Every robot has a controller, which continuously reads from sensors like motor encoders, force sensors, or even vision or depth sensors, and updates the actuator commands so as to achieve the desired robot behavior. Examples of control objectives include motion control, as when a robot arm moves along a specified trajectory; force control, where the objective is to apply specific forces to an object or the environment; hybrid motion-force control, as when writing on a board: you control the motion in the plane of the board but the force into the board; and impedance control, as when a robot is used to render a virtual environment. In this case, the user grabs the end-effector of the robot and moves it around to explore objects in a virtual world, which could be displayed to the user as masses, springs, or dampers.

If the robot is a robot arm driven by electric motors, this is a typical electromechanical block diagram. A power supply takes AC power from the wall and delivers DC power to motor amplifiers. The controller takes as input a desired motion from the user and sensor feedback from the robot. At a rate of perhaps a thousand times per second, the controller evaluates a control law and requests joint torques from each motor amplifier. At each joint, the amplifier sends a current to the motor to achieve the desired torque, since the torque of an electric motor is proportional to the current. Typically a current sensor senses the actual current, and the amplifier updates its signal to better achieve the current needed to generate the desired torque. These inner control loops can run tens of thousands of times per second. Some robot joints have torque sensors embedded in the actuators themselves, and this feedback is used in the local torque control loop.

Finally, the motors are coupled to each other through the dynamics of the arm, and the actual motion of the robot is measured by the encoders. The measured motion is sent to the controller. This is a block diagram of the robot control system. The controller produces low-power signals telling the amplifiers what to do; the amplifiers send high-power current through the motors, which produce the forces and torques that drive the robot. The robot's motion and forces are measured by sensors that send the measurements back to the controller. We call this closed-loop control because of the sensor feedback.

It's also common to model force disturbances and sensor errors as being inserted into the control loop. In this chapter, though, we will simplify our analysis by assuming that the amplifiers and actuators work perfectly to generate the control forces requested by the controller and that the sensors measure the robot's performance perfectly. We also ignore the fact that the controller is typically implemented at a finite frequency and instead assume that control laws are implemented in continuous time. Then our block diagram can be simplified to this block diagram, consisting of only the controller and the dynamics blocks. Chapter 8 covered the dynamics of a robot. In this chapter, we will derive the control laws that drive a robot. We begin this process in the next video by introducing the notion of error dynamics.