Observations#

genesis_forge.mdp.observations.contact_force(env: GenesisEnv, contact_manager: ContactManager) → torch.Tensor[source]#

Returns the vector norm contact force at each contact point.

Parameters:

  • env – The Genesis Forge environment

  • contact_manager – The contact manager to check for contact

Returns:

Shape (num_envs, num_contacts).

Return type:

torch.Tensor

genesis_forge.mdp.observations.current_actions(env: GenesisEnv, action_manager: PositionActionManager = None) → torch.Tensor[source]#

The most current step actions.

genesis_forge.mdp.observations.entity_angular_velocity(env: GenesisEnv, entity_manager: EntityManager = None, entity_attr: str = 'robot') → torch.Tensor[source]#

The angular velocity of the entity’s base link, in the entity’s local frame.

Parameters:

  • env – The Genesis environment containing the entity

  • entity_manager – The entity manager for the robot/entity the observation is being computed for. This is slightly more performant than using the entity_attr parameter.

  • entity_attr – The attribute name of the entity in the environment. This isn’t necessary if entity_manager is provided.

Returns:

The angular velocity of the entity’s base link, in the entity’s local frame.

Return type:

torch.Tensor

genesis_forge.mdp.observations.entity_dofs_force(env: GenesisEnv, actuator_manager: ActuatorManager = None, entity_attr: str = 'robot', dofs_idx: list[int] = None, clip_to_max_force: bool = False, action_manager: PositionActionManager = None) → torch.Tensor[source]#

The DOF’s force being experienced.

Parameters:

  • env – The Genesis environment containing the entity

  • actuator_manager – The actuator manager for the robot/entity. This bypasses the need for dofs_idx and entity_attr parameters.

  • entity_attr – The attribute name of the entity in the environment. This isn’t necessary if action_manager is provided.

  • dofs_idx – The indices of the DOFs to get the force of. This isn’t necessary if action_manager is provided.

  • clip_to_max_force – Clip the force to the maximum force defined in the action_manager.

  • action_manager – (deprecated) The action manager for the robot/entity.

Returns:

The force of the entity’s DOFs.

Return type:

torch.Tensor

genesis_forge.mdp.observations.entity_dofs_position(env: GenesisEnv, actuator_manager: ActuatorManager = None, entity_attr: str = 'robot', dofs_idx: list[int] = None, action_manager: PositionActionManager = None) → torch.Tensor[source]#

The position of the entity’s DOFs.

Parameters:

  • env – The Genesis environment containing the entity

  • actuator_manager – The actuator manager for the robot/entity. This bypasses the need for dofs_idx and entity_attr parameters.

  • entity_attr – The attribute name of the entity in the environment. This isn’t necessary if action_manager is provided.

  • dofs_idx – The indices of the DOFs to get the position of. This isn’t necessary if action_manager is provided.

  • action_manager – (deprecated) The action manager for the robot/entity. This bypasses the need for dofs_idx and entity_attr parameters.

Returns:

The position of the entity’s DOFs.

Return type:

torch.Tensor

genesis_forge.mdp.observations.entity_dofs_velocity(env: GenesisEnv, action_manager: PositionActionManager = None, entity_attr: str = 'robot', dofs_idx: list[int] = None) → torch.Tensor[source]#

The velocity of the entity’s DOFs.

Parameters:

  • env – The Genesis environment containing the entity

  • action_manager – The action manager for the robot/entity. This is slightly more performant than using the entity_attr parameter.

  • entity_attr – The attribute name of the entity in the environment. This isn’t necessary if action_manager is provided.

  • dofs_idx – The indices of the DOFs to get the velocity of. This isn’t necessary if action_manager is provided.

Returns:

The velocity of the entity’s DOFs.

Return type:

torch.Tensor

genesis_forge.mdp.observations.entity_linear_velocity(env: GenesisEnv, entity_manager: EntityManager = None, entity_attr: str = 'robot') → torch.Tensor[source]#

The linear velocity of the entity’s base link, in the entity’s local frame.

Parameters:

  • env – The Genesis environment containing the entity

  • entity_manager – The entity manager for the robot/entity the observation is being computed for. This is slightly more performant than using the entity_attr parameter.

  • entity_attr – The attribute name of the entity in the environment. This isn’t necessary if entity_manager is provided.

Returns:

The linear velocity of the entity’s base link, in the entity’s local frame.

Return type:

torch.Tensor

genesis_forge.mdp.observations.entity_projected_gravity(env: GenesisEnv, entity_manager: EntityManager = None, entity_attr: str = 'robot') → torch.Tensor[source]#

The projected gravity of the entity’s base link, in the entity’s local frame.

Parameters:

  • env – The Genesis environment containing the entity

  • entity_manager – The entity manager for the robot/entity the observation is being computed for. This is slightly more performant than using the entity_attr parameter.

  • entity_attr – The attribute name of the entity in the environment. This isn’t necessary if entity_manager is provided.

Returns:

The projected gravity of the entity’s base link, in the entity’s local frame.

Return type:

torch.Tensor

genesis_forge.mdp.observations.has_contact(env: GenesisEnv, contact_manager: ContactManager, threshold=1.0) → torch.Tensor[source]#

Return boolean (1/0) for each link in the contact manager that meets the contact threshold.

Parameters:

  • env – The Genesis Forge environment

  • contact_manager – The contact manager to check for contact

  • threshold – The minimum force necessary for contact detection (default: 1.0)

Returns:

1 for each link meeting the contact threshold

genesis_forge.mdp.observations.read_imu(env: GenesisEnv, imu: genesis.gs.sensors.IMU) → torch.Tensor[source]#

Makes an IMU reading and returns the concatenated linear acceleration and angular velocity readings.

Example:

self.imu = gs.sensors.IMU(
    entity_idx=self.robot.idx,
    pos_offset=(0.24, 0.0, 0.0),
    euler_offset=(0.0, 0.0, 0.0),
)

...

ObservationManager(
    self,
    cfg={
        "imu_sensor": {
            "fn": self.imu_observation,
        },
    }
)
Returns:

Shape (n_envs, 6) — [lin_acc_xyz, ang_vel_xyz] per env.

Return type:

torch.Tensor