模块：
| 名称 | 描述 |
|---|---|
rewards |
|
类：
| 名称 | 描述 |
|---|---|
HelixTrajectory |
Batched helix trajectory. |
LemniscateTrajectory |
Batched Bernoulli lemniscate trajectory. |
LissajousTrajectory |
Batched three-dimensional Lissajous trajectory. |
RectangleTrajectory |
Batched constant-speed rectangle trajectory in the horizontal plane. |
RandomTrajectoryCommand |
Trajectory command generator with randomized type and parameters per environment. |
RandomTrajectoryCommandCfg |
Configuration for randomized trajectory commands. |
DifferentialDriveController |
PX4-style position/heading cascade with differential speed allocation. |
DifferentialDriveActionMapper |
Map normalized ground actions into differential controller targets. |
DifferentialDriveMappingConfig |
Policy-facing scaling for differential-drive controller modes. |
DifferentialDriveControlAction |
Map selectable ground-control actions to drive-joint velocity targets. |
DifferentialDriveControlActionCfg |
Configuration for selectable differential-drive control. |
函数：
| 名称 | 描述 |
|---|---|
root_euler_w |
Euler angles of the root in world frame. |
planar_pos_error_tanh |
Reward XY position tracking without constraining ground-contact height. |
track_trajectory_ang_vel_z_exp |
Reward yaw-rate tracking for trajectory commands with yaw at index three. |
属性：
| 名称 | 类型 | 描述 |
|---|---|---|
ACTION_KEY_ORDER |
Stable policy-action field order derived from the shared controller schema. |
module-attribute
ACTION_KEY_ORDER = tuple(ControllerState.__annotations__)
Stable policy-action field order derived from the shared controller schema.
Only fields present in the active control mask consume action slices.
dataclass
HelixTrajectory(*, num_envs: int = 1, device: str | None = None, backend: BackendName | None = None, xp: ModuleType | None = None, initialize: bool = True, yaw_from_velocity: bool = True, fixed_yaw: ArrayLike | float = 0.0, attitude: ArrayLike | tuple[float, float] = (0.0, 0.0), body_rate: ArrayLike | tuple[float, float] = (0.0, 0.0), center: ArrayLike | tuple[float, float, float] = (0.0, 0.0, 1.0), radius: ArrayLike | float = 1.0, omega: ArrayLike | float = 0.5, z_amplitude: ArrayLike | float = 0.0, z_frequency: ArrayLike | float = 1.0, z_phase: ArrayLike | float = 0.0)
Bases: SpatialTrajectory
Batched helix trajectory.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample batched yaw and yaw-rate references for time values |
build_target |
Assemble a batched dict target from motion primitives. |
__post_init__ |
Initialize HelixTrajectory. |
sample |
Sample the helix at time t. |
sample_heading(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> tuple[ArrayLike, ArrayLike]
Sample batched yaw and yaw-rate references for time values t.
build_target(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> ControllerTarget
Assemble a batched dict target from motion primitives.
__post_init__()
Initialize HelixTrajectory.
sample(t: ArrayLike) -> ControllerTarget
Sample the helix at time t.
dataclass
LemniscateTrajectory(*, num_envs: int = 1, device: str | None = None, backend: BackendName | None = None, xp: ModuleType | None = None, initialize: bool = True, yaw_from_velocity: bool = True, fixed_yaw: ArrayLike | float = 0.0, attitude: ArrayLike | tuple[float, float] = (0.0, 0.0), body_rate: ArrayLike | tuple[float, float] = (0.0, 0.0), center: ArrayLike | tuple[float, float, float] = (0.0, 0.0, 1.0), scale: ArrayLike | float = 1.0, omega: ArrayLike | float = 0.5, z_amplitude: ArrayLike | float = 0.0, z_frequency: ArrayLike | float = 1.0, z_phase: ArrayLike | float = 0.0)
Bases: SpatialTrajectory
Batched Bernoulli lemniscate trajectory.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample batched yaw and yaw-rate references for time values |
build_target |
Assemble a batched dict target from motion primitives. |
__post_init__ |
Initialize LemniscateTrajectory. |
sample |
Sample the lemniscate at time t. |
sample_heading(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> tuple[ArrayLike, ArrayLike]
Sample batched yaw and yaw-rate references for time values t.
build_target(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> ControllerTarget
Assemble a batched dict target from motion primitives.
