Cognitive Robotics

Total Page:16

File Type:pdf, Size:1020Kb

Cognitive Robotics Cognitive Robotics: Analysis of Preconditions and Implementation of a Cognitive Robotic System for Navigation Tasks Stefano Bennati [[email protected]] Universita` degli Studi di Brescia Brescia, Italy Marco Ragni [[email protected]] Department of Cognitive Science, Friedrichstrasse 50 Freiburg 79098, Germany Abstract Cognitive robotics is a fascinating field in its own right and comprises both key features of autonomicity and cognitive skills like learning behavior. Cognitive architectures aim at mirroring human memory and assumptions about mental pro- cesses. A robot does not only extend the cognitive architecture regarding real-world interaction but brings new and important challenges regarding perception and action processes. Cog- nitive robotics is a step towards embodied cognition and may have influences not only on cognitive science but on robotics as well. This paper presents an integration of the cognitive archi- tecture ACT-R on a simple but programmable robotic system. This system is evaluated on a navigation experiment. Keywords: Cognitive Science; Robotics; Mindstorms; ACT- R; Navigation Introduction From the early beginning of robotics one line of research has tried to bring human cognition and robotics closer together Figure 1: Layouts of two mazes: The task is to find the target Brooks et al., 1999. Nowadays, technological progress in the object (red dot) at the edge or center Buechner et al., 2009. field of robotics and the development of cognitive architec- tures allows for a leap forward: A robot able to navigate an Modeling navigation tasks, for instance in labyrinths, still environment, with the ability to learn and a human-like atten- poses a challenge for cognitive architectures: Although they tion shift. can model decision processes they typically abstract from This new and exciting field is sometimes referred to as metrical details of the world, from sensor-input, and from the Cognitive Robotics 1. This combination of two fields leads to integration processes of environmental input to actions (like a number of important research questions: What are the im- move operations). Robotics, on the other hand, has typically mediate advantages of cognitive robotics (a term we will use captured all of these aspects, but does not necessarily make in the following for a robot controlled by a cognitive archi- use of human-like learning and reasoning processes or even tecture) over classical robotics? Is the cognitive architecture try to explain human errors or strategies. (which partially is able to simulate human learning processes) restricting or improving navigation skills? In cognitive sci- Compared to humans a robotic agent has limited percep- ence new research focuses on embodied cognition. tions and capabilities. On the other hand, it can teach us Embodied cognition claims that understanding (especially something about the relevant perceptions that are already suf- of spatial problems) is derived from the environment Ander- ficient for the robotic agent to perform successfully. For in- son, 2003. In other words, cognition is not independent on its stance, in the navigation task above (e.g., cp. Fig. 1), the physical realization. The study described in Buechner et al., distance from the wall (in the direction it is facing) and the 2009 used a virtual reality environment. Participants had to color of the floor the robot is standing on are sufficient. navigate through a labyrinth in the ego-perspective and had Much research is being done in the field of the cognitive to find an initially specified goal (red dot). The study identi- robotics; some prototypes of cognitive robots have already 2 fied recurrent navigation strategies (which we introduce later) been built . This research concentrates on the human-robot used by the subjects. and robot-environment interaction, allowing the robots to rec- 1”Towards a Cognitive Robotics”, Clark, Andy https://www. 2e.g., Cognitive Robotics with the architecture ACT-R/E http: era.lib.ed.ac.uk/handle/1842/1297 //www.nrl.navy.mil/aic/iss/aas/CognitiveRobots.php 157 ognize and interact with objects and people through their vi- sual and auditory modules Sofge et al., 2004. The architec- ture proposed contains Path Planning and Navigation rou- tines based on the Vector Field Histogram Borenstein and Ko- ren, 1991 that allow the robot to navigate avoiding obstacles and explore the environment. Unlike the architecture pro- posed, the objective of this paper is to implement a Cognitive Navigation System which is completely based on ACT-R and takes advantage of its cognitive features like Utility Learn- ing, that allows Reinforcement Learning Russell and Norvig, Figure 2: The Mindstorms class robot. It is equipped with a 2003, p.771 on productions. No other softwares than ACT-R