from robot_bases import MJCFBasedRobot import numpy as np class WalkerBase(MJCFBasedRobot): def __init__(self, fn, robot_name, action_dim, obs_dim, power): MJCFBasedRobot.__init__(self, fn, robot_name, action_dim, obs_dim) self.power = power self.camera_x = 0 self.walk_target_x = 1e3 # kilometer away self.walk_target_y = 0 self.body_xyz=[0,0,0] def robot_specific_reset(self): for j in self.ordered_joints: j.reset_current_position(self.np_random.uniform(low=-0.1, high=0.1), 0) self.feet = [self.parts[f] for f in self.foot_list] self.feet_contact = np.array([0.0 for f in self.foot_list], dtype=np.float32) self.scene.actor_introduce(self) self.initial_z = None def apply_action(self, a): assert (np.isfinite(a).all()) for n, j in enumerate(self.ordered_joints): j.set_motor_torque(self.power * j.power_coef * float(np.clip(a[n], -1, +1))) def calc_state(self): j = np.array([j.current_relative_position() for j in self.ordered_joints], dtype=np.float32).flatten() # even elements [0::2] position, scaled to -1..+1 between limits # odd elements [1::2] angular speed, scaled to show -1..+1 self.joint_speeds = j[1::2] self.joints_at_limit = np.count_nonzero(np.abs(j[0::2]) > 0.99) body_pose = self.robot_body.pose() parts_xyz = np.array([p.pose().xyz() for p in self.parts.values()]).flatten() self.body_xyz = ( parts_xyz[0::3].mean(), parts_xyz[1::3].mean(), body_pose.xyz()[2]) # torso z is more informative than mean z self.body_rpy = body_pose.rpy() z = self.body_xyz[2] if self.initial_z == None: self.initial_z = z r, p, yaw = self.body_rpy self.walk_target_theta = np.arctan2(self.walk_target_y - self.body_xyz[1], self.walk_target_x - self.body_xyz[0]) self.walk_target_dist = np.linalg.norm( [self.walk_target_y - self.body_xyz[1], self.walk_target_x - self.body_xyz[0]]) angle_to_target = self.walk_target_theta - yaw rot_speed = np.array( [[np.cos(-yaw), -np.sin(-yaw), 0], [np.sin(-yaw), np.cos(-yaw), 0], [ 0, 0, 1]] ) vx, vy, vz = np.dot(rot_speed, self.robot_body.speed()) # rotate speed back to body point of view more = np.array([ z-self.initial_z, np.sin(angle_to_target), np.cos(angle_to_target), 0.3* vx , 0.3* vy , 0.3* vz , # 0.3 is just scaling typical speed into -1..+1, no physical sense here r, p], dtype=np.float32) return np.clip( np.concatenate([more] + [j] + [self.feet_contact]), -5, +5) def calc_potential(self): # progress in potential field is speed*dt, typical speed is about 2-3 meter per second, this potential will change 2-3 per frame (not per second), # all rewards have rew/frame units and close to 1.0 debugmode=0 if (debugmode): print("calc_potential: self.walk_target_dist") print(self.walk_target_dist) print("self.scene.dt") print(self.scene.dt) print("self.scene.frame_skip") print(self.scene.frame_skip) print("self.scene.timestep") print(self.scene.timestep) return - self.walk_target_dist / self.scene.dt class Hopper(WalkerBase): foot_list = ["foot"] def __init__(self): WalkerBase.__init__(self, "hopper.xml", "torso", action_dim=3, obs_dim=15, power=0.75) def alive_bonus(self, z, pitch): return +1 if z > 0.8 and abs(pitch) < 1.0 else -1 class Walker2D(WalkerBase): foot_list = ["foot", "foot_left"] def __init__(self): WalkerBase.