__post_init__()
Initialize LemniscateTrajectory.
sample(t: ArrayLike) -> ControllerTarget
Sample the lemniscate at time t.
dataclass
LissajousTrajectory(*, num_envs: int = 1, device: str | None = None, backend: BackendName | None = None, xp: ModuleType | None = None, initialize: bool = True, yaw_from_velocity: bool = True, fixed_yaw: ArrayLike | float = 0.0, attitude: ArrayLike | tuple[float, float] = (0.0, 0.0), body_rate: ArrayLike | tuple[float, float] = (0.0, 0.0), center: ArrayLike | tuple[float, float, float] = (0.0, 0.0, 1.0), amplitude: ArrayLike | tuple[float, float, float] = (1.0, 1.0, 0.2), frequency: ArrayLike | tuple[float, float, float] = (1.0, 2.0, 0.5), phase: ArrayLike | tuple[float, float, float] = (0.0, 0.0, 0.0), omega: ArrayLike | float = 0.5)
Bases: SpatialTrajectory
Batched three-dimensional Lissajous trajectory.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample batched yaw and yaw-rate references for time values |
build_target |
Assemble a batched dict target from motion primitives. |
__post_init__ |
Initialize LissajousTrajectory. |
sample |
Sample the Lissajous trajectory at time t. |
sample_heading(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> tuple[ArrayLike, ArrayLike]
Sample batched yaw and yaw-rate references for time values t.
build_target(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> ControllerTarget
Assemble a batched dict target from motion primitives.
__post_init__()
Initialize LissajousTrajectory.
sample(t: ArrayLike) -> ControllerTarget
Sample the Lissajous trajectory at time t.
dataclass
RectangleTrajectory(*, num_envs: int = 1, device: str | None = None, backend: BackendName | None = None, xp: ModuleType | None = None, initialize: bool = True, yaw_from_velocity: bool = True, fixed_yaw: ArrayLike | float = 0.0, attitude: ArrayLike | tuple[float, float] = (0.0, 0.0), body_rate: ArrayLike | tuple[float, float] = (0.0, 0.0), center: ArrayLike | tuple[float, float, float] = (0.0, 0.0, 1.0), size: ArrayLike | tuple[float, float] = (2.0, 1.0), speed: ArrayLike | float = 0.5)
Bases: SpatialTrajectory
Batched constant-speed rectangle trajectory in the horizontal plane.
方法：
| 名称 | 描述 |
|---|---|
sample_heading |
Sample batched yaw and yaw-rate references for time values |
build_target |
Assemble a batched dict target from motion primitives. |
__post_init__ |
Initialize RectangleTrajectory. |
sample |
Sample the rectangle trajectory at time t. |
sample_heading(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> tuple[ArrayLike, ArrayLike]
Sample batched yaw and yaw-rate references for time values t.
build_target(t: ArrayLike, pos: ArrayLike, vel: ArrayLike, acc: ArrayLike) -> ControllerTarget
Assemble a batched dict target from motion primitives.
__post_init__()
Initialize RectangleTrajectory.
sample(t: ArrayLike) -> ControllerTarget
Sample the rectangle trajectory at time t.
RandomTrajectoryCommand(cfg: RandomTrajectoryCommandCfg, env: ManagerBasedEnv)
Bases: CommandTerm
Trajectory command generator with randomized type and parameters per environment.
Bases: CommandTermCfg
Configuration for randomized trajectory commands.
DifferentialDriveController(params: VehicleParams, control_mask: dict | None = None, gains: dict | None = None, limits: dict | None = None, num_envs: int = 1, device=None, *, backend: BackendName | None = None, xp: ModuleType | None = None)
Bases: ControllerBase
PX4-style position/heading cascade with differential speed allocation.
