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Autonomous Systems > Glossary A-M > Flashcards

Glossary A-M Flashcards

1
Q

Achievement Goal

A

A state the system tries to reach, such as the end of a maze.

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2
Q

Actuator

A

The mechanism that enables an effector to execute an action or movement.

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3
Q

Actuator uncertainty

A

Not being able to know the exact outcome of an action ahead of time, even for a simple action such as “go forward three feet”.

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4
Q

Amplifying

A

Something that causes an increase in size, volume, or significance.

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5
Q

Artificial intelligence (AI)

A

The field that studies how intelligent machines (should) think. AI was officially “born” in 1956 at a conference held at Dartmouth University, in Hanover, New Hampshire.

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6
Q

Assistive robotics

A

Robot systems capable of helping people with special needs, such as individuals covalescing from an illness, rehabilitating from an accident or trauma, learning or training in a special setting, or aging at home or in a managed care facility.

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7
Q

Autonomy

A

The ability to make one’s own decisions and act on them.

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8
Q

Behavioral coordination

A

Deciding what behavior or set of behaviors should be executed at a given time.

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9
Q

Bit

A

The fundamental unit of information, which has two possible values: the binary digits 0 and 1; the word come from “binary digit”.

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10
Q

Bottom-up

A

Progression from the simpler to the more complex.

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11
Q

Broadcast communication

A

Sending a message to everyone on the communication channel.

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12
Q

Calibration

A

The process of adjusting a mechanism to maximize its performance (accuracy, range, etc.)

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13
Q

Cartesian robots

A

Robots that are similar in principle to cartesian plotter printer, and are usually used for high-precision assembly tasks.

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14
Q

Command arbitration

A

The process of selecting one action or behavior from multiple possibilities.

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15
Q

Continuous state

A

State that is expressed as a continuous function (50 km/h)

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16
Q

Control architecture

A

A set of guiding principles and constraints for organizing a robot’s control system.

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17
Q

Cooperation

A

Joint action with a mutual benefit.

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18
Q

Coordination

A

Arranging things in some kind of order (ord and ordin mean order in Latin).

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19
Q

Cybernetics

A

A field of study that was inspired by biological systems, from the level of neurons (nerve cells) to the level of behavior, and tried to implement similar principles in simple robots, using methods from control theory.

  • > A study and comparison of communication and control processes in biological and artificial systems.
  • > Machines use similar steersman to produce sophisticated behavior similar to nature
  • > lead to the Walter’s tortoises
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20
Q

Damping

A

The process of systematically decreasing oscillations.

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21
Q

Data association problem

A

The problem of uniquely associating the sensed data with absolute ground truth.

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22
Q

Degrees of freedom

A

The dimensions in which a manipulator can move.

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23
Q

Deliberative control

A

Type of control that looks into the future, so it works on a long time-scale.

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24
Q

Demodulator

A

A mechanism that is tuned to the particular frequency of the modulation, so it can be decoded.

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25
Q

Desired state + synonym

A

The state the system wants to be in also called the goal state.

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26
Q

Detector

A

A mechanism that perceives (detects) a property to be measured.

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27
Q

Differential drive

A

The ability to drive wheels separately and independently, through the use of seperate motors.

28
Q

Diffuse reflection

A

Light that penetrates into the object, is absorbed, and then comes back out

29
Q

Discrete state

A

Different and separate state of a system (from the Latin discretus meaning “separate”), such as down , blue and red.

30
Q

Dynamics

A

The study of the effects of forces on the motion of objects.

31
Q

Effector

A

Any device on a robot that has an effect (impact, influence) on the environment.

32
Q

Embodiment

A

Having a physical body.

33
Q

Emitter

A

A mechanism that produces (emits) a signal.

34
Q

Error

A

The difference between a desired value and the measured value.

35
Q

Exo-skeleton

A

The outer skeleton (from the Greek ex meaning “outside”)

36
Q

External state

A

The state of the world, as the robot can perceive it (it is dark).

37
Q

Internal state

A

The state of the robot, as the robot can perceive it (my battery is low).

38
Q

Exteroception

A

The process of sensing the world around the robot, not including sensing the robot itself.

39
Q

Feedback

A

The information that is sent back, literally “fed back”, into the system’s controller.

40
Q

Fixed hierarchies

A

Hierarchies whose ordering does not change, like royal families where the order of power is determined by heredity.

41
Q

Focus

A

A point toward which light rays are made to converge.

42
Q

Foraging

A

The process of finding and collecting certain items from some specified area, such as harvesting a crop or removing trash from a stretch of highway.

43
Q

Fusion

A

The process of combining multiple possible possibilities into a single result.

44
Q

Grasp points

A

Locations where the fingers or grippers should be placed in order to best grasp an object. Grasp points are computed relative to the centre of gravity, friction, location of obstacles, etc.

45
Q

Goal state

A

The state the system wants to be in, also called the desired state.

46
Q

Haptics

A

The study of the sense of touch.

47
Q

Heuristics

A

Rules of thumb that help guide and hopefully speed up the search.

48
Q

Hierarchies

A

Groups or organizations that are ordered by power.

49
Q

Holonomic

A

Being able to controll all available degrees of freedom (DOF)

50
Q

Human-robot interaction (HRI)

A

A new field of robots focusing on the challenges of perceiving and understanding human behavior in real-time (who is that talking to me, what is she saying, is she happy or sad, is she getting closer or moving away), responding in real-time (what should I say? What should I do?), and doing so in a socially appropriate and natural way that engages the human participant.

51
Q

Hybrid control

A

Approaches to control that combine the long time-scale of deliberative control and the short time-scale of reactive control, with some cleverness in between.

52
Q

Image plane

A

The projection of the world onto the camera image; it corresponds to the retina of the biologicak eye.

53
Q

Inhibitrory connection

A

A connection in which the stronger the sensory input, the weaker the motor output.

54
Q

Inverse pendulum problem

A

Controlling a system that is like an upside-down pendulum, such as balancing in one-legged robots.

55
Q

Joint limit

A

The extreme of how far a joint can move.

56
Q

Kinematics

A

The correspondence between actuator motion and the resulting effector motion.

57
Q

Lens

A

The structure that refracts the light to focus it on the retina or image plane.

58
Q

Level of abstraction

A

Level of detail.

59
Q

Life-long learning

A

The idea of having a robot learn continually as long as it is functional.

60
Q

Linear actuator

A

An actuator that provides linear movement, such as getting longer or shorter.

61
Q

Maintenance goal

A

A goal that requires ongoing active work on the part of the system, such as “keeping away from obstacles”.

62
Q

Manipulation

A

Any goal-driven movement of a manipulator.

63
Q

Manipulator

A

A robotic manipulator is an effector.

64
Q

Manipulator links

A

Individual components of the manipulator.

65
Q

Model-based vision

A

An approach to machine vision which uses models of objects (prior information or knowledge about those objects) represented and stored in a way that allows comparison and recognition.

Autonomous Systems (10 decks)

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