irsim.lib.behavior.behavior_methods#

Functions#

`beh_diff_rvo`(→ numpy.ndarray)	Behavior function for differential drive robot using RVO (Reciprocal Velocity Obstacles).
`beh_diff_dash`(→ numpy.ndarray)	Behavior function for differential drive robot using dash-to-goal behavior.
`beh_omni_dash`(→ numpy.ndarray)	Behavior function for omnidirectional robot using dash-to-goal behavior.
`beh_omni_rvo`(→ numpy.ndarray)	Behavior function for omnidirectional robot using RVO (Reciprocal Velocity Obstacles).
`beh_diff_sfm`(→ numpy.ndarray)	Behavior function for differential drive robot using the Social Force Model.
`beh_omni_sfm`(→ numpy.ndarray)	Behavior function for omnidirectional robot using the Social Force Model.
`beh_omni_angular_dash`(→ numpy.ndarray)	Behavior function for omnidirectional-angular robot using dash-to-goal behavior.
`beh_acker_dash`(→ numpy.ndarray)	Behavior function for Ackermann steering robot using dash-to-goal behavior.
`SFMVelocity`(→ tuple[float, float])	Compute the next world-frame velocity using the Social Force Model.
`OmniRVO`(→ numpy.ndarray)	Calculate the omnidirectional velocity using RVO.
`DiffRVO`(→ numpy.ndarray)	Calculate the differential drive velocity using RVO.
`OmniDash`(→ numpy.ndarray)	Calculate the body-frame velocity to reach a goal.
`OmniAngularDash`(→ numpy.ndarray)	Calculate body-frame velocity to reach a goal.
`DiffDash`(→ numpy.ndarray)	Calculate the differential drive velocity to reach a goal.
`AckerDash`(→ numpy.ndarray)	Calculate the Ackermann steering velocity to reach a goal.

Module Contents#

irsim.lib.behavior.behavior_methods.beh_diff_rvo(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for differential drive robot using RVO (Reciprocal Velocity Obstacles).

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- Additional keyword arguments: - vxmax (float): Maximum x velocity, default 1.5. - vymax (float): Maximum y velocity, default 1.5. - acce (float): Acceleration factor, default 1.0. - factor (float): Additional scaling factor, default 1.0. - mode (str): RVO calculation mode, default "rvo". - neighbor_threshold (float): Neighbor threshold distance, default 10.0.

返回:

Velocity [linear, angular] (2x1) for differential drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_diff_dash(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for differential drive robot using dash-to-goal behavior.

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- Additional keyword arguments: - angle_tolerance (float): Allowable angular deviation, default 0.1.

返回:

Velocity [linear, angular] (2x1) for differential drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_omni_dash(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for omnidirectional robot using dash-to-goal behavior.

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- Additional keyword arguments (currently unused).

返回:

Velocity [vx, vy] (2x1) for omnidirectional drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_omni_rvo(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for omnidirectional robot using RVO (Reciprocal Velocity Obstacles).

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- Additional keyword arguments: - vxmax (float): Maximum x velocity, default 1.5. - vymax (float): Maximum y velocity, default 1.5. - acce (float): Acceleration factor, default 1.0. - factor (float): Additional scaling factor, default 1.0. - mode (str): RVO calculation mode, default "rvo". - neighbor_threshold (float): Neighbor threshold distance, default 3.0.

返回:

Velocity [vx, vy] (2x1) for omnidirectional drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_diff_sfm(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for differential drive robot using the Social Force Model.

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- SFM tuning parameters; see SFMVelocity().

返回:

Velocity [linear, angular] (2x1) for differential drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_omni_sfm(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for omnidirectional robot using the Social Force Model.

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- SFM tuning parameters; see SFMVelocity().

返回:

Velocity [vx, vy] (2x1) for omnidirectional drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_omni_angular_dash(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for omnidirectional-angular robot using dash-to-goal behavior.

