037 * height if gender == "f" else 0.038 * height) / 17.5, ] ), 4, ) scales.append(scale) elif name == "right_upperarm_1": # upperarm mesh scale = np.round( np.array( [ 1.05 * sgt_lengths["right_upperarm_0"] / 46, sgt_lengths["right_upperarm_0"] / 46, 1.16 * sgt_lengths["right_upperarm_0"] / 46, ] ), 4, ) scales.append(scale) elif name == "right_lowerarm_0": # lowerarm mesh scale = np.round( np.array( [ sgt_lengths["right_lowerarm_0"] / 45, sgt_lengths["right_lowerarm_0"] / 45, sgt_lengths["right_lowerarm_0"] / 45, ] ), 4, ) scales.append(scale) elif name == "right_lowerarm_1": # elbow mesh scale = np.round( np.array( [ (0.037 * height if gender == "f" else 0.038 * height) / 12.5, (0.037 * height if gender == "f" else 0.038 * height) / 12.5, (0.037 * height if gender == "f" else 0.038 * height) / 12.5, ] ), 4, ) scales.append(scale) elif name == "right_hand_0": # hand mesh scale = np.round( np.array( [ sgt_lengths["right_hand_0"] / 30, sgt_lengths["right_hand_0"] / 30, sgt_lengths["right_hand_0"] / 30, ] ), 4, ) scales.append(scale) elif name == "right_upperleg_0": # upperleg mesh scale = np.round( np.array( [ 0.96 * sgt_lengths["right_upperleg_0"] / 68.524, sgt_lengths["right_upperleg_0"] / 68.524, 1.08 * sgt_lengths["right_upperleg_0"] / 68.524, ] ), 4, ) scales.append(scale) elif name == "right_lowerleg_0": # lowerleg mesh scale = np.round( np.array( [ 0.96 * sgt_lengths["right_lowerleg_0"] / 67, sgt_lengths["right_lowerleg_0"] / 67, 1.07 * sgt_lengths["right_lowerleg_0"] / 67, ] ), 4, ) scales.append(scale) elif name == "right_lowerleg_1": # knee mesh scale = np.round( np.array( [ 0.7 * (0.053 * height if gender == "f" else 0.056 * height) / 12.5, 0.7 * (0.053 * height if gender == "f" else 0.056 * height) / 12.5, 0.7 * (0.053 * height if gender == "f" else 0.056 * height) / 12.5, ] ), 4, ) scales.append(scale) elif name == "right_foot_0": # foot mesh scale = np.round( np.array( [ sgt_lengths["right_foot_0"] / 40.5, sgt_lengths["right_foot_0"] / 40.5, sgt_lengths["right_foot_0"] / 40.5, ] ), 4, ) scales.append(scale) return dict(zip(meshes_names, scales)) def _scale_pin_model( self, model: pin.Model, visual_model: pin.GeometryModel, height: float, weight: float, gender: str = "m", ) -> None: """ Overwrite model.inertias, model.jointPlacements, and model.geometryObjects.meshScale based on anthropometry. """ # compute parameters joints = self.get_dict_joint_placements(height, gender) inert, sgt_lengths = self.get_dict_inertial_param(height, weight, gender) scales = self.get_dict_meshes_scale(height, sgt_lengths, gender) # apply inertias for seg, P in inert.items(): b_id = model.frames[model.getFrameId(seg)].parentJoint Ixx, Ixy, Ixz, Iyy, Iyz, Izz = P["inertia"] I_mat = np.array([[Ixx, Ixy, Ixz], [Ixy, Iyy, Iyz], [Ixz, Iyz, Izz]]) model.inertias[b_id] = pin.Inertia(P["mass"], P["com"], I_mat) # apply joint placements for j, pos in joints.items(): j_id = model.getJointId(j) M = model.jointPlacements[j_id] M.translation = pos model.jointPlacements[j_id] = M # scale visuals assert len(visual_model.geometryObjects.tolist()) == len(scales) for geom_obj in visual_model.geometryObjects: geom_obj.meshScale = scales[geom_obj.name]