Hardware & control
Impedance control
Impedance control regulates the dynamic relationship between a robot’s motion error and the force or torque it exerts, usually by giving the robot virtual stiffness, damping and sometimes inertia. It lets an end effector or limb yield predictably during contact instead of trying to hold an exact position regardless of interaction forces.
Also known as: Robot impedance control, Mechanical impedance control
Updated
A controlled relationship, not one variable
Neville Hogan’s original impedance-control theory argues that manipulation cannot be described by controlling position or force alone: the robot and environment are mechanically coupled. The controller instead imposes a chosen relation between motion deviation and interaction force.
A virtual spring-damper is the common simple case. Its equilibrium pose sets where the robot tends to return, stiffness sets how strongly displacement is opposed, and damping resists relative velocity. A fuller impedance can include inertia, coupling between axes and nonlinear behaviour. The official libfranka Cartesian example maps Cartesian pose and velocity errors through stiffness, damping and the Jacobian to joint torques.
Impedance, admittance and position control
Direct impedance control commonly takes motion as input and produces force or torque. Admittance control takes measured force as input and produces a motion command, often for an inner position loop. An ICRA treatment of both implementations explains why their causality and contact behaviour differ, although some literature uses “impedance control” as the umbrella term.
A position controller may feel stiff, but that alone does not specify a desired mechanical impedance. The distinction matters when comparing controllers or judging how a robot should respond to a push.
What humanoid data must include
Humanoids may use different impedance along different axes, limbs and contact phases. A position trajectory therefore captures only the equilibrium motion, not the intended compliance.
Training records should include stiffness, damping and inertia parameters where used, their coordinate frame, equilibrium targets, torque output, measured wrench, contact state, saturation and update rate. Without them, two demonstrations with the same pose path but very different contact behaviour look falsely equivalent.
Sources
Related terms
Hardware & control
Torque control
Torque control is a control mode in which desired joint torques, or equivalent linear forces, are the command variables sent to a robot’s low-level actuators. Unlike position control, it does not directly command where each joint should be. Motion and contact instead emerge from the applied efforts, robot dynamics, feedback, constraints and any higher-level controller.
Hardware & control
End effector
An end effector is a task-specific device attached to a robot manipulator’s mechanical interface so the robot can act on its environment, such as a gripper, hand or welding tool. It is distinct from the wrist or mounting flange, and from the tool centre point, which is only a coordinate frame used to plan the device’s motion.
Hardware & control
Whole-body control
Whole-body control coordinates a humanoid’s full multibody state, actuated joints and environmental contacts to pursue several motion or force objectives while respecting constraints such as balance, joint limits and friction. It is a family of hierarchical or optimisation-based methods, not one algorithm; implementations may output joint positions, accelerations or torques.
Hardware & control
Proprioception
Proprioception is sensing of a robot’s own internal configuration and motion rather than the external scene. For a humanoid it commonly includes joint positions and velocities, actuator effort or torque, and inertial measurements of body rotation and acceleration. These signals support state estimation and feedback control but do not, by themselves, directly describe nearby objects or terrain.