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- Additional keyword arguments: - angle_tolerance (float): Allowable angular deviation, default 0.1.

返回:

Velocity [forward, lateral, yaw_rate] (3x1) in body frame.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.beh_acker_dash(ego_object: Any, external_objects: list[Any], **kwargs: Any) → numpy.ndarray[源代码]#

Behavior function for Ackermann steering robot using dash-to-goal behavior.

参数:

ego_object -- The ego robot object.
external_objects (list) -- List of external objects in the environment.
**kwargs -- Additional keyword arguments: - angle_tolerance (float): Allowable angular deviation, default 0.1.

返回:

Velocity [linear, steering angle] (2x1) for Ackermann drive.

返回类型:

np.array

irsim.lib.behavior.behavior_methods.SFMVelocity(state_tuple: Any, neighbor_list: list[Any] | None = None, line_segments: list[list[float]] | None = None, vmax: float = 1.5, step_time: float = 0.1, neighbor_threshold: float = 10.0, relaxation_time: float = 0.5, force_factor_desired: float = 1.0, force_factor_social: float = 2.1, force_factor_obstacle: float = 10.0, sigma_obstacle: float = 0.8, lambda_importance: float = 2.0, gamma: float = 0.35, n_angular: float = 2.0, n_velocity: float = 3.0, safety_radius: float = 0.0, **_: Any) → tuple[float, float][源代码]#

Compute the next world-frame velocity using the Social Force Model.

Anisotropic Moussaid-Helbing (2009) variant.

参数:

state_tuple -- Full RVO-style state [x, y, vx, vy, radius, vx_des, vy_des, theta].
neighbor_list -- Neighbour states [[x, y, vx, vy, radius], ...].
line_segments -- Line obstacles [[x1, y1, x2, y2], ...].
vmax -- Speed cap.
step_time -- Integration step.
neighbor_threshold -- Spatial cutoff for social interactions.
relaxation_time -- gamma, n_angular, n_velocity: SFM tuning parameters (see social_force_model).
force_factor_* -- gamma, n_angular, n_velocity: SFM tuning parameters (see social_force_model).
sigma_obstacle -- gamma, n_angular, n_velocity: SFM tuning parameters (see social_force_model).
lambda_importance -- gamma, n_angular, n_velocity: SFM tuning parameters (see social_force_model).

:paramgamma, n_angular, n_velocity: SFM tuning parameters: (see social_force_model).

返回:: Updated world-frame velocity (vx, vy).
返回类型:: tuple[float, float]

irsim.lib.behavior.behavior_methods.OmniRVO(state_tuple: Any, neighbor_list: list[Any] | None = None, vxmax: float = 1.5, vymax: float = 1.5, acce: float = 1, factor: float = 1.0, mode: str = 'rvo', neighbor_threshold: float = 3.0, line_segments: list[list[float]] | None = None) → numpy.ndarray[源代码]#

Calculate the omnidirectional velocity using RVO.

参数:

state_tuple (tuple) -- Current state and orientation.
neighbor_list (list) -- List of neighboring agents (default None).
vxmax (float) -- Maximum x velocity (default 1.5).
vymax (float) -- Maximum y velocity (default 1.5).
acce (float) -- Acceleration factor (default 1).
factor (float) -- Additional scaling factor (default 1.0).
mode (str) -- RVO calculation mode (default "rvo").
neighbor_threshold (float) -- Neighbor threshold (default 3.0).
line_segments (list) -- Line segments [[x1, y1, x2, y2], ...] (default None).

返回:

Velocity [vx, vy] (2x1).

返回类型:

np.array

irsim.lib.behavior.behavior_methods.DiffRVO(state_tuple: Any, neighbor_list: list[Any] | None = None, vxmax: float = 1.5, vymax: float = 1.5, acce: float = 1, factor: float = 1.0, mode: str = 'rvo', neighbor_threshold: float = 3.0, line_segments: list[list[float]] | None = None) → numpy.ndarray[源代码]#

Calculate the differential drive velocity using RVO.

