Machines That Learn
The vocabulary of AI and robotics, kept precise.
What does AI stand for?
A robot is a loop: sense the world, decide something, move. These ten questions are about the sensing and the moving.
Most of what makes robotics hard has nothing to do with intelligence. A machine has to know where its own limbs are, where the floor is, and what will happen if it pushes. Every one of those facts arrives through a sensor with noise in it, and every response goes out through an actuator that lags behind the command. The discipline that grew up around closing that gap, control theory, is older than the computer. The questions here cover the physical vocabulary: what an actuator is, why an arm is described by its degrees of freedom, how a machine builds a map of a room it has never seen. The explanations note where a neat-sounding term hides a genuinely unsolved problem, which in robotics is often.
Every question in this quiz is listed below with its correct answer and the reasoning behind it. Play first if you would rather not see the answers — or read through as a study sheet.
Play it insteadAnswer: D. Converts a control signal into physical movement
Why: Electric motors, hydraulic cylinders and pneumatic pistons are all actuators. Sensors run the other way, turning a physical quantity into a signal.
Answer: C. The number of independent ways it can move
Why: A human arm from shoulder to wrist has seven. Six is the minimum needed to place a tool at any position and any angle within reach.
Answer: B. The end effector
Why: Grippers, welding torches and paint sprayers are all end effectors. Being able to swap them is what lets one arm cover several jobs on a line.
Answer: A. Timing pulses of laser light reflected from surfaces
Why: The word is usually expanded as light detection and ranging. Sonar does the same job with sound and radar with radio waves.
Answer: D. Uses measurements of the output to adjust the input
Why: A thermostat is the everyday example, switching heating against a measured temperature. Control theory grew out of steam governors, long before electronics.
Answer: C. Simultaneous localisation and mapping
Why: The machine builds a map of an unknown space while working out its own position within it. Robot vacuum cleaners run simplified versions of the same idea.
Answer: B. A fast, powerful arm cannot tell that a person is in its path
Why: They move to fixed positions at speed regardless of what is there. Collaborative robots run slower and stop on contact so they can share floor space with people.
Answer: A. Reports and controls its own shaft position
Why: A position sensor and a small controller are built into it, so the shaft turns to a commanded angle and holds there. Stepper motors reach similar precision by moving in fixed increments instead.
Answer: D. Humanlike figures becoming unsettling as they approach realism
Why: Masahiro Mori proposed the idea in 1970. It is now applied as often to animated characters as to physical robots.
Answer: C. It stays upright even if it stops in mid-stride
Why: That requires keeping its centre of mass above the area covered by its feet. Human walking is closer to controlled falling, with balance recovered at each step.
Stripped of the vocabulary, it is pattern-finding in data. What follows from that, including the failures.
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