def reset(self):
#if self.state == feb.RUN:
if self.state is None:
return FurutaEnvTorqueDeepq.reset(self, position=0, velocity=0)
# position 0rad is upright
return FurutaEnvTorqueDeepq.reset(
self,
position=cm.sgn() *
np.random.uniform(0, cm.deg2Rad(cm.ANGLE_TERMINAL_MIN_D)),
#position=cm.sgn()*cm.deg2Rad(feb.ANGLE_TERMINAL_MIN_D),
velocity=cm.sgn() * np.random.uniform(0, cm.VEL_MAX_POLE),
arm_vel=cm.sgn() * np.random.uniform(0, cm.VEL_MAX_ARM))
def reset(self):
# position 0rad is upright
return FurutaEnvTorqueDeepq.reset(
self,
#position=cm.sgn()*np.random.uniform(cm.deg2Rad(feb.ANGLE_TERMINAL_MIN_D), 2*feb.PI),
#velocity=cm.sgn()*np.random.uniform(0, feb.VEL_MAX_POLE),
#arm_vel=cm.sgn()*np.random.uniform(0, feb.VEL_MAX_ARM)
# start in the spin we never want to see
position=cm.sgn() *
np.random.uniform(cm.deg2Rad(cm.ANGLE_TERMINAL_MAX_D),
2 * cm.deg2Rad(cm.ANGLE_TERMINAL_MAX_D)),
#position=cm.sgn()*feb.PI,
velocity=cm.sgn() * np.random.uniform(0, cm.VEL_MAX_POLE),
arm_vel=cm.sgn() * np.random.uniform(0, cm.VEL_MAX_ARM))
def reset(self):
# position 0rad is upright
if False: #self.state == feb.RUN:
return FurutaEnvPosTrpo.reset(self,
position=cm.deg2Rad(
cm.ANGLE_TERMINAL_MIN_D / 2),
velocity=0,
arm_vel=0)
return FurutaEnvPosTrpo.reset(
self,
position=cm.sgn() *
np.random.uniform(0, cm.deg2Rad(cm.ANGLE_TERMINAL_MIN_D)),
velocity=cm.sgn() * np.random.uniform(0, cm.VEL_MAX_POLE),
arm_vel=cm.sgn() * np.random.uniform(0, cm.VEL_MAX_ARM))
def haze(self):
if abs(self.pole_angle_real) > cm.deg2Rad(cm.ANGLE_TERMINAL_MAX_D):
return
velocity = 0
if cm.TRAIN == self.state and POS_HAZE == cm.TRAIN:
if self._envStepCounter % 500 == 0:
velocity = cm.sgn() * np.random.uniform(0,
cm.VEL_MAX_POLE) * 0.3
if cm.RUN == self.state and POS_HAZE == cm.RUN:
if self._envStepCounter % 500 == 0:
velocity = cm.sgn() * cm.VEL_MAX_POLE * 0.2
if 0 != velocity:
p.setJointMotorControl2(bodyUniqueId=self.botId,
jointIndex=self.poleId,
controlMode=p.VELOCITY_CONTROL,
targetVelocity=self.pole_vel_real +
velocity)
def randTraj(action):
if np.random.uniform(0, 1) > 0.0:
action += cm.sgn() * round(np.random.uniform(0, 1)**3 * 4, 0)
action = cm.clamp(action, 0, len(action_table) - 1)
return int(action)