def __init__(self, config):
self.config = config
self.velocity = config.get("velocity", 1.0)
LocomotorRobot.__init__(self,
"turtlebot/turtlebot.urdf",
action_dim=2,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control="velocity")
def __init__(self, config):
self.config = config
self.velocity = config.get('velocity', 1.0)
LocomotorRobot.__init__(self,
"jr2_urdf/jr2.urdf",
action_dim=4,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", True),
control='velocity')
def __init__(self, config):
self.config = config
self.torque = config.get("torque", 0.03)
LocomotorRobot.__init__(self,
"husky/husky.urdf",
action_dim=4,
torque_coef=2.5,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control="torque")
def __init__(self, config):
self.config = config
self.torque = config.get("torque", 1.0)
LocomotorRobot.__init__(
self,
"ant/ant.xml",
action_dim=8,
torque_coef=2.5,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control="torque",
)
def __init__(self, config):
self.config = config
self.wheel_velocity = config.get('wheel_velocity', 0.3)
self.wheel_dim = 2
self.arm_velocity = config.get('arm_velocity', 1.0)
self.arm_dim = 5
LocomotorRobot.__init__(self,
"jr2_urdf/jr2_kinova.urdf",
action_dim=self.wheel_dim + self.arm_dim,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control='velocity',
self_collision=True)
def __init__(self, config):
self.config = config
self.torque = config.get("torque", 0.1)
self.glass_id = None
self.glass_offset = 0.3
LocomotorRobot.__init__(
self,
"humanoid/humanoid.xml",
action_dim=17,
torque_coef=0.41,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control="torque",
self_collision=True,
)
def __init__(self, config):
self.config = config
self.wheel_velocity = config.get('wheel_velocity', 1.0)
self.torso_lift_velocity = config.get('torso_lift_velocity', 1.0)
self.arm_velocity = config.get('arm_velocity', 1.0)
self.wheel_dim = 2
self.torso_lift_dim = 1
self.arm_dim = 7
LocomotorRobot.__init__(self,
"fetch/fetch.urdf",
action_dim=self.wheel_dim +
self.torso_lift_dim + self.arm_dim,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control="velocity",
self_collision=True)
def __init__(self, config):
self.config = config
# https://www.trossenrobotics.com/locobot-pyrobot-ros-rover.aspx
# Maximum translational velocity: 70 cm/s
# Maximum rotational velocity: 180 deg/s (>110 deg/s gyro performance will degrade)
self.linear_velocity = config.get('linear_velocity', 0.5)
self.angular_velocity = config.get('angular_velocity', np.pi / 2.0)
self.wheel_dim = 2
self.wheel_axle_half = 0.115 # half of the distance between the wheels
self.wheel_radius = 0.038 # radius of the wheels
LocomotorRobot.__init__(self,
"locobot/locobot.urdf",
base_name="base_link",
action_dim=self.wheel_dim,
scale=config.get("robot_scale", 1.0),
is_discrete=config.get("is_discrete", False),
control="differential_drive")
def __init__(self, config, env=None, pd_control_enabled=True,
accurate_motor_model_enabled=True):
"""Constructs a minitaur and reset it to the initial states.
Properties:
self_collision_enabled: Whether to enable self collision.
motor_velocity_limit: The upper limit of the motor velocity.
pd_control_enabled: Whether to use PD control for the motors. If true, need smaller time step to stablize (1/500.0 timestep)
accurate_motor_model_enabled: Whether to use the accurate DC motor model.
motor_kp: proportional gain for the accurate motor model
motor_kd: derivative gain for the acurate motor model
torque_control_enabled: Whether to use the torque control, if set to
False, pose control will be used.
motor_overheat_protection: Whether to shutdown the motor that has exerted
large torque (OVERHEAT_SHUTDOWN_TORQUE) for an extended amount of time
(OVERHEAT_SHUTDOWN_TIME). See apply_action() in minitaur_robot.py for more
details.
on_rack: Whether to place the minitaur on rack. This is only used to debug
the walking gait. In this mode, the minitaur's base is hanged midair so
that its walking gait is clearer to visualize.
kd_for_pd_controllers: kd value for the pd controllers of the motors.
"""
self.config = config
self.model_type = "URDF"
#self.robot_name = "quadruped"
self.robot_name = "base_chassis_link"
scale = config["robot_scale"] if "robot_scale" in config.keys(
) else self.default_scale
LocomotorRobot.__init__(self,
"quadruped/minitaur.urdf",
self.robot_name,
action_dim=8,
sensor_dim=self.OBSERVATION_DIM,
power=5,
scale=scale,
initial_pos=config['initial_pos'],
target_pos=config["target_pos"],
resolution=config["resolution"],
env=env)
self.r_f = 0.1
self.time_step = config["speed"]["timestep"]
self.pd_control_enabled = pd_control_enabled
self.minitaur = None # TODO: fix this
self.accurate_motor_model_enabled = accurate_motor_model_enabled
if self.accurate_motor_model_enabled:
self._kp = self.motor_kp
self._kd = self.motor_kd
self._motor_model = motor.MotorModel(torque_control_enabled=self.torque_control_enabled,
kp=self._kp,
kd=self._kd)
elif self.pd_control_enabled:
self._kp = 8
self._kd = self.kd_for_pd_controllers
else:
self._kp = 1
self._kd = 1
if config["is_discrete"]:
self.action_space = gym.spaces.Discrete(17)
self.torque = 10
## Hip_1, Ankle_1, Hip_2, Ankle_2, Hip_3, Ankle_3, Hip_4, Ankle_4
self.action_list = [[self.r_f * self.torque, 0, 0, 0, 0, 0, 0, 0],
[0, self.r_f * self.torque, 0, 0, 0, 0, 0, 0],
[0, 0, self.r_f * self.torque, 0, 0, 0, 0, 0],
[0, 0, 0, self.r_f * self.torque, 0, 0, 0, 0],
[0, 0, 0, 0, self.r_f * self.torque, 0, 0, 0],
[0, 0, 0, 0, 0, self.r_f * self.torque, 0, 0],
[0, 0, 0, 0, 0, 0, self.r_f * self.torque, 0],
[0, 0, 0, 0, 0, 0, 0, self.r_f * self.torque],
[-self.r_f * self.torque, 0, 0, 0, 0, 0, 0, 0],
[0, -self.r_f * self.torque, 0, 0, 0, 0, 0, 0],
[0, 0, -self.r_f * self.torque, 0, 0, 0, 0, 0],
[0, 0, 0, -self.r_f * self.torque, 0, 0, 0, 0],
[0, 0, 0, 0, -self.r_f * self.torque, 0, 0, 0],
[0, 0, 0, 0, 0, -self.r_f * self.torque, 0, 0],
[0, 0, 0, 0, 0, 0, -self.r_f * self.torque, 0],
[0, 0, 0, 0, 0, 0, 0, -self.r_f * self.torque],
[0, 0, 0, 0, 0, 0, 0, 0]]
self.setup_keys_to_action()
self.debug_count = 0
self.qmax = [0] * 8
self.fmax = [0] * 8