Trajectory implementations package for LAV2.
模块：
| 名称 | 描述 |
|---|---|
base |
NumPy trajectory base classes. |
helix |
NumPy helix trajectory implementation. |
hover_step |
NumPy piecewise hover-step trajectory implementation. |
lemniscate |
NumPy lemniscate trajectory implementation. |
lissajous |
NumPy Lissajous trajectory implementation. |
rectangle |
NumPy rectangle trajectory implementation. |
torch |
Torch trajectory implementations for batched RL environments. |
类：
| 名称 | 描述 |
|---|---|
BaseTrajectory |
Abstract base class for time-parameterized NumPy reference trajectories. |
SpatialTrajectory |
Base class for trajectories centered around a world-frame anchor point. |
HelixTrajectory |
Helix trajectory with optional vertical oscillation. |
HoverStepTrajectory |
Piecewise-constant position and yaw trajectory. |
LemniscateTrajectory |
Bernoulli lemniscate trajectory with optional vertical oscillation. |
LissajousTrajectory |
Three-dimensional Lissajous trajectory. |
RectangleTrajectory |
Constant-speed rectangle trajectory in the horizontal plane. |
dataclass
BaseTrajectory(yaw_from_velocity: bool = True, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0))
Bases: ABC
Abstract base class for time-parameterized NumPy reference trajectories.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample |
Sample the full 12D target at time |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
abstractmethod
sample(t: float) -> np.ndarray
Sample the full 12D target at time t.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
dataclass
SpatialTrajectory(yaw_from_velocity: bool = True, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0), center: tuple[float, float, float] = (0.0, 0.0, 1.0))
Bases: BaseTrajectory
Base class for trajectories centered around a world-frame anchor point.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample |
Sample the full 12D target at time |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
__post_init__ |
Cache the trajectory center as a float32 NumPy vector. |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
abstractmethod
sample(t: float) -> np.ndarray
Sample the full 12D target at time t.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
__post_init__()
Cache the trajectory center as a float32 NumPy vector.
dataclass
HelixTrajectory(yaw_from_velocity: bool = True, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0), center: tuple[float, float, float] = (0.0, 0.0, 1.0), radius: float = 1.0, omega: float = 0.5, z_amplitude: float = 0.0, z_frequency: float = 1.0, z_phase: float = 0.0)
Bases: SpatialTrajectory
Helix trajectory with optional vertical oscillation.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
__post_init__ |
Cache the trajectory center as a float32 NumPy vector. |
sample |
Sample the helix trajectory at time |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
__post_init__()
Cache the trajectory center as a float32 NumPy vector.
sample(t: float) -> np.ndarray
Sample the helix trajectory at time t.
dataclass
HoverStepTrajectory(yaw_from_velocity: bool = False, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0), initial: tuple[float, float, float, float] = (0.0, 0.0, 1.0, 0.0), steps: tuple[tuple[float, tuple[float, float, float, float]], ...] = ((5.0, (1.0, 0.0, 1.0, 0.0)), (10.0, (1.0, 1.0, 1.5, np.pi / 2.0)), (15.0, (0.0, 1.0, 1.5, np.pi))))
Bases: BaseTrajectory
Piecewise-constant position and yaw trajectory.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
sample |
Sample the active hover target at time |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
sample(t: float) -> np.ndarray
Sample the active hover target at time t.
dataclass
LemniscateTrajectory(yaw_from_velocity: bool = True, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0), center: tuple[float, float, float] = (0.0, 0.0, 1.0), scale: float = 1.0, omega: float = 0.5, z_amplitude: float = 0.0, z_frequency: float = 1.0, z_phase: float = 0.0)
Bases: SpatialTrajectory
Bernoulli lemniscate trajectory with optional vertical oscillation.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
__post_init__ |
Cache the trajectory center as a float32 NumPy vector. |
sample |
Sample the lemniscate trajectory at time |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
__post_init__()
Cache the trajectory center as a float32 NumPy vector.
sample(t: float) -> np.ndarray
Sample the lemniscate trajectory at time t.
dataclass
LissajousTrajectory(yaw_from_velocity: bool = True, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0), center: tuple[float, float, float] = (0.0, 0.0, 1.0), amplitude: tuple[float, float, float] = (1.0, 1.0, 0.2), frequency: tuple[float, float, float] = (1.0, 2.0, 0.5), phase: tuple[float, float, float] = (0.0, np.pi / 2.0, 0.0), omega: float = 0.5)
Bases: SpatialTrajectory
Three-dimensional Lissajous trajectory.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
__post_init__ |
Cache vector-valued parameters as float32 NumPy arrays. |
sample |
Sample the Lissajous trajectory at time |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
__post_init__()
Cache vector-valued parameters as float32 NumPy arrays.
sample(t: float) -> np.ndarray
Sample the Lissajous trajectory at time t.
dataclass
RectangleTrajectory(yaw_from_velocity: bool = True, fixed_yaw: float = 0.0, attitude: tuple[float, float] = (0.0, 0.0), body_rate: tuple[float, float] = (0.0, 0.0), center: tuple[float, float, float] = (0.0, 0.0, 1.0), size: tuple[float, float] = (2.0, 1.0), speed: float = 0.5)
Bases: SpatialTrajectory
Constant-speed rectangle trajectory in the horizontal plane.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample yaw and yaw-rate references for time |
build_target |
Assemble a full 12D target from position, velocity, and acceleration. |
sample_batch |
Sample a batch of timestamps and stack the resulting 12D targets. |
__post_init__ |
Precompute rectangle corners and edge lengths. |
sample |
Sample the rectangle trajectory at time |
sample_heading(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> tuple[float, float]
Sample yaw and yaw-rate references for time t and translation state.
build_target(t: float, pos: ndarray, vel: ndarray, acc: ndarray) -> np.ndarray
Assemble a full 12D target from position, velocity, and acceleration.
sample_batch(ts: ndarray) -> np.ndarray
Sample a batch of timestamps and stack the resulting 12D targets.
__post_init__()
Precompute rectangle corners and edge lengths.
sample(t: float) -> np.ndarray
Sample the rectangle trajectory at time t.