irsim.lib#

Submodules#

Attributes#

register_behavior

register_group_behavior

kinematics_factory

Classes#

reciprocal_vel_obs

A class to implement the Reciprocal Velocity Obstacle (RVO) algorithm for multi-robot collision avoidance.

Behavior

Represents the behavior of an agent in the simulation.

GeometryFactory

Factory class to create geometry handlers.

KinematicsFactory

Factory class to create kinematics handlers.

Functions#

generate_polygon(→ numpy.ndarray)

Generate a random polygon around a center point.

random_generate_polygon(→ Union[numpy.ndarray, ...)

reference: https://stackoverflow.com/questions/8997099/algorithm-to-generate-random-2d-polygon

ackermann_kinematics(→ numpy.ndarray)

Calculate the next state for an Ackermann steering vehicle.

differential_kinematics(→ numpy.ndarray)

Calculate the next state for a differential wheel robot.

omni_kinematics(→ numpy.ndarray)

Calculate the next position for an omnidirectional robot.

Package Contents#

irsim.lib.generate_polygon(center: list[float], avg_radius: float, irregularity: float, spikeyness: float, num_vertices: int) → numpy.ndarray[source]#

Generate a random polygon around a center point.

Parameters:

  • center (Tuple[float, float]) – Center of the polygon.

  • avg_radius (float) – Average radius from the center to vertices.

  • irregularity (float) – Variance of angle spacing between vertices. Range [0, 1]

  • spikeyness (float) – Variance of radius from the center. Range [0, 1]

  • num_vertices (int) – Number of vertices for the polygon.

Returns:

Vertices of the polygon in CCW order.

Return type:

numpy.ndarray

irsim.lib.random_generate_polygon(number: int = 1, center_range: list[float] | None = None, avg_radius_range: list[float] | None = None, irregularity_range: list[float] | None = None, spikeyness_range: list[float] | None = None, num_vertices_range: list[int] | None = None, **kwargs: Any) → numpy.ndarray | list[numpy.ndarray][source]#

reference: https://stackoverflow.com/questions/8997099/algorithm-to-generate-random-2d-polygon

Generate random polygons with specified properties.

Parameters:

  • number (int) – Number of polygons to generate (default 1).

  • center_range (List[float]) – Range for the polygon center [min_x, min_y, max_x, max_y].

  • avg_radius_range (List[float]) – Range for the average radius of the polygons.

  • irregularity_range (List[float]) – Range for the irregularity of the polygons.

  • spikeyness_range (List[float]) – Range for the spikeyness of the polygons.

  • num_vertices_range (List[int]) – Range for the number of vertices of the polygons.

Returns:

List of vertices for each polygon or a single polygon’s vertices if number=1.

irsim.lib.ackermann_kinematics(state: numpy.ndarray, velocity: numpy.ndarray, step_time: float, noise: bool = False, alpha: list[float] | None = None, mode: str = 'steer', wheelbase: float = 1) → numpy.ndarray[source]#

Calculate the next state for an Ackermann steering vehicle.

Parameters:

  • state – A 4x1 vector [x, y, theta, steer_angle] representing the current state.

  • velocity – A 2x1 vector representing the current velocities, format depends on mode. For “steer” mode, [linear, steer_angle] is expected. For “angular” mode, [linear, angular] is expected.

  • step_time – The time step for the simulation.

  • noise – Boolean indicating whether to add noise to the velocity (default False).

  • alpha – List of noise parameters for the velocity model (default [0.03, 0, 0, 0.03]). alpha[0] and alpha[1] are for linear velocity, alpha[2] and alpha[3] are for angular velocity.

  • mode – The kinematic mode, either “steer” or “angular” (default “steer”).

  • wheelbase – The distance between the front and rear axles (default 1).

Returns:

A 4x1 vector representing the next state.

Return type:

new_state

irsim.lib.differential_kinematics(state: numpy.ndarray, velocity: numpy.ndarray, step_time: float, noise: bool = False, alpha: list[float] | None = None) → numpy.ndarray[source]#

Calculate the next state for a differential wheel robot.

Parameters:

  • state – A 3x1 vector [x, y, theta] representing the current position and orientation.

  • velocity – A 2x1 vector [linear, angular] representing the current velocities.

  • step_time – The time step for the simulation.

  • noise – Boolean indicating whether to add noise to the velocity (default False).

  • alpha – List of noise parameters for the velocity model (default [0.03, 0, 0, 0.03]). alpha[0] and alpha[1] are for linear velocity, alpha[2] and alpha[3] are for angular velocity.

Returns:

A 3x1 vector [x, y, theta] representing the next state.

Return type:

next_state

irsim.lib.omni_kinematics(state: numpy.ndarray, velocity: numpy.ndarray, step_time: float, noise: bool = False, alpha: list[float] | None = None) → numpy.ndarray[source]#

Calculate the next position for an omnidirectional robot.

Parameters:

  • state – A 2x1 vector [x, y] representing the current position.

  • velocity – A 2x1 vector [vx, vy] representing the current velocities.

  • step_time – The time step for the simulation.

  • noise – Boolean indicating whether to add noise to the velocity (default False).

  • alpha – List of noise parameters for the velocity model (default [0.03, 0.03]). alpha[0] is for x velocity, alpha[1] is for y velocity.