The output is [left, right] drive-shaft angular velocity in rad/s. The
controller is independent of wheel count: a platform adapter commands one
physical drive joint per side, while backend mechanical constraints
synchronize any follower road wheels or wheel shells.
Initialize the batched differential-drive controller.
方法：
| 名称 | 描述 |
|---|---|
randomize |
Randomize gains and limits for selected environments. |
reset |
Reset all PID state for selected environments. |
update |
Compute left/right drive-shaft angular-velocity targets in rad/s. |
属性：
| 名称 | 类型 | 描述 |
|---|---|---|
params |
VehicleParams
|
Vehicle parameters for the controller. |
instance-attribute
params: VehicleParams = params
Vehicle parameters for the controller.
randomize(env_ids=None, gains: dict[str, Any] | None = None, limits: dict[str, Any] | None = None)
Randomize gains and limits for selected environments.
reset(env_ids=None)
Reset all PID state for selected environments.
update(target: ControllerTarget, state: ControllerState) -> ArrayLike
Compute left/right drive-shaft angular-velocity targets in rad/s.
DifferentialDriveActionMapper(control_mode: str, params: VehicleParams, mapping: DifferentialDriveMappingConfig | None = None, control_mask: dict | None = None, num_envs: int = 1, device=None, *, backend: BackendName | None = None, xp: ModuleType | None = None)
Map normalized ground actions into differential controller targets.
Initialize the ground mapper and stable action-field indices.
方法：
| 名称 | 描述 |
|---|---|
decode_action |
Decode a policy action into side speed or a controller target. |
map_action |
Resolve an action into left/right output-shaft speed targets. |
属性：
| 名称 | 类型 | 描述 |
|---|---|---|
requires_controller |
bool
|
Whether this mode passes through the differential controller. |
property
requires_controller: bool
Whether this mode passes through the differential controller.
decode_action(action: ArrayLike, *, state: ControllerState | None = None) -> DifferentialDriveMapping
Decode a policy action into side speed or a controller target.
map_action(action: ArrayLike, *, state: ControllerState | None = None, controller: ControllerBase | None = None) -> DifferentialDriveMapping
Resolve an action into left/right output-shaft speed targets.
dataclass
DifferentialDriveMappingConfig(forward_speed_range: float | None = None, yaw_rate_range: float | None = None, heading_range: float = pi, side_speed_range: float | None = None)
Policy-facing scaling for differential-drive controller modes.
方法：
| 名称 | 描述 |
|---|---|
from_params |
Build mapping ranges from track or wheel platform parameters. |
resolve |
Resolve explicit overrides against platform-derived defaults. |
classmethod
from_params(params: VehicleParams) -> DifferentialDriveMappingConfig
Build mapping ranges from track or wheel platform parameters.
resolve(params: VehicleParams) -> DifferentialDriveMappingConfig
Resolve explicit overrides against platform-derived defaults.
DifferentialDriveControlAction(cfg: DifferentialDriveControlActionCfg, env: ManagerBasedRLEnv)
Bases: ActionTerm
Map selectable ground-control actions to drive-joint velocity targets.
属性：
| 名称 | 类型 | 描述 |
|---|---|---|
IO_descriptor |
GenericActionIODescriptor
|
Describe policy channels for the selected ground-control mode. |
property
IO_descriptor: GenericActionIODescriptor
Describe policy channels for the selected ground-control mode.
Bases: ActionTermCfg
Configuration for selectable differential-drive control.
root_euler_w(env: ManagerBasedRLEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg('robot')) -> torch.Tensor
Euler angles of the root in world frame.
planar_pos_error_tanh(env: ManagerBasedRLEnv, std: float, command_name: str) -> torch.Tensor
Reward XY position tracking without constraining ground-contact height.
track_trajectory_ang_vel_z_exp(env: ManagerBasedRLEnv, std: float, command_name: str, asset_cfg: SceneEntityCfg = SceneEntityCfg('robot')) -> torch.Tensor
Reward yaw-rate tracking for trajectory commands with yaw at index three.