This is a simple constant velocity motion model. More...

#include <constant_velocity.hpp>

Inheritance diagram for autoware::motion::motion_model::ConstantVelocity:

Collaboration diagram for autoware::motion::motion_model::ConstantVelocity:

Classes
struct	States
	This state gives named handles for state indexing. More...

Public Member Functions
ConstantVelocity &	operator= (const ConstantVelocity &rhs)
	Default assignment operator. More...

void	predict (Eigen::Matrix< float32_t, 4U, 1U > &x, const std::chrono::nanoseconds &dt) const override
	Do motion based on current state, store result somewhere else. This is intended to be used with motion planning/collision avoidance i.e. to make multiple calls to predict with different time deltas for a rollout to get a concrete representation of predicted trajectories. This function does not mutate the core state of the motion model, and should only mutate some cached worker variables at most. More...

void	predict (const std::chrono::nanoseconds &dt) override
	Update current state with a given motion. Note that this should be called after compute_jacobian() as it will change the object's state. This is meant to be called before doing assignment and observation updating. This is the equivalent of temporal update for the state. This function mutates the core state of the motion model. More...

void	compute_jacobian (Eigen::Matrix< float32_t, 4U, 4U > &F, const std::chrono::nanoseconds &dt) override
	Compute the jacobian based on the current state and store the result somewhere else. More...

void	compute_jacobian_and_predict (Eigen::Matrix< float32_t, 4U, 4U > &F, const std::chrono::nanoseconds &dt) override
	This is called by Esrcf. This should be first a computation of the jacobian, and then a motion to update the state. This is a distinct function because depending on the motion model, there is some caching and optimization that can be done computing both the motion and jacobian together. More...

float32_t	operator[] (const index_t idx) const override
	Get elements of the model's state. More...

void	reset (const Eigen::Matrix< float32_t, 4U, 1U > &x) override
	Set the state. More...

const Eigen::Matrix< float32_t, 4U, 1U > &	get_state () const override
	const access to internal state More...

Public Member Functions inherited from autoware::motion::motion_model::MotionModel< 4U >
virtual void	predict (Eigen::Matrix< float32_t, NumStates, 1U > &x, const std::chrono::nanoseconds &dt) const=0
	Do motion based on current state, store result somewhere else. This is intended to be used with motion planning/collision avoidance, i.e. to make multiple calls to predict with different time deltas for a rollout to get a concrete representation of predicted trajectories. This function does not mutate the core state of the motion model, and should only mutate some cached worker variables at most. More...

virtual void	compute_jacobian (Eigen::Matrix< float32_t, NumStates, NumStates > &F, const std::chrono::nanoseconds &dt)=0
	Compute the jacobian based on the current state and store the result somewhere else. More...

virtual void	compute_jacobian_and_predict (Eigen::Matrix< float32_t, NumStates, NumStates > &F, const std::chrono::nanoseconds &dt)=0
	This is called by Esrcf. This should be first a computation of the jacobian, and then a motion to update the state. This is a distinct function because depending on the motion model, there is some caching and optimization that can be done computing both the motion and jacobian together. More...

virtual void	reset (const Eigen::Matrix< float32_t, NumStates, 1U > &x)=0
	Set the state. More...

virtual const Eigen::Matrix< float32_t, NumStates, 1U > &	get_state () const=0
	const access to internal state More...

constexpr index_t	get_num_states () const noexcept
	get dimensionality of this model More...

virtual	~MotionModel ()=default
	Destructor. More...

Detailed Description

This is a simple constant velocity motion model.

Member Function Documentation

◆ compute_jacobian()

void autoware::motion::motion_model::ConstantVelocity::compute_jacobian	(	Eigen::Matrix< float32_t, 4U, 4U > &	F,
		const std::chrono::nanoseconds &	dt
	)

override

Compute the jacobian based on the current state and store the result somewhere else.

Parameters

[out]	F	matrix to store jacobian into
[in]	dt	prediction horizon to build jacobian off of

◆ compute_jacobian_and_predict()

void autoware::motion::motion_model::ConstantVelocity::compute_jacobian_and_predict	(	Eigen::Matrix< float32_t, 4U, 4U > &	F,
		const std::chrono::nanoseconds &	dt
	)

override

This is called by Esrcf. This should be first a computation of the jacobian, and then a motion to update the state. This is a distinct function because depending on the motion model, there is some caching and optimization that can be done computing both the motion and jacobian together.

Parameters

[out]	F	matrix to store jacobian into
[in]	dt	prediction horizon to build jacobian off of

◆ get_state()

const Eigen::Matrix< float32_t, 4U, 1U > & autoware::motion::motion_model::ConstantVelocity::get_state ( ) const

override

const access to internal state

Returns: const reference to internal state vector

◆ operator=()

ConstantVelocity & autoware::motion::motion_model::ConstantVelocity::operator= ( const ConstantVelocity & rhs )

Default assignment operator.

Parameters

[in] rhs Object to copy

Returns: reference to this object

◆ operator[]()

float autoware::motion::motion_model::ConstantVelocity::operator[] ( const index_t idx ) const

overridevirtual

Get elements of the model's state.

Parameters

[in] idx index of state variable to get

Returns: copy of state variable

Implements autoware::motion::motion_model::MotionModel< 4U >.

◆ predict() [1/2]

void autoware::motion::motion_model::ConstantVelocity::predict ( const std::chrono::nanoseconds & dt )

overridevirtual

Update current state with a given motion. Note that this should be called after compute_jacobian() as it will change the object's state. This is meant to be called before doing assignment and observation updating. This is the equivalent of temporal update for the state. This function mutates the core state of the motion model.

Parameters

[in] dt prediction horizon based on current state

Implements autoware::motion::motion_model::MotionModel< 4U >.

◆ predict() [2/2]

void autoware::motion::motion_model::ConstantVelocity::predict	(	Eigen::Matrix< float32_t, 4U, 1U > &	x,
		const std::chrono::nanoseconds &	dt
	)		const

override

Do motion based on current state, store result somewhere else. This is intended to be used with motion planning/collision avoidance i.e. to make multiple calls to predict with different time deltas for a rollout to get a concrete representation of predicted trajectories. This function does not mutate the core state of the motion model, and should only mutate some cached worker variables at most.

Parameters

[out]	x	vector to store result into
[in]	dt	prediction horizon based on current state

◆ reset()

void autoware::motion::motion_model::ConstantVelocity::reset ( const Eigen::Matrix< float32_t, 4U, 1U > & x )

override

Set the state.

Parameters

[in] x the state to store internally

The documentation for this class was generated from the following files:

Classes

Public Member Functions

Detailed Description

Member Function Documentation

◆ compute_jacobian()

◆ compute_jacobian_and_predict()

◆ get_state()

◆ operator=()

◆ operator[]()

◆ predict() [1/2]

◆ predict() [2/2]

◆ reset()