color, ultrasonic and two touch sensors. will be used to control the robot. That experiment has the merit of have taken the first steps towards interfacing ACT-R with a mobile robot, but the data is still incomplete and tries Chassis design. The chassis is the structure to which the to combine as many different abilities as possible (from nat- central brick, the motors and the sensors are attached. To limit ural language processing, to parallel computing) in a manner odometry errors two fixed, independent driving wheels have that is likely more complex than necessary. Our approach been used, instead of caterpillar tracks. A third central fixed starts at the other end, taking only those aspects and sen- idle wheel allows the robot to keep its balance. The struc- sor data into account that are necessary to perform the task ture resembles a differential drive robot, with the exception – the most simple robot. Other research studied the possi- that the third wheel cannot pivot. Removing the tire from the bility of interfacing ACT-R with a robot and giving it direct wheel allows the robot to turn without too many difficulties. control over the robot’s actions. That effort produced an ex- tension of ACT-R called ACT-R/E(mbodied) Trafton, 2009; Sensors. A robot can be equipped with several kinds of sen- Harrison and Trafton, 2010. ACT-R/E contains some new sors: from a simple sound or light sensor, to more complex modules that act as an interface between the cognitive model ones like a compass or webcam. Our design makes use only and the Mobile-Dexterous-Social (MDS) robot Breazeal et al., of the most basic sensors: a touch sensor activated by pres- 2008, allowing it to perceive the physical world through a sure, a color sensor capable of recognizing light intensity or video camera. However, no navigation was investigated, as six tonalities of color, and an ultrasonic sensor for distance the robot did not navigate an environment. In both this and measurements. The color sensor and the ultrasonic sensor our implementation ACT-R has been extended. The vast dif- are fixed to the front, while a touch sensor is placed on each ference between the two is the smaller amount of changes side. Both touch sensors are linked to a structure that covers made to the standard ACT-R by our implementation, due to the front of the robot on that side. They are not used during the sensors’ higher complexity in the MDS. navigation but to stop the robot when it touches a wall. Consequently this article investigates, first, how to control a robot through ACT-R and, second, if this cognitive robot Integrating Architecture and Robot shows human-like behavior while navigating and searching The first step towards a cognitive robot is to create a working for a goal, e.g., an exit from the maze. The paper is structured interface between the ACT-R framework and the NXT plat- in three parts: The first part – The Elements – contains a brief form. This interface allows an ACT-R model to control the description of ACT-R, the robot and its features. The second robot and to receive sensor inputs from the robot. Due to the part – the Integration – describes the software that connects modular structure of ACT-R, this interface is composed of ACT-R with the robot, through which perceptions can reach modules. the cognitive architecture and actions the actuators. The third part – the Evaluation – tests the robot on a navigation task and analyzes the results. Low level lisp function. On the basis of these modules The Elements there is a library called nxt-lsp Hiraishi, 2007 that provides low-level lisp functions to execute simple tasks like interro- The Robotic System gate a sensor or move a motor. The capabilities of this library are the following: it can read information about the environ- Our device of choice is a standard Mindstorms3 class robot ment from the light sensor, the distance sensor and the touch (cf. Fig. 2). It consists of a central “brick” that contains the sensor; it can make the robot perform some actions, like move processor and the batteries. At this core component several its motors, turn on and off the light and play some sounds; it peripherals can be attached. It supports up to three step-to- can also check the robot’s internal state, querying the battery step engines and up to four sensors. or the motors about their states. The library did not have the support for the color sensor, so it has been extended to sup- 3This type of robot is produced by The Lego Group port that sensor, necessary for our purposes, as well. 158 Extending ACT-R Evaluation: Navigation in a Labyrinth The interface is composed by several modules with different We decided to test the cognitive robot on several self-built functions, this step has been taken to keep things simple and labyrinths. The environment is perceived by the robot to follow the general design of ACT-R.