参数:

state_tuple (tuple) -- Current state and orientation.
neighbor_list (list) -- List of neighboring agents (default None).
vxmax (float) -- Maximum x velocity (default 1.5).
vymax (float) -- Maximum y velocity (default 1.5).
acce (float) -- Acceleration factor (default 1).
factor (float) -- Additional scaling factor (default 1.0).
mode (str) -- RVO calculation mode (default "rvo").
neighbor_threshold (float) -- Neighbor threshold (default 3.0).
line_segments (list) -- Line segments [[x1, y1, x2, y2], ...] (default None).

返回:

Velocity [linear, angular] (2x1).

返回类型:

np.array

irsim.lib.behavior.behavior_methods.OmniDash(state: numpy.ndarray, goal: numpy.ndarray, max_vel: numpy.ndarray, goal_threshold: float = 0.1) → numpy.ndarray[源代码]#

Calculate the body-frame velocity to reach a goal.

参数:

state (np.array) -- Current state [x, y, theta] (3x1 or 2x1).
goal (np.array) -- Goal position [x, y] (2x1).
max_vel (np.array) -- Maximum velocity [forward, lateral] (2x1).
goal_threshold (float) -- Distance threshold to consider goal reached (default 0.1).

返回:

Body-frame velocity [forward, lateral] (2x1).

返回类型:

np.array

irsim.lib.behavior.behavior_methods.OmniAngularDash(state: numpy.ndarray, goal: numpy.ndarray, max_vel: numpy.ndarray, goal_threshold: float = 0.3, angle_tolerance: float = 0.1) → numpy.ndarray[源代码]#

Calculate body-frame velocity to reach a goal.

Drives forward and strafes laterally toward the goal while turning to face it. After arriving at the goal position, rotates in place to match the goal orientation.

参数:

state (np.array) -- Current state [x, y, theta] (3x1).
goal (np.array) -- Goal state [x, y, theta] (3x1).
max_vel (np.array) -- Maximum velocity [forward, lateral, yaw_rate] (3x1).
goal_threshold (float) -- Distance threshold to consider goal reached (default 0.3).
angle_tolerance (float) -- Allowable angular deviation (default 0.1).

返回:

Body-frame velocity [forward, lateral, yaw_rate] (3x1).

返回类型:

np.array

irsim.lib.behavior.behavior_methods.DiffDash(state: numpy.ndarray, goal: numpy.ndarray, max_vel: numpy.ndarray, goal_threshold: float = 0.1, angle_tolerance: float = 0.2) → numpy.ndarray[源代码]#

Calculate the differential drive velocity to reach a goal.

参数:

state (np.array) -- Current state [x, y, theta] (3x1).
goal (np.array) -- Goal position [x, y] (2x1).
max_vel (np.array) -- Maximum velocity [linear, angular] (2x1).
goal_threshold (float) -- Distance threshold to consider goal reached (default 0.1).
angle_tolerance (float) -- Allowable angular deviation (default 0.2).

返回:

Velocity [linear, angular] (2x1).

返回类型:

np.array

irsim.lib.behavior.behavior_methods.AckerDash(state: numpy.ndarray, goal: numpy.ndarray, max_vel: numpy.ndarray, goal_threshold: float, angle_tolerance: float) → numpy.ndarray[源代码]#

Calculate the Ackermann steering velocity to reach a goal.

参数:

state (np.array) -- Current state [x, y, theta] (3x1).
goal (np.array) -- Goal position [x, y] (2x1).
max_vel (np.array) -- Maximum velocity [linear, steering angle] (2x1).
goal_threshold (float) -- Distance threshold to consider goal reached.
angle_tolerance (float) -- Allowable angular deviation.

返回:

Velocity [linear, steering angle] (2x1).

返回类型:

np.array