skrobot.sdf.UnionSDF¶

class skrobot.sdf.UnionSDF(sdf_list, coords=None)[source]¶

One can concat multiple SDFs sdf_list by using this class.

For consistency in the concatenation, it is required that the all SDFs to be concated are with use_abs=False.

Methods

__call__(points_obj)[source]¶

Compute signed distances of input points to the implicit surface.

Parameters:: points_obj (numpy.ndarray[float](n_point, 3)) – 2 dim point array w.r.t. object coordinate.
Returns:: signed_distances – 1 dim (n_point,) array of signed distance.
Return type:: numpy.ndarray[float]

classmethod from_robot_model(robot_model, dim_grid=50)[source]¶

Create union sdf from a robot model

Parameters:: robot_model (skrobot.model.RobotModel) – Using the links of the robot_model this creates the UnionSDF instance.
Returns:: union_sdf – union sdf of robot_model
Return type:: skrobot.sdf.UnionSDF

on_surface(points_obj)[source]¶

Check if points are on the surface.

Parameters:

points_obj (numpy.ndarray[float](n_point, 3)) – 2 dim point array w.r.t. an object coordinate.

Returns:

logicals (numpy.ndarray[bool](n_point,)) – boolean vector of the on-surface predicate for points_obj.
sd_vals (numpy.ndarray[float](n_point,)) – signed distances corresponding to logicals.

surface_points(n_sample=1000)[source]¶

Sample points from the implicit surface of the sdf.

Parameters:

n_sample (int) – number of sample points.

Returns:

points_obj (numpy.ndarray[float](n_point, 3)) – sampled points w.r.t object coordinate.
dists (numpy.ndarray[float](n_point,)) – signed distances corresponding to points_obj.