Recommended publications
  • Current Advances in Cognitive Robotics Amir Aly, Sascha Griffiths, Francesca Stramandinoli
    Towards Intelligent Social Robots: Current Advances in Cognitive Robotics Amir Aly, Sascha Griffiths, Francesca Stramandinoli To cite this version: Amir Aly, Sascha Griffiths, Francesca Stramandinoli. Towards Intelligent Social Robots: Current Advances in Cognitive Robotics . France. 2015. hal-01673866 HAL Id: hal-01673866 https://hal.archives-ouvertes.fr/hal-01673866 Submitted on 1 Jan 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Proceedings of the Full Day Workshop Towards Intelligent Social Robots: Current Advances in Cognitive Robotics in Conjunction with Humanoids 2015 South Korea November 3, 2015 Amir Aly1, Sascha Griffiths2, Francesca Stramandinoli3 1- ENSTA ParisTech – France 2- Queen Mary University – England 3- Italian Institute of Technology – Italy Towards Emerging Multimodal Cognitive Representations from Neural Self-Organization German I. Parisi, Cornelius Weber and Stefan Wermter Knowledge Technology Institute, Department of Informatics University of Hamburg, Germany fparisi,weber,[email protected] http://www.informatik.uni-hamburg.de/WTM/ Abstract—The integration of multisensory information plays a processing of a huge amount of visual information to learn crucial role in autonomous robotics. In this work, we investigate inherent spatiotemporal dependencies in the data. To tackle how robust multimodal representations can naturally develop in this issue, learning-based mechanisms have been typically used a self-organized manner from co-occurring multisensory inputs.
    [Show full text]
  • Psychological Aspect of Cognitive Robotics
    VI Psychological Aspect of Cognitive Robotics 169 CHAPTER 9 Robotic Action Control: On the Crossroads of Cognitive Psychology and Cognitive Robotics Roy de Kleijn Leiden Institute for Brain and Cognition, Leiden University, The Netherlands. George Kachergis Leiden Institute for Brain and Cognition, Leiden University, The Netherlands. Bernhard Hommel Leiden Institute for Brain and Cognition, Leiden University, The Netherlands. CONTENTS 9.1 Early history of the fields .................................... 172 9.1.1 History of cognitive psychology .................... 172 9.1.2 The computer analogy ............................... 173 9.1.3 Early cognitive robots ................................ 174 9.2 Action control ................................................. 174 9.2.1 Introduction ........................................... 175 9.2.2 Feedforward and feedback control in humans ..... 175 9.2.3 Feedforward and feedback control in robots ....... 176 9.2.4 Robotic action planning .............................. 177 9.3 Acquisition of action control ................................. 178 9.3.1 Introduction ........................................... 178 9.3.2 Human action-effect learning ....................... 179 171 172 Cognitive Robotics 9.3.2.1 Traditional action-effect learning research .................................. 179 9.3.2.2 Motor babbling .......................... 179 9.3.3 Robotic action-effect learning ........................ 180 9.4 Directions for the future ...................................... 181 9.4.1 Introduction ..........................................
    [Show full text]
  • Artificial Intelligence Vs (General) Artificial Intelligence 3
    ISSN 0798 1015 HOME Revista ESPACIOS ÍNDICES / Index A LOS AUTORES / To the ! ! AUTORS ! Vol. 40 (Number 4) Year 2019. Page 3 ¿Will machines ever rule the world? ¿Las máquinas dominarán el mundo? PEDROZA, Mauricio 1; VILLAMIZAR, Gustavo 2; MENDEZ, James 3 Received: 11/08/2018 • Approved: 16/12/2018 • Published 04/02/2019 Contents 1. Introduction 2. (Narrow) Artificial Intelligence vs (General) Artificial Intelligence 3. Machines designed as tools of man 4. Machines thought as similar to man 5. Conclusions Acknowledgments Bibliographic references ABSTRACT: RESUMEN: From ancient automatons, to the latest technologies Desde los antiguos autómatas hasta las últimas of robotics and supercomputing, the continued tecnologías de la robótica, el continuo progreso de la progress of mankind has led man to even question his humanidad ha llevado al hombre a cuestionar incluso future status as a dominant species. “Will machines su estatus futuro como especie dominante. "¿Alguna ever rule the world?” or more precisely: Do we want vez dominarán las máquinas el mundo?" O más machines to rule the world? Theoretical and precisamente: ¿Queremos que las máquinas dominen technological challenges involved in this choice will be el mundo? Los retos teóricos y tecnológicos que se considered both under the conservative approach of plantean en esta elección serán considerados tanto "machines designed as tools of man" and in the bajo el enfoque conservador de "máquinas que sirven scenario of "machines thought as similar to man". al hombre" como en el escenario de "máquinas Keywords: Artificial Intelligence, Cognitive Machines, equiparables al hombre" Narrow Artificial Intelligence Strong Artificial Palabras clave: Inteligencia Artificial, Máquinas Intelligence, Artificial General Intelligence.
    [Show full text]
  • Cognitive Robotics
    Volume title 1 The editors c 2006 Elsevier All rights reserved Chapter 24 Cognitive Robotics Hector Levesque and Gerhard Lakemeyer This chapter is dedicated to the memory of Ray Reiter. It is also an overview of cognitive robotics, as we understand it to have been envisaged by him.1 Of course, nobody can control the use of a term or the direction of research. We apologize in advance to those who feel that other approaches to cognitive robotics and related problems are inadequately represented here. 24.1 Introduction In its most general form, we take cognitive robotics to be the study of the knowledge rep- resentation and reasoning problems faced by an autonomous robot (or agent) in a dynamic and incompletely known world. To quote from a manifesto by Levesque and Reiter [42]: “Central to this effort is to develop an understanding of the relationship between the knowledge, the perception, and the action of such a robot. The sorts of questions we want to be able to answer are • to execute a program, what information does a robot need to have at the outset vs. the information that it can acquire en route by perceptual means? • what does the robot need to know about its environment vs. what need only be known by the designer? • when should a robot use perception to find out if something is true as opposed to reasoning about what it knows was true in the past? • when should the inner workings of an action be available to the robot for reasoning and when should the action be considered primitive or atomic? 1To the best of our knowledge, the term was first used publicly by Reiter at his lecture on receiving the IJCAI Award for Research Excellence in 1993.
    [Show full text]
  • Cognitive Robotics
    Cognitive Robotics . Cognitive Robotics . Embodied AI/Embodied CS . Robot capable of perception, reasoning, learning, deliberation, planning, acting, interacting, etc. Cognitive Architecture . Unified Theory of Cognition . Cognitive Models Cognitive Systems and Robotics • Since 2001: Cognitive Systems intensely funded by the EU "Robots need to be more robust, context-aware and easy-to-use. Endowing them with advanced learning, cognitive and reasoning capabilities will help them adapt to changing situations, and to carry out tasks intelligently with people" Research Areas . Biorobotics . Bio-inspirata, biomimetica, etc. Enactive Robotics . Dynamic interaction with the environment icub . Developmental Robotics (Epigenetic) . Robot learns as a baby . Incremental sensorimotor and cognitive ability [Piaget] . Neuro-Robotics . Models from cognitive neuroscience . Prosthesis, wearable systems, BCI, etc. Cog Developmental Robotics . iCub Platform . Italian Institute of Technology . EU project RobotCub: open source cognitive humanoid platf. Developmental Robotics . iCub Platform . Italian Institute of Technology . EU project RobotCub: open source cognitive humanoid platf. Developmental Robotics . iCub Platform Developmental Robotics . iCub Platform Developmental Robotics . Cognitive Architecture: The procedural memory is a network of associations between action events and perception events When an image is presented to the memory, if a previously stored image matches the stored image is recalled; otherwise, the presented image is stored Affordance . Affordance: property of an object or a feature of the immediate environment, that indicates how to interface with that object or feature ("action possibilities" latent in the environment [Gibson 1966]) . “The affordances of the environment are what it offers the animal, what it provides or furnishes, either for good or ill. The verb to afford is found in the dictionary, but the noun affordance is not.