__init__(self, "walker2d.xml", "torso", action_dim=6, obs_dim=22, power=0.40) def alive_bonus(self, z, pitch): return +1 if z > 0.8 and abs(pitch) < 1.0 else -1 def robot_specific_reset(self): WalkerBase.robot_specific_reset(self) for n in ["foot_joint", "foot_left_joint"]: self.jdict[n].power_coef = 30.0 class HalfCheetah(WalkerBase): foot_list = ["ffoot", "fshin", "fthigh", "bfoot", "bshin", "bthigh"] # track these contacts with ground def __init__(self): WalkerBase.__init__(self, "half_cheetah.xml", "torso", action_dim=6, obs_dim=26, power=0.90) def alive_bonus(self, z, pitch): # Use contact other than feet to terminate episode: due to a lot of strange walks using knees return +1 if np.abs(pitch) < 1.0 and not self.feet_contact[1] and not self.feet_contact[2] and not self.feet_contact[4] and not self.feet_contact[5] else -1 def robot_specific_reset(self): WalkerBase.robot_specific_reset(self) self.jdict["bthigh"].power_coef = 120.0 self.jdict["bshin"].power_coef = 90.0 self.jdict["bfoot"].power_coef = 60.0 self.jdict["fthigh"].power_coef = 140.0 self.jdict["fshin"].power_coef = 60.0 self.jdict["ffoot"].power_coef = 30.0 class Ant(WalkerBase): foot_list = ['front_left_foot', 'front_right_foot', 'left_back_foot', 'right_back_foot'] def __init__(self): WalkerBase.__init__(self, "ant.xml", "torso", action_dim=8, obs_dim=28, power=2.5) def alive_bonus(self, z, pitch): return +1 if z > 0.26 else -1 # 0.25 is central sphere rad, die if it scrapes the ground class Humanoid(WalkerBase): self_collision = True foot_list = ["right_foot", "left_foot"] # "left_hand", "right_hand" def __init__(self): WalkerBase.__init__(self, 'humanoid_symmetric.xml', 'torso', action_dim=17, obs_dim=44, power=0.41) # 17 joints, 4 of them important for walking (hip, knee), others may as well be turned off, 17/4 = 4.25 def robot_specific_reset(self): WalkerBase.robot_specific_reset(self) self.motor_names = ["abdomen_z", "abdomen_y", "abdomen_x"] self.motor_power = [100, 100, 100] self.motor_names += ["right_hip_x", "right_hip_z", "right_hip_y", "right_knee"] self.motor_power += [100, 100, 300, 200] self.motor_names += ["left_hip_x", "left_hip_z", "left_hip_y", "left_knee"] self.motor_power += [100, 100, 300, 200] self.motor_names += ["right_shoulder1", "right_shoulder2", "right_elbow"] self.motor_power += [75, 75, 75] self.motor_names += ["left_shoulder1", "left_shoulder2", "left_elbow"] self.motor_power += [75, 75, 75] self.motors = [self.jdict[n] for n in self.motor_names] if self.random_yaw: position = [0,0,0] orientation = [0,0,0] yaw = self.np_random.uniform(low=-3.14, high=3.14) if self.random_lean and self.np_random.randint(2)==0: cpose.set_xyz(0, 0, 1.4) if self.np_random.randint(2)==0: pitch = np.pi/2 position = [0, 0, 0.45] else: pitch = np.pi*3/2 position = [0, 0, 0.25] roll = 0 orientation = [roll, pitch, yaw] else: position = [0, 0, 1.4] orientation = [0, 0, yaw] # just face random direction, but stay straight otherwise self.robot_body.reset_position(position) self.robot_body.reset_orientation(orientation) self.initial_z = 0.8 random_yaw = False random_lean = False def apply_action(self, a): assert( np.isfinite(a).all() ) force_gain = 1 for i, m, power in zip(range(17), self.motors, self.motor_power): m.set_motor_torque( float(force_gain * power*self.power*a[i]) ) #m.set_motor_torque(float(force_gain * power * self.power * np.clip(a[i], -1, +1))) def alive_bonus(self, z, pitch): return +2 if z > 0.78 else -1 # 2 here because 17 joints produce a lot of electricity cost just from policy noise, living must be better than dying