Robotics

Robotics

What is Robotics?

• Roboticists develop man-made mechanical devices that can move by themselves, whose motion must be modelled, planned, sensed, actuated and controlled, and whose motion behaviour can be influenced by “programming”.
•  Robots are called “intelligent” if they succeed in moving in safe interaction with an unstructured environment, while autonomously achieving their specified tasks.
• This definition implies that a device can only be called a “robot” if it contains a movable mechanism, influenced by sensing, planning, actuation and control components. 

• It does not imply that a minimum number of these components must be implemented in software, or be changeable by the “consumer” who uses the device; for example, the motion behaviour can have been hard-wired into the device by the manufacturer.

• Robotics is, to a very large extent, all about system integration, achieving a task by an actuated mechanical device, via an “intelligent” integration of components, many of which it shares with other domains, such as systems and control, computer science, character animation, machine design, computer vision, artificial intelligence, cognitive science, biomechanics, etc. 
• In addition, the boundaries of robotics cannot be clearly defined, since also its “core” ideas, concepts and algorithms are being applied in an ever increasing number of “external” applications, and, vice versa, core technology from other domains are becoming crucial components in more and more modern robotic systems.

Components of  Robotic Systems

• The purpose of this Section is to describe the semantics of the terminology used to classify : “sensing”, “planning”, “modelling”, “control”, etc.
• The real robot is some mechanical device (“mechanism”) that moves around in the environment, and, in doing so, physically interacts with this environment. This interaction involves the exchange of physical energy, in some form or another. Both the robot mechanism and the environment can be the “cause” of the physical interaction through “Actuation”, or experience the “effect” of the interaction, which can be measured through “Sensing”.

• Robotics as an integrated system of control interacting with the physical world.
• Sensing and actuation are the physical ports through which the “Controller” of the robot determines the interaction of its mechanical body with the physical world. 
• As mentioned already before, the controller can, in one extreme, consist of software only, but in the other extreme everything can also be implemented in hardware.
• Within the Controller component, several sub-activities are often identified:
• Modelling. The input-output relationships of all control components can (but need not) be derived from information that is stored in a model. This model can have many forms: analytical formulas, empirical look-up tables, fuzzy rules, neural networks, etc.

Planning. This is the activity that predicts the outcome of potential actions, and selects the “best” one. Almost by definition, planning can only be done on the basis of some sort of model.

Regulation. This component processes the outputs of the sensing and planning components, to generate an actuation setpoint. Again, this regulation activity could or could not rely on some sort of (system) model.

The term “control” is often used instead of “regulation”, but it is impossible to clearly identify the domains that use one term or the other. The meaning used in the WEBook will be clear from the context.

Scales in robotic systems

Mechanical scale. The physical volume of the robot determines to a large extent the limites of what can be done with it. Roughly speaking, a large-scale robot has different capabilities and control problems than a macrorobot, a desktop robot, or milli micro or nano robots. 

Spatial scale. There are large differences between robots that act in 1D, 2D, 3D, or 6D.

Time scale. There are large differences between robots that must react within hours, seconds, milliseconds, or microseconds.

Power density scale. A robot must be actuated in order to move, but actuators need space as well as energy, so the ratio between both determines some capabilities of the robot.

System complexity scale. The complexity of a robot system increases with the number of interactions between independent sub-systems, and the control components must adapt to this complexity.

Computational complexity scale. Robot controllers are inevitably running on real-world computing hardware, so they are constrained by the available number of computations, the available communication bandwidth, and the available memory storage.