    [Show full text]
  • Report of Comest on Robotics Ethics
    SHS/YES/COMEST-10/17/2 REV. Paris, 14 September 2017 Original: English REPORT OF COMEST ON ROBOTICS ETHICS Within the framework of its work programme for 2016-2017, COMEST decided to address the topic of robotics ethics building on its previous reflection on ethical issues related to modern robotics, as well as the ethics of nanotechnologies and converging technologies. At the 9th (Ordinary) Session of COMEST in September 2015, the Commission established a Working Group to develop an initial reflection on this topic. The COMEST Working Group met in Paris in May 2016 to define the structure and content of a preliminary draft report, which was discussed during the 9th Extraordinary Session of COMEST in September 2016. At that session, the content of the preliminary draft report was further refined and expanded, and the Working Group continued its work through email exchanges. The COMEST Working Group then met in Quebec in March 2017 to further develop its text. A revised text in the form of a draft report was submitted to COMEST and the IBC in June 2017 for comments. The draft report was then revised based on the comments received. The final draft of the report was further discussed and revised during the 10th (Ordinary) Session of COMEST, and was adopted by the Commission on 14 September 2017. This document does not pretend to be exhaustive and does not necessarily represent the views of the Member States of UNESCO. – 2 – REPORT OF COMEST ON ROBOTICS ETHICS EXECUTIVE SUMMARY I. INTRODUCTION II. WHAT IS A ROBOT? II.1. The complexity of defining a robot II.2.
    [Show full text]
  • Applications of Cognitive Robotics in Disassembly of Products
    Applications of Cognitive Robotics in Disassembly of Products By Supachai Vongbunyong B. Eng., M. Eng. A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy School of Mechanical and Manufacturing Engineering The University of New South Wales July 2013 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name Vongbunyong First name. Supachai Other name/s: - Abbreviation for degree as g1ven in the University calendar: PhD School· Mechamcal and Manufacturing Engmeering Faculty· Engmeenng Tille. Applications of cogmtlve robotics in disassembly of products Abstract 350 words maximum: (PLEASE TYPE) Disassembly automation has encountered difficulties in disassembly proces11 due to the variability in the planning and operation levels that result from uncertainties in quality-quantity of the products returned. Thus, the concept of cognitive robotics is Implemented to the vision-based and (semi-) destructive disassembly automation for end-of-life electronic products to handle this variability. The system consists of three operating modules, I.e. cognitive robotic module, vision system module, and disassembly operation module. First, the cognitive robotic module controls the system according to its behaviour influenced by four cognitive functions: reasoning, execution monitoring, learning, and revision. The cognitive robotic agent uses rule-based reasoning to schedule the actions according to the existing knowledge and sensed information from the physical world in regard to the disassembly state. Execution monitoring is used to determine accomplishment of the process. The significant Information of the current process is learned and will be Implemented in subsequent processes. Learning also occurs in the form of demonstration conducted by the expert user via the graphic user interface to overcome unresolved complex problem.
    [Show full text]
  • Cognitive Robotics and Control
    electronics Editorial Cognitive Robotics and Control Cecilio Angulo IDEAI-UPC, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain; [email protected]; Tel.: +34-9341-34021 Received: 29 April 2020; Accepted: 1 May 2020; Published: 6 May 2020 1. Introduction Robotics and control are both research and application domains that have been frequently engineered with the use of interdisciplinary approaches like cybernetics [1]. Cognition is a particular concept of this approach, abstracted from the context of living organisms to that of artificial devices, about knowledge acquisition and understanding through thought, experience, and the senses [2]. Cognitive robotics and control refer to knowledge processing as much as knowledge generation from problem understanding, leading to special forms of architectures enabling systems to behave in an autonomous way [3–5]. The main aim of this special issue is to highlight emerging applications and address recent breakthroughs in the domain of cognitive robotics and control and related areas. Procedures, algorithms, architectures and implementations for reasoning, problem solving or decision making in the domain of robotics and control are elements under consideration. 2. The Present Issue This special issue consists of eight papers covering important topics in the field of cognitive robotics and control, including robotic platforms in interactive scenarios such as operating rooms, trajectories learning and optimisation from nature-inspired and computational cognition approaches, and hardware developments for motor control. The contents of these papers are introduced here. Robotic platforms are taking their place in the operating room, providing stability and accuracy during surgery. Most of these platforms are tele-operated, as in Reference [6], where the learning from demonstration (LfD) approach is extended for object tele-manipulation.
    [Show full text]
  • Social Robots Social and Family Companion Robots
    Advanced Manufacturing Technology (TechVision) Social Robots Social and Family Companion Robots D718-TV March 04, 2016 Contents Section Slide Numbers Innovation–Social Robots 3 Social Home Robot 4 Family Companion Robot 5 Leonardo–A Socially Interactive Robot 6 Keepon® Pro 7 Strategic Insights 8 Key Patents 9 Industry Interactions 11 D718-TV 2 Innovations in Social Robots D718-TV 3 Social Home Robot Jibo Inc.–Jibo Tech. Profile Wide-scale Adoption Market Opportunity Jibo is a social interactive home robot for Pre-orders for Jibo have been very family and personnel assistance. Jibo is a active from early 2015. The • Robotics static robot but is capable of seeing, company is planning on shipping • Sensors hearing, speaking, helping, learning and from April 2016. This novel • Social/Commercial robots engaging in various household chores and innovation is expected to be • Space roles such as delivering information, commercialized over the relative • Defence and military controlling the environment, capturing near term. • Hospitality and tourism pictures, providing an educative medium for children, browsing the Web and providing relevant information, managing and co-ordinating family activities. Technology Convergence 1 9 22 Robotics is actually a convergence of Competing Aspects major technologies such as sensors, microelectronics and so on. This novel Jibo has a touch sensitive 8 3 aluminum body which has the technology development has opportunities to be widely adopted for capability to rotate in all three axis Technology different applications in various and face the person who is 7 Readiness 4 addressing it. The system runs on a Level industries mentioned in market opportunities. Robotics products such Linux platform and ARM processor 6 5 and the data collected by the as Jibo have potential to impact on the system is directly stored in the Jibo commercial electronics market.
    [Show full text]
  • Towards Cognitive Robotics : Robotics, Biology and Developmental
    Towards cognitive robotics : robotics, biology and developmental psychology LEE, Mark, NEHMZOW, Ulrich and RODRIGUES, Marcos <http://orcid.org/0000-0002-6083-1303> Available from Sheffield Hallam University Research Archive (SHURA) at: http://shura.shu.ac.uk/5282/ This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. Published version LEE, Mark, NEHMZOW, Ulrich and RODRIGUES, Marcos (2012). Towards cognitive robotics : robotics, biology and developmental psychology. In: MCFARLAND, David, STENNING, Keith, MCGONIGLE, Maggie and HENDRY, Derek, (eds.) The complex mind : an interdisciplinary approach. Basingstoke, Palgrave Macmillan, 103-126. Copyright and re-use policy See http://shura.shu.ac.uk/information.html Sheffield Hallam University Research Archive http://shura.shu.ac.uk Towards Cognitive Robotics: Robotics, Biology and Developmental Psychology Mark Lee, Ulrich Nehmzow and Marcos Rodrigues 1 Introduction — Early Robotics Research The question of how “intelligent” controllers can be designed for machines has always attracted much interest and research activity. The idea of reproducing some facets of human cognition in a designed artifact has fascinated scientists, philosophers and charlatans throughout history. But despite the enormous efforts that have been directed at this issue in the twentieth century, only very recently has any significant progress been made. The robots of the last century typically were brittle, they failed in even simple tasks as soon as these tasks deviated even slightly from the original specifications; they were slow; and they needed constant attention from software engineers. Up to the late 1980s and early 1990s robotics research was dominated by work originating from the control theory and cybernetics communities, which meant that the fundamental assumptions of how intelligent behaviour could be achieved were very similar if not identical.
    [Show full text]
  • Cognitive Robotics to Understand Human Beings
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE QUARTERLY REVIEW No.20 / July 2006 1 Cognitive Robotics to Understand Human Beings KAYOKO ISHII Life Science Unit taking place at that time. 1 Introduction In Japan, research on the computational theory of the brain[1] and research combining The question of what human beings (self theory and physiological experiments[2] has been and others), the mind, and the world are has carried out. One of the major themes in Japanese always been of great interest to humankind. brain science in the 1990s was “creating the Most academic disciplines originated to answer brain” beside analytical experimental sciences these questions. As neuroscience has advanced, (“understanding the brain”) and research oriented the notion that brain function is closely related to medical applications (“protecting the brain”). to the mind has become more widely accepted, This theme was significant in that it not only increasing the expectation that unknown aspects expressed the concept of understanding brain of the mind could be explored by neuroscience. functions through “cycles of creation of models of However, a long-standing question regarding the brain, computational theory and neural networks, mind is that one’s mind seems to be associated their verification through experimental science, with oneself as a physical existence, yet its and improvement of theories and models,” but content seems not to be expressed physically. also expressed the unconventional orientation Simply accumulating knowledge acquired of creating new systems inspired by the brain. through external analysis and observation of Furthermore, computational neuroscience was the brain as a physical entity is not sufficient to defined as “to investigate information processing elucidate the essential functions of the brain and of the brain to the extent that artificial machines, the nature of the mind.
    [Show full text]
  • Cognitive Robotics: the Science of Building Intelligent Autonomous Robots and Software Agents
    Cognitive Robotics: The science of building intelligent autonomous robots and software agents Giuseppe De Giacomo University of Roma “La Sapienza”, Italy Miegunyah Fellow, University of Melbourne, Australia Cognitive Robotics Giuseppe De Giacomo - Miegunyah Fellow 1 Cognitive Robotics: The science of building intelligent autonomous robots and software agents INTRODUCTION Cognitive Robotics Giuseppe De Giacomo - Miegunyah Fellow 2 Introduction • Cognitive Robotics is the science of building autonomous robots/agents that operate in changing, incompletely known, unpredictable environments. • Cognitive robots are “smart”: have autonomy, including autonomous reasoning and planning capabilities. • Cognitive robots are already a reality. Cognitive Robotics Giuseppe De Giacomo - Miegunyah Fellow 3 Example: “Curiosity” the Latest NASA Mars Rover •! “Cognitive robotics” in a NASA cartoon! Cognitive Robotics Giuseppe De Giacomo - Miegunyah Fellow 4 Example: “Curiosity” the Latest NASA Mars Rover •! The previous video is referring to Curiosity, the latest NASA Mars Rover (a large, mobile laboratory), which started its mission a year ago (landed on Mars on Aug. 6, 2012) •! Within the first 8 months of a planned 23-month primary mission, Curiosity met its major objective of finding evidence of a past environment well suited to supporting microbial life. Cognitive Robotics Giuseppe De Giacomo - Miegunyah Fellow 5 Robots Come in a Variety of Shapes •! Nowadays through increasing use of software (and hence CS) robots are increasingly acquiring forms of autonomy Rhex: power - and computation - autonomous hexapod robot with compliant legs and only one actuator per leg, developed by a consortium of American universities, including University of Michigan, McGill University, Carnegie Mellon University, University of California, Berkeley, Princeton University, Cornell University, University of Pennsylvania, within the RHex DARPA project.
    [Show full text]