SplineOptimizationParameters Struct Reference

#include <spline_trajectory.hpp>

Public Member Functions
	SplineOptimizationParameters (const Eigen::Index num_dims_in)

Public Attributes
const Eigen::Index	num_dims = 0
	Number of dimensions for the spline optimization.
double	weight_velocity = 10.0
	Weight for the velocity term in the cost function.
double	weight_acceleration = 1.0
	Weight for the acceleration term in the cost function.
double	weight_jerk = 0.0
	Weight for the jerk term in the cost function.
bool	soft_position = false
	Whether each point's position is fit with a least-squares penalty instead of a hard interpolation constraint.
double	weight_position = 100.0
	Least-squares weight pulling each point toward its target position when soft_position is true. Ignored otherwise. Larger values track the points more closely; smaller values smooth more. Callers may override this default for their workload (the chunked trajectory executor does).
Eigen::VectorNd	end_acceleration
	Desired end acceleration for each dimension.
Eigen::VectorNd	end_velocity
	Desired end velocity for each dimension.
Eigen::VectorNd	start_acceleration
	Desired start acceleration for each dimension.
Eigen::VectorNd	start_velocity
	Desired start velocity for each dimension.
double	constraint_norm_tolerance = 1E-6
	Tolerance for the norm of the constraint violations.
Eigen::VectorNd	velocity_limits
	Velocity limits for each dimension, used to enforce dynamic constraints during spline optimization.
Eigen::VectorNd	acceleration_limits
	Acceleration limits for each dimension, used to enforce dynamic constraints during spline optimization.
double	dt = 0.1
	The discrete timestep used for sampling to detect constraint violations in seconds.

Constructor & Destructor Documentation

SplineOptimizationParameters()

SplineOptimizationParameters::SplineOptimizationParameters ( const Eigen::Index  num_dims_in )

inlineexplicit

Member Data Documentation

acceleration_limits

Eigen::VectorNd SplineOptimizationParameters::acceleration_limits

Acceleration limits for each dimension, used to enforce dynamic constraints during spline optimization.

constraint_norm_tolerance

double SplineOptimizationParameters::constraint_norm_tolerance = 1E-6

Tolerance for the norm of the constraint violations.

dt

double SplineOptimizationParameters::dt = 0.1

The discrete timestep used for sampling to detect constraint violations in seconds.

end_acceleration

Eigen::VectorNd SplineOptimizationParameters::end_acceleration

Desired end acceleration for each dimension.

end_velocity

Eigen::VectorNd SplineOptimizationParameters::end_velocity

Desired end velocity for each dimension.

num_dims

const Eigen::Index SplineOptimizationParameters::num_dims = 0

Number of dimensions for the spline optimization.

soft_position

bool SplineOptimizationParameters::soft_position = false

Whether each point's position is fit with a least-squares penalty instead of a hard interpolation constraint.

When false (default), the spline passes exactly through every point. When true it becomes a smoothing spline: the curve may deviate from a jittery input to lower its velocity, acceleration, and jerk, since every point after the first is only pulled toward its target position (see weight_position) rather than matched exactly. Still held exactly: the first point's position, position continuity at the interior knots, velocity and acceleration continuity, and the start and end velocity and acceleration boundary conditions.

start_acceleration

Eigen::VectorNd SplineOptimizationParameters::start_acceleration

Desired start acceleration for each dimension.

start_velocity

Eigen::VectorNd SplineOptimizationParameters::start_velocity

Desired start velocity for each dimension.

velocity_limits

Eigen::VectorNd SplineOptimizationParameters::velocity_limits

Velocity limits for each dimension, used to enforce dynamic constraints during spline optimization.

weight_acceleration

double SplineOptimizationParameters::weight_acceleration = 1.0

Weight for the acceleration term in the cost function.

weight_jerk

double SplineOptimizationParameters::weight_jerk = 0.0

Weight for the jerk term in the cost function.

weight_position

double SplineOptimizationParameters::weight_position = 100.0

Least-squares weight pulling each point toward its target position when soft_position is true. Ignored otherwise. Larger values track the points more closely; smaller values smooth more. Callers may override this default for their workload (the chunked trajectory executor does).

weight_velocity

double SplineOptimizationParameters::weight_velocity = 10.0

Weight for the velocity term in the cost function.

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The documentation for this struct was generated from the following file:

• spline_trajectory.hpp