Cognitive Robotics or Cognitive Technology is a subfield of

robotics Robotics is an interdisciplinary branch of computer science and engineering. Robotics involves design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrat ...

concerned with endowing a robot with intelligent behavior by providing it with a processing architecture that will allow it to

learn Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed by humans, animals, and some machines; there is also evidence for some kind of learn ...

and reason about how to behave in response to complex goals in a complex world. Cognitive robotics may be considered the engineering branch of

embodied cognitive science Embodied cognitive science is an interdisciplinary field of research, the aim of which is to explain the mechanisms underlying intelligent behavior. It comprises three main methodologies: the modeling of psychological and biological systems in a ...

and

embodied embedded cognition Embodied embedded cognition (EEC) is a philosophical theoretical position in cognitive science, closely related to situated cognition, embodied cognition, embodied cognitive science and dynamical systems theory. The theory states that intellige ...

, consisting of

Robotic Process Automation Robotic process automation (RPA) is a form of business process automation technology based on metaphorical software robots (bots) or on artificial intelligence (AI)/digital workers. It is sometimes referred to as ''software robotics'' (not to be ...

Artificial Intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech re ...

Machine Learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...

Deep Learning Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. De ...

Optical Character Recognition Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scen ...

Image Processing An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensiona ...

Process Mining Process mining is a family of techniques relating the fields of data science and process management to support the analysis of operational processes based on event logs. The goal of process mining is to turn event data into insights and actions. ...

Analytics Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making. It ...

Software Development Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components. Software development invol ...

and

System Integration System integration is defined in engineering as the process of bringing together the component sub- systems into one system (an aggregation of subsystems cooperating so that the system is able to deliver the overarching functionality) and ensuring ...

Core issues

While traditional

cognitive model A cognitive model is an approximation of one or more cognitive processes in humans or other animals for the purposes of comprehension and prediction. There are many types of cognitive models, and they can range from box-and-arrow diagrams to a set ...

ing approaches have assumed symbolic coding schemes as a means for depicting the world, translating the world into these kinds of symbolic representations has proven to be problematic if not untenable.

Perception Perception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system ...

and

action Action may refer to: * Action (narrative), a literary mode * Action fiction, a type of genre fiction * Action game, a genre of video game Film * Action film, a genre of film * ''Action'' (1921 film), a film by John Ford * ''Action'' (1980 fil ...

and the notion of symbolic representation are therefore core issues to be addressed in cognitive robotics.

Starting point

Cognitive robotics views human or animal cognition as a starting point for the development of robotic information processing, as opposed to more traditional

techniques. Target robotic cognitive capabilities include perception processing, attention allocation,

anticipation Anticipation is an emotion involving pleasure or anxiety in considering or awaiting an expected event. Anticipatory emotions include fear, anxiety, hope and trust. When the anticipated event fails to occur, it results in disappointment (if posit ...

, planning, complex motor coordination, reasoning about other agents and perhaps even about their own mental states. Robotic cognition embodies the behavior of

intelligent agent 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 c ...

s in the physical world (or a virtual world, in the case of simulated cognitive robotics). Ultimately the robot must be able to act in the real world.

Learning techniques

Motor Babble

A preliminary robot learning technique called motor babbling involves correlating pseudo-random complex motor movements by the robot with resulting visual and/or auditory feedback such that the robot may begin to ''expect'' a pattern of sensory feedback given a pattern of motor output. Desired sensory feedback may then be used to inform a motor control signal. This is thought to be analogous to how a baby learns to reach for objects or learns to produce speech sounds. For simpler robot systems, where for instance

inverse kinematics In computer animation and robotics, inverse kinematics is the mathematical process of calculating the variable joint parameters needed to place the end of a kinematic chain, such as a robot manipulator or animation character's skeleton, in a g ...

may feasibly be used to transform anticipated feedback (desired motor result) into motor output, this step may be skipped.

Imitation

Once a robot can coordinate its motors to produce a desired result, the technique of ''learning by imitation'' may be used. The robot monitors the performance of another agent and then the robot tries to imitate that agent. It is often a challenge to transform imitation information from a complex scene into a desired motor result for the robot. Note that imitation is a high-level form of cognitive behavior and imitation is not necessarily required in a basic model of embodied animal cognition.

Knowledge acquisition

A more complex learning approach is "autonomous knowledge acquisition": the robot is left to explore the environment on its own. A system of goals and beliefs is typically assumed. A somewhat more directed mode of exploration can be achieved by "curiosity" algorithms, such as Intelligent Adaptive Curiosity or Category-Based Intrinsic Motivation. These algorithms generally involve breaking sensory input into a finite number of categories and assigning some sort of prediction system (such as an

Artificial Neural Network Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected unit ...

) to each. The prediction system keeps track of the error in its predictions over time. Reduction in prediction error is considered learning. The robot then preferentially explores categories in which it is learning (or reducing prediction error) the fastest.

Other architectures

Some researchers in cognitive robotics have tried using architectures such as (

ACT-R ACT-R (pronounced /ˌækt ˈɑr/; short for "Adaptive Control of Thought—Rational") is a cognitive architecture mainly developed by John Robert Anderson and Christian Lebiere at Carnegie Mellon University. Like any cognitive architecture, ACT-R ...

and

Soar (cognitive architecture) Soar is a cognitive architecture, originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University. (Rosenbloom continued to serve as co-principal investigator after moving to Stanford University, then to the Uni ...

) as a basis of their cognitive robotics programs. These highly modular symbol-processing architectures have been used to simulate operator performance and human performance when modeling simplistic and symbolized laboratory data. The idea is to extend these architectures to handle real-world sensory input as that input continuously unfolds through time. What is needed is a way to somehow translate the world into a set of symbols and their relationships.

Questions

Some of the fundamental questions to still be answered in cognitive robotics are: * How much human programming should or can be involved to support the learning processes? * How can one quantify progress? Some of the adopted ways is the reward and punishment. But what kind of reward and what kind of punishment? In humans, when teaching a child for example, the reward would be candy or some encouragement, and the punishment can take many forms. But what is an effective way with robots?

Books

Cognitive Robotics book by Hooman Samani, takes a multidisciplinary approach to cover various aspects of cognitive robotics such as artificial intelligence, physical, chemical, philosophical, psychological, social, cultural, and ethical aspects.

References

The Symbolic and Subsymbolic Robotic Intelligence Control System (SS-RICS)The Cognitive Robotics Group - University of Toronto
* The

IDSIA The Dalle Molle Institute for Artificial Intelligence Research ( it, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, italic=no, IDSIA) is a research institution based in Lugano, in Canton Ticino in southern Switzerland. It was found ...

br>Robotics Lab
an

of Juergen Schmidhuber
What Does the Future Hold for Cognitive Robots? - Idaho National LaboratoryCognitive Robotics at the Naval Research LaboratoryCognitive robotics at ENSTA
autonomous embodied systems, evolving in complex and non-constraint environments, using mainly vision as sensor.
The Center for Intelligent Systems - Vanderbilt UniversityInstitute for Cognition and Robotics (CoR-Lab) at Bielefeld UniversitySocioCognitive Robotics at Delft University of TechnologyAutonomous Systems Laboratory at Universidad Politecnica de MadridKnowledge Technology at Universität HamburgThe Cognitive Robotics Association
founded in 1998, directed by Gerhard Lakemeyer, University of Aachen, organizes every two years the Cognitive Robotics Workshop and it is generously supported b
the AI journal

External links

iCub iCub is a 1 metre tall open source robotics humanoid robot testbed for research into human cognition and artificial intelligence. It was designed by the RobotCub Consortium of several European universities and built by Italian Institute of ...

RoboBusiness: Robots that Dream of Being Better

The cognitive Robotics Association
{{Robotics Robotics Machine learning