Python APIΒΆ

cuRobo provides accelerated modules for robotics which can be used to build high-performance robotics applications. The library has several modules for numerical optimization, robot kinematics, geometry processing, collision checking, graph search planning. cuRobo provides high-level APIs for performing tasks like collision-free inverse kinematics, model predictive control, and motion planning.

Public API Quick Start:

from curobo.inverse_kinematics import InverseKinematics, InverseKinematicsCfg
from curobo.trajectory_optimizer import TrajectoryOptimizer, TrajectoryOptimizerCfg
from curobo.motion_planner import MotionPlanner, MotionPlannerCfg
from curobo.model_predictive_control import ModelPredictiveControl, ModelPredictiveControlCfg
from curobo.kinematics import Kinematics, KinematicsCfg
from curobo.scene import Scene, Cuboid, Sphere, Mesh
from curobo.types import JointState

# Forward kinematics
kin = Kinematics(KinematicsCfg.from_robot_yaml_file("franka.yml"))
js = JointState.from_position(q, joint_names=kin.joint_names)
state = kin.compute_kinematics(js)

# Scene representation
scene = Scene(
    cuboid=[Cuboid(name="table", dims=[1, 1, 0.1], pose=[0, 0, 0.5, 1, 0, 0, 0])],
)

# Inverse kinematics
ik_config = InverseKinematicsCfg.create(robot="franka.yml")
ik = InverseKinematics(ik_config)
result = ik.solve_pose(goal_tool_poses=target_poses)

# Trajectory optimization
trajopt = TrajectoryOptimizer(trajopt_config)
trajectory = trajopt.solve_pose(goal_tool_poses=target_poses)

# Model predictive control
mpc = ModelPredictiveControl(mpc_config)
result = mpc.optimize_action_sequence(current_state)

Public API Modules: