(
    robot: typing.Any,
    link_id: int,
)
return jacobian
Computes the Jacobian matrix for the given link.

  Args:
    robot: A robot instance.
    link_id: The link id as returned from loadURDF.

  Returns:
    The 3 x N transposed Jacobian matrix. where N is the total DoFs of the
    robot. For a quadruped, the first 6 columns of the matrix corresponds to
    the CoM translation and rotation. The columns corresponds to a leg can be
    extracted with indices [6 + leg_id * 3: 6 + leg_id * 3 + 3].
Computes the Jacobian matrix for the given link.
Computes the Jacobian matrix for the given link .
def compute_jacobian(
    robot: typing.Any,
    link_id: int,
):
  """Computes the Jacobian matrix for the given link.

  Args:
    robot: A robot instance.
    link_id: The link id as returned from loadURDF.

  Returns:
    The 3 x N transposed Jacobian matrix. where N is the total DoFs of the
    robot. For a quadruped, the first 6 columns of the matrix corresponds to
    the CoM translation and rotation. The columns corresponds to a leg can be
    extracted with indices [6 + leg_id * 3: 6 + leg_id * 3 + 3].
  """

  all_joint_angles = [state[0] for state in robot.joint_states]
  zero_vec = [0] * len(all_joint_angles)
  jv, _ = robot.pybullet_client.calculateJacobian(robot.quadruped, link_id,
                                                  (0, 0, 0), all_joint_angles,
                                                  zero_vec, zero_vec)
  jacobian = np.array(jv)
  return jacobian
def compute_jacobian ( robot : typing . Any , link_id : int , ) : all_joint_angles = [ state [ 0 ] for state in robot . joint_states ] zero_vec = [ 0 ] * len ( all_joint_angles ) jv , _ = robot . pybullet_client . calculateJacobian ( robot . quadruped , link_id , ( 0 , 0 , 0 ) , all_joint_angles , zero_vec , zero_vec ) jacobian = np . array ( jv ) return jacobian