Towards the development of cognitive robots

Similar documents
A Three-Dimensional Evaluation of Body Representation Change of Human Upper Limb Focused on Sense of Ownership and Sense of Agency

ENHANCED HUMAN-AGENT INTERACTION: AUGMENTING INTERACTION MODELS WITH EMBODIED AGENTS BY SERAFIN BENTO. MASTER OF SCIENCE in INFORMATION SYSTEMS

Evaluating Effect of Sense of Ownership and Sense of Agency on Body Representation Change of Human Upper Limb

Hybrid architectures. IAR Lecture 6 Barbara Webb

Supplementary Figure 1

Combining interactive multimedia and virtual reality to rehabilitate agency in schizophrenia

Modeling cortical maps with Topographica

Lecture IV. Sensory processing during active versus passive movements

The Special Senses: Vision

Towards a Methodology for Designing Artificial Conscious Robotic Systems

Virtual Reality in Neuro- Rehabilitation and Beyond

Embodiment illusions via multisensory integration

An Unreal Based Platform for Developing Intelligent Virtual Agents

Cognitive Systems and Robotics: opportunities in FP7

FP7 ICT Call 6: Cognitive Systems and Robotics

GPU Computing for Cognitive Robotics

Key-Words: - Fuzzy Behaviour Controls, Multiple Target Tracking, Obstacle Avoidance, Ultrasonic Range Finders

I+ I. Eric Eisenstadt, Ph.D. DARPA Defense Sciences Office. Direct Brain-Machine Interface. Science and Technology Symposium April 2004

Below is provided a chapter summary of the dissertation that lays out the topics under discussion.

Non-Invasive Brain-Actuated Control of a Mobile Robot

Human Robot Interaction (HRI)

Modeling, Architectures and Signal Processing for Brain Computer Interfaces

Artificial Intelligence

Reinventing movies How do we tell stories in VR? Diego Gutierrez Graphics & Imaging Lab Universidad de Zaragoza

Cognitive robots and emotional intelligence Cloud robotics Ethical, legal and social issues of robotic Construction robots Human activities in many

Glossary of terms. Short explanation

Lecture 4 Foundations and Cognitive Processes in Visual Perception From the Retina to the Visual Cortex

Brain Computer Interfaces Lecture 2: Current State of the Art in BCIs

Intro to Intelligent Robotics EXAM Spring 2008, Page 1 of 9

Booklet of teaching units

Multisensory brain mechanisms. model of bodily self-consciousness.

Non Invasive Brain Computer Interface for Movement Control

What do I need to know about multisensory interactions?

Sensations and Perceptions in Cicerobot a Museum Guide Robot

YDDON. Humans, Robots, & Intelligent Objects New communication approaches

FP7 STREP. The. Consortium. Marine Robots and Dexterous Manipulation for Enabling Autonomous Underwater Multipurpose Intervention Missions

A neuronal structure for learning by imitation. ENSEA, 6, avenue du Ponceau, F-95014, Cergy-Pontoise cedex, France. fmoga,

ROBOT CONTROL VIA DIALOGUE. Arkady Yuschenko

State of the Science Symposium

Making Representations: From Sensation to Perception

Steering a Driving Simulator Using the Queueing Network-Model Human Processor (QN-MHP)

The organization of the human nervous system. OVERHEAD Organization of the Human Nervous System CHAPTER 11 BLM

Dipartimento di Elettronica Informazione e Bioingegneria Robotics

MECHANICAL DESIGN LEARNING ENVIRONMENTS BASED ON VIRTUAL REALITY TECHNOLOGIES

Processing streams PSY 310 Greg Francis. Lecture 10. Neurophysiology

R (2) Controlling System Application with hands by identifying movements through Camera

INTELLIGENT WHEELCHAIRS

Presented by: V.Lakshana Regd. No.: Information Technology CET, Bhubaneswar

EEG frequency tagging to study active and passive rhythmic movements

TOWARDS A NEW GENERATION OF CONSCIOUS AUTONOMOUS ROBOTS

10th International Workshop on DATA ANALYSIS METHODS FOR SOFTWARE SYSTEMS

Multi-Agent Planning

Multi-Agent Systems in Distributed Communication Environments

Jane Li. Assistant Professor Mechanical Engineering Department, Robotic Engineering Program Worcester Polytechnic Institute

Capturing and Adapting Traces for Character Control in Computer Role Playing Games

Towards affordance based human-system interaction based on cyber-physical systems

Natural Interaction with Social Robots

Behaviour-Based Control. IAR Lecture 5 Barbara Webb

Why interest in visual perception?