Returns:

A 2x1 vector [x, y] representing the next position.

Return type:

new_position

class irsim.lib.reciprocal_vel_obs(state: list, obs_state_list=None, vxmax=1.5, vymax=1.5, acce=0.5, factor=1.0)[source]#

A class to implement the Reciprocal Velocity Obstacle (RVO) algorithm for multi-robot collision avoidance.

Parameters:

  • state (list) – The rvo state of the agent [x, y, vx, vy, radius, vx_des, vy_des].

  • obs_state_list (list) – List of states of static obstacles [[x, y, vx, vy, radius]].

  • vxmax (float) – Maximum velocity in the x direction.

  • vymax (float) – Maximum velocity in the y direction.

  • acce (float) – Acceleration limit.

  • factor (float) – Penalty weighting factor for velocity selection.

state#
obs_state_list = None#
vxmax = 1.5#
vymax = 1.5#
acce = 0.5#
factor = 1.0#
update(state, obs_state_list)[source]#
cal_vel(mode='rvo')[source]#

Calculate the velocity of the agent based on the Reciprocal Velocity Obstacle (RVO) algorithm.

Parameters:

mode (str) – The vo configure to calculate the velocity. It can be “rvo”, “hrvo”, or “vo”. - rvo: Reciprocal Velocity Obstacle (RVO) algorithm, for multi-robot collision avoidance. - hrvo: Hybrid Reciprocal Velocity Obstacle (HRVO) algorithm, for multi-robot collision avoidance. - vo: Velocity Obstacle (VO) algorithm, for obstacle-robot collision avoidance.

Returns:

Selected velocity [vx, vy].

Return type:

list[float]

config_rvo()[source]#
config_rvo_mode(obstacle)[source]#
config_hrvo()[source]#
config_hrvo_mode(obstacle)[source]#
config_vo()[source]#
config_vo_mode(obstacle)[source]#
vel_candidate(rvo_list)[source]#
vo_out(vx, vy, rvo_list)[source]#
vel_select(vo_outside, vo_inside)[source]#
penalty(vel, vel_des, factor)[source]#
static between_vector(line_left_vector, line_right_vector, line_vector)[source]#
static cross_product(vector1, vector2)[source]#
class irsim.lib.Behavior(object_info=None, behavior_dict=None)[source]#

Represents the behavior of an agent in the simulation.

Parameters:

  • object_info (object) – Object information from the object_base class ObjectInfo.

  • behavior_dict (dict) –

    Dictionary containing behavior parameters for different behaviors. Name Options include: ‘dash’, ‘rvo’. target_roles:

    • ’all’: all objects in the environment will be considered within this behavior.

    • ’obstacle’: only obstacles will be considered within this behavior.

    • ’robot’: only robots will be considered within this behavior.

Initialize the behavior with object info and parameters.

Parameters:

  • object_info – Information about the agent (from ObjectBase.ObjectInfo).

  • behavior_dict (dict | None) – Behavior parameters; if None, defaults to an empty dict.

object_info = None#
behavior_dict#
gen_vel(ego_object, external_objects=None)[source]#

Generate a velocity for the agent based on configured behavior.

Parameters:

  • ego_object – The agent itself (object with needed attributes).

  • external_objects (list | None) – Other objects in the environment.

Returns:

A 2x1 velocity vector appropriate for the agent kinematics.

Return type:

numpy.ndarray

load_behavior(behaviors: str = '.behavior_methods')[source]#

Load behavior parameters from the script.

Parameters:

behaviors (str) – name of the behavior script.

invoke_behavior(kinematics: str, action: str, **kwargs: Any) → Any[source]#

Invoke a specific behavior method based on kinematics model and action type.

This method looks up and executes the appropriate behavior function from the behavior registry based on the combination of kinematics model and action name.

Parameters:

  • kinematics (str) –

    Kinematics model identifier. Supported values:

    • ’diff’: Differential drive kinematics

    • ’omni’: Omnidirectional kinematics

    • ’acker’: Ackermann steering kinematics

  • action (str) –

    Behavior action name. Examples:

    • ’dash’: Direct movement toward goal

    • ’rvo’: Reciprocal Velocity Obstacles for collision avoidance

  • **kwargs – Additional keyword arguments passed to the behavior function. Common parameters include ego_object, external_objects, goal, etc.

Returns:

Generated velocity vector (2x1) in the format appropriate for the specified kinematics model.

Return type:

np.ndarray

Raises:

ValueError – If no behavior method is found for the given kinematics and action combination.

Example

>>> # Invoke differential drive dash behavior
>>> vel = behavior.invoke_behavior('diff', 'dash',
...                               ego_object=robot,
...                               external_objects=obstacles)
irsim.lib.register_behavior#
irsim.lib.register_group_behavior#
class irsim.lib.GeometryFactory[source]#

Factory class to create geometry handlers.

static create_geometry(name: str = 'circle', **kwargs) → geometry_handler[source]#
class irsim.lib.KinematicsFactory[source]#

Factory class to create kinematics handlers.

static create_kinematics(name: str | None = None, noise: bool = False, alpha: list | None = None, mode: str = 'steer', wheelbase: float | None = None, role: str = 'robot') → KinematicsHandler[source]#
irsim.lib.kinematics_factory: dict[str, Callable[Ellipsis, Any]]#