Robotic paradigm

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In robotics, a robotic paradigm is a mental model of how a robot operates. A robotic paradigm can be described by the relationship between the three basic elements of robotics: Sensing, Planning, and Acting. It can also be described by how sensory data is processed and distributed through the system, and where decisions are made.

Contents

Hierarchical/deliberative paradigm

Hierarchical Paradigm schema Hierarchical.png
Hierarchical Paradigm schema

The reactive paradigm

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Reactive Paradigm schema

Hybrid deliberate/reactive paradigm

Hybrid Deliberate/Reactive Paradigm schema Hybrid Deliberate-Reactive Paradigm schema.png
Hybrid Deliberate/Reactive Paradigm schema

See also

Related Research Articles

Subsumption architecture is a reactive robotic architecture heavily associated with behavior-based robotics which was very popular in the 1980s and 90s. The term was introduced by Rodney Brooks and colleagues in 1986. Subsumption has been widely influential in autonomous robotics and elsewhere in real-time AI.

In computer science, a software agent is a computer program that acts for a user or other program in a relationship of agency, which derives from the Latin agere : an agreement to act on one's behalf. Such "action on behalf of" implies the authority to decide which, if any, action is appropriate. Agents are colloquially known as bots, from robot. They may be embodied, as when execution is paired with a robot body, or as software such as a chatbot executing on a phone or other computing device. Software agents may be autonomous or work together with other agents or people. Software agents interacting with people may possess human-like qualities such as natural language understanding and speech, personality or embody humanoid form.

Behavior-based robotics (BBR) or behavioral robotics is an approach in robotics that focuses on robots that are able to exhibit complex-appearing behaviors despite little internal variable state to model its immediate environment, mostly gradually correcting its actions via sensory-motor links.

Automated planning and scheduling, sometimes denoted as simply AI planning, is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space. Planning is also related to decision theory.

Perceptual control theory (PCT) is a model of behavior based on the properties of negative feedback control loops. A control loop maintains a sensed variable at or near a reference value by means of the effects of its outputs upon that variable, as mediated by physical properties of the environment. In engineering control theory, reference values are set by a user outside the system. An example is a thermostat. In a living organism, reference values for controlled perceptual variables are endogenously maintained. Biological homeostasis and reflexes are simple, low-level examples. The discovery of mathematical principles of control introduced a way to model a negative feedback loop closed through the environment, which differs fundamentally from theories of behaviorism and cognitive psychology which model stimuli as causes of behavior. PCT research is published in experimental psychology, neuroscience, ethology, anthropology, linguistics, sociology, robotics, developmental psychology, organizational psychology and management, and a number of other fields. PCT has been applied to design and administration of educational systems, and has led to a psychotherapy called the method of levels.

Decentralised system Systems without a single most important component or cluster

A decentralised system in systems theory is a system in which lower level components operate on local information to accomplish global goals. The global pattern of behaviour is an emergent property of dynamical mechanisms that act upon local components, such as indirect communication, rather than the result of a central ordering influence of a centralised system.

Intelligent agent Software agent which acts autonomously

In artificial intelligence, an intelligent agent (IA) is anything which perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or may use knowledge. They may be simple or complex — a thermostat is considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm, a state, or a biome.

Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behaviour in an agent environment. The term is also sometimes used in ethology or animal behavior.

In artificial intelligence, reactive planning denotes a group of techniques for action selection by autonomous agents. These techniques differ from classical planning in two aspects. First, they operate in a timely fashion and hence can cope with highly dynamic and unpredictable environments. Second, they compute just one next action in every instant, based on the current context. Reactive planners often exploit reactive plans, which are stored structures describing the agent's priorities and behaviour.

Nouvelle artificial intelligence (AI) is an approach to artificial intelligence pioneered in the 1980s by Rodney Brooks, who was then part of MIT artificial intelligence laboratory. Nouvelle AI differs from classical AI by aiming to produce robots with intelligence levels similar to insects. Researchers believe that intelligence can emerge organically from simple behaviors as these intelligences interacted with the "real world," instead of using the constructed worlds which symbolic AIs typically needed to have programmed into them.

A hierarchical control system (HCS) is a form of control system in which a set of devices and governing software is arranged in a hierarchical tree. When the links in the tree are implemented by a computer network, then that hierarchical control system is also a form of networked control system.

Glossary of robotics List of definitions of terms and concepts commonly used in the study of robotics

Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots. Robotics is related to the sciences of electronics, engineering, mechanics, and software.

4D-RCS Reference Model Architecture Reference model for military unmanned vehicles to identify and organize their software components

The 4D/RCS Reference Model Architecture is a reference model for military unmanned vehicles on how their software components should be identified and organized.

Real-time Control System

Real-time Control System (RCS) is a reference model architecture, suitable for many software-intensive, real-time computing control problem domains. It defines the types of functions needed in a real-time intelligent control system, and how these functions relate to each other.

The following outline is provided as an overview of and topical guide to robotics:

In artificial intelligence research, the situated approach builds agents that are designed to behave effectively successfully in their environment. This requires designing AI "from the bottom-up" by focussing on the basic perceptual and motor skills required to survive. The situated approach gives a much lower priority to abstract reasoning or problem-solving skills.

Winner-take-all is a computer science concept that has been widely applied in behavior-based robotics as a method of action selection for intelligent agents. Winner-take-all systems work by connecting modules in such a way that when one action is performed it stops all other actions from being performed, so only one action is occurring at a time. The name comes from the idea that the "winner" action takes all of the motor system's power.

Behavior tree (artificial intelligence, robotics and control)

A behavior tree is a mathematical model of plan execution used in computer science, robotics, control systems and video games. They describe switchings between a finite set of tasks in a modular fashion. Their strength comes from their ability to create very complex tasks composed of simple tasks, without worrying how the simple tasks are implemented. Behavior trees present some similarities to hierarchical state machines with the key difference that the main building block of a behavior is a task rather than a state. Its ease of human understanding make behavior trees less error prone and very popular in the game developer community. Behavior trees have been shown to generalize several other control architectures. Mathematically, they are directed acyclic graphs.

Genghis (robot) Early six legged insect-like robot from the 1970s

Genghis was a six legged insect-like robot that was created by roboticist Rodney Brooks at MIT. Brooks wanted to solve the problem of how to make robots intelligent and suggested that it is possible to create robots that displayed intelligence by using a "subsumption architecture" which is a type of reactive robotic architecture where a robot can react to the world around them. His paper "Intelligence Without Representation", which is still widely respected in the fields of robotics and Artificial Intelligence, further outlines his theories on this.

GOLOG is a high-level logic programming language for the specification and execution of complex actions in dynamical domains. It is based on the situation calculus. It is a first-order logical language for reasoning about action and change. GOLOG was developed at the University of Toronto.

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