Autoplay of the YouTube playlist for all videos in this chapter.  This description box will not be updated with information about each video as the videos advance.

This video introduces different robot control objectives (motion control, force control, hybrid motion-force control, and impedance control) and typical block diagram models of controlled robots.

This video introduces the error response for a controlled system and characterizes the error response in terms of its steady-state error and its transient response (overshoot and settling time).

This video introduces linear error response, where the error dynamics are represented by a linear ordinary differential equation, which can also be represented as a set of coupled first-order differential equations, xdot = Ax. Stability of the error dynamics is achieved if the real components of the eigenvalues of A are all negative, or, equivalently,

This video studies error dynamics modeled as a first-order linear ordinary differential equation.

This video studies error dynamics modeled as a second-order linear ordinary differential equation. Stable error dynamics are characterized as overdamped, critically damped, or underdamped.

This video introduces proportional (P) control of the position of a single-degree-of-freedom system where the control input is a velocity.

This video introduces proportional-integral (PI) control of the position of a single-degree-of-freedom system, and feedforward plus PI feedback control, for the case where the desired position is a ramp as a function of time (constant velocity) and the control input is the velocity. The approach generalizes easily to the control of a multi-degree-of-freedom robot.

This video addresses task-space motion control of a robot, where the control inputs are the joint velocities and the desired motion of the end-effector is expressed as its configuration X in SE(3) and the end-effector velocity is expressed as a twist. The proposed control method is a feedforward plus PI feedback controller.

This video introduces proportional-integral-derivative (PID) control for a single robot joint, as well as PD control to a desired constant position, for the case where the control input is a joint torque or force.

This video compares PD vs. PID control for setpoint control of a single robot joint moving in gravity, where the control input is a torque.

This video introduces the computed-torque motion control method for robots, where the control inputs are torques or forces. The controller is defined both in joint space as well as task space.

This video describes Jacobian-transpose-based force control for a robot, both with and without end-effector force-torque feedback.

This video introduces hybrid motion-force control: controlling a robot to generate desired motions in unconstrained directions and desired forces in constrained directions.