An articulated system comprises of actuated joints, also called the degrees of freedom (DOF). In a physical system, the actuation typically happens either through active components, such as electric or hydraulic motors, or passive components, such as springs. These components can introduce certain non-linear characteristics which includes delays or maximum producible velocity or torque.

In simulation, the joints are either position, velocity, or torque-controlled. For position and velocity control, the physics engine internally implements a spring-damp (PD) controller which computes the torques applied on the actuated joints. In torque-control, the commands are set directly as the joint efforts. While this mimics an ideal behavior of the joint mechanism, it does not truly model how the drives work in the physical world. Thus, we provide a mechanism to inject external models to compute the joint commands that would represent the physical robot’s behavior.

Actuator models#

We name two different types of actuator models:

  1. implicit: corresponds to the ideal simulation mechanism (provided by physics engine).

  2. explicit: corresponds to external drive models (implemented by user).

The explicit actuator model performs two steps: 1) it computes the desired joint torques for tracking the input commands, and 2) it clips the desired torques based on the motor capabilities. The clipped torques are the desired actuation efforts that are set into the simulation.

As an example of an ideal explicit actuator model, we provide the omni.isaac.lab.actuators.IdealPDActuator class, which implements a PD controller with feed-forward effort, and simple clipping based on the configured maximum effort:

\[\begin{split}\tau_{j, computed} & = k_p * (q - q_{des}) + k_d * (\dot{q} - \dot{q}_{des}) + \tau_{ff} \\ \tau_{j, applied} & = clip(\tau_{computed}, -\tau_{j, max}, \tau_{j, max})\end{split}\]

where, \(k_p\) and \(k_d\) are joint stiffness and damping gains, \(q\) and \(\dot{q}\) are the current joint positions and velocities, \(q_{des}\), \(\dot{q}_{des}\) and \(\tau_{ff}\) are the desired joint positions, velocities and torques commands. The parameters \(\gamma\) and \(\tau_{motor, max}\) are the gear box ratio and the maximum motor effort possible.

Actuator groups#

The actuator models by themselves are computational blocks that take as inputs the desired joint commands and output the joint commands to apply into the simulator. They do not contain any knowledge about the joints they are acting on themselves. These are handled by the omni.isaac.lab.assets.Articulation class, which wraps around the physics engine’s articulation class.

Actuator are collected as a set of actuated joints on an articulation that are using the same actuator model. For instance, the quadruped, ANYmal-C, uses series elastic actuator, ANYdrive 3.0, for all its joints. This grouping configures the actuator model for those joints, translates the input commands to the joint level commands, and returns the articulation action to set into the simulator. Having an arm with a different actuator model, such as a DC motor, would require configuring a different actuator group.

The following figure shows the actuator groups for a legged mobile manipulator:

Actuator models for a legged mobile manipulator Actuator models for a legged mobile manipulator

See also

We provide implementations for various explicit actuator models. These are detailed in omni.isaac.lab.actuators sub-package.