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J-PARSE API Reference

jparse.JParseCore

Pure J-PARSE algorithm. Only requires numpy.

solver = jparse.JParseCore(gamma=0.1)
Parameter Type Default Description
gamma float 0.1 Singularity threshold (0 < gamma < 1). Directions with σᵢ/σₘₐₓ < gamma are treated as singular.

solver.compute(jacobian, ...)

Compute the J-PARSE pseudo-inverse of a Jacobian matrix.

J_parse = solver.compute(J)
J_parse, nullspace = solver.compute(J, return_nullspace=True)
Parameter Type Default Description
jacobian ndarray required m × n Jacobian matrix
singular_direction_gain_position float 1.0 Gain for position singular directions
singular_direction_gain_angular float 1.0 Gain for angular singular directions
position_dimensions int None Number of position rows (e.g., 3 for 3D)
angular_dimensions int None Number of angular rows (e.g., 3 for 3D)
return_nullspace bool False Also return nullspace projection matrix

Returns:

  • J_parse (ndarray): n × m J-PARSE pseudo-inverse matrix
  • nullspace (ndarray, optional): n × n nullspace projection matrix

solver.pinv(jacobian)

Standard Moore-Penrose pseudo-inverse (for comparison).

Returns: n × m pseudo-inverse matrix

solver.damped_least_squares(jacobian, damping=0.01)

Damped least squares pseudo-inverse (for comparison).

Parameter Type Default Description
jacobian ndarray required m × n Jacobian matrix
damping float 0.01 Damping factor λ

Returns: n × m DLS pseudo-inverse matrix

jparse.Robot

High-level robot interface with URDF support (requires Pinocchio).

robot = jparse.Robot.from_urdf("robot.urdf", "base_link", "ee_link", gamma=0.1)
Parameter Type Default Description
urdf str required Path to URDF file or XML string
base_link str required Name of base link
end_link str required Name of end-effector link
gamma float 0.1 J-PARSE singularity threshold

Properties

Property Type Description
num_joints int Number of actuated joints
gamma float Current singularity threshold (settable)

robot.jacobian(q)

Compute the 6 × n geometric Jacobian.

Returns: 6 × n Jacobian matrix (rows 0-2: linear, rows 3-5: angular)

robot.jparse(q, ...)

Compute J-PARSE pseudo-inverse at configuration q.

J_parse = robot.jparse(q)
J_parse = robot.jparse(q, position_only=True)  # 3D position only
J_parse, nullspace = robot.jparse(q, return_nullspace=True)
Parameter Type Default Description
q ndarray required Joint configuration
position_only bool False Use only position rows (3×n)
return_nullspace bool False Also return nullspace matrix
singular_direction_gain_position float 1.0 Position gain
singular_direction_gain_angular float 1.0 Angular gain

Returns: J-PARSE pseudo-inverse (and optionally nullspace)

robot.forward_kinematics(q)

Compute end-effector pose.

Returns: (position, rotation) - 3D position and 3×3 rotation matrix

robot.manipulability(q)

Compute Yoshikawa's manipulability measure: √det(JJᵀ)

Returns: float (higher = better conditioned)

robot.inverse_condition_number(q)

Compute σₘᵢₙ/σₘₐₓ of the Jacobian.

Returns: float in [0, 1] (0 = singular, 1 = isotropic)

Utility Functions

# Manipulability measure
m = jparse.manipulability_measure(J)  # √det(JJᵀ)

# Inverse condition number
icn = jparse.inverse_condition_number(J)  # σₘᵢₙ/σₘₐₓ

ROS Integration

from jparse_robotics.ros import ROSRobot

robot = ROSRobot.from_parameter_server("base_link", "ee_link", gamma=0.1)
robot.publish_ellipsoids(q, end_effector_pose)  # Visualize in RViz