Intelligent Systems: Perspectives and Research Challenges. Rajendra Akerkar

Analysis of brain waves according to their frequency

CSE 165: 3D User Interaction. Lecture #14: 3D UI Design

A developmental approach to grasping

Birth of An Intelligent Humanoid Robot in Singapore

A Robust Neural Robot Navigation Using a Combination of Deliberative and Reactive Control Architectures

Android (Child android)

Touch Perception and Emotional Appraisal for a Virtual Agent

CONSIDERATION OF HUMAN COMPUTER INTERACTION IN ROBOTIC FIELD

Chapter 8: Perceiving Motion

Virtual Reality to Support Modelling. Martin Pett Modelling and Visualisation Business Unit Transport Systems Catapult

Interface Design V: Beyond the Desktop

AN AUTONOMOUS SIMULATION BASED SYSTEM FOR ROBOTIC SERVICES IN PARTIALLY KNOWN ENVIRONMENTS

Outline. Agents and environments Rationality PEAS (Performance measure, Environment, Actuators, Sensors) Environment types Agent types

An Integrated HMM-Based Intelligent Robotic Assembly System

Motor Imagery based Brain Computer Interface (BCI) using Artificial Neural Network Classifiers

Agents in the Real World Agents and Knowledge Representation and Reasoning

Digital image processing vs. computer vision Higher-level anchoring

Feelable User Interfaces: An Exploration of Non-Visual Tangible User Interfaces

Keywords Multi-Agent, Distributed, Cooperation, Fuzzy, Multi-Robot, Communication Protocol. Fig. 1. Architecture of the Robots.

Roles for Sensorimotor Behavior in Cognitive Awareness: An Immersive Sound Kinetic-based Motion Training System. Ioannis Tarnanas, Vicky Tarnana PhD

A DIALOGUE-BASED APPROACH TO MULTI-ROBOT TEAM CONTROL

Cognitive Robotics 2016/2017

Governing Lethal Behavior: Embedding Ethics in a Hybrid Reactive Deliberative Architecture

Vision V Perceiving Movement

Vision V Perceiving Movement

Training in realistic virtual environments:

Towards The Adoption of a Perception-Driven Perspective in the Design of Complex Robotic Systems

OCCUPATIONAL THERAPY. Essential Question: Do Humans Have a Sixth Sense? Learning Targets: Lesson Overview

Embodiment from Engineer s Point of View

INTERACTIVE SKETCHING OF THE URBAN-ARCHITECTURAL SPATIAL DRAFT Peter Kardoš Slovak University of Technology in Bratislava

Cognitive Science: What Is It, and How Can I Study It at RPI?

What is Artificial Intelligence? Alternate Definitions (Russell + Norvig) Human intelligence

RV - AULA 05 - PSI3502/2018. User Experience, Human Computer Interaction and UI

Navigating in a dynamic world

MULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT

CSC384 Intro to Artificial Intelligence* *The following slides are based on Fahiem Bacchus course lecture notes.

Introduction to AI. What is Artificial Intelligence?

Using Multivariate Pattern Analysis to Investigate the Neural Representation of Concepts With Visual and Haptic Features

CSCI 445 Laurent Itti. Group Robotics. Introduction to Robotics L. Itti & M. J. Mataric 1

An Auditory Localization and Coordinate Transform Chip

Transcription:

Towards the development of cognitive robots Antonio Bandera Grupo de Ingeniería de Sistemas Integrados Universidad de Málaga, Spain Pablo Bustos RoboLab Universidad de Extremadura, Spain International Workshop on Brain-inspired computing Cretaro (Italy) July 8-11, 2013

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Who are we? ISIS/RoboLab groups Our goals: present and future The development of robots that can share the environment with us, exhibiting a correct (social) behavior. People Cáceres Madrid Albacete A small group at Málaga and Cáceres (Spain) but with a lot of friends that know a lot about robotics, computer vision, mathematics Realities Málaga Linares Integra project (200K EUR) Therapist project (200K EUR) Adapta project (300K EUR)

Motivation Robots for acting From motor control Control of action A well-functioning motor system is an essential requirement if the robot is to move through the environment safely, reach and grasp objects and learn new skills. Abnormalities in the awareness and control of action - C. Frith, S. Blakemore, D. Wolpert, 2000 MUECAS, LOKI and URSUS RoboLab But the problem is also to determine which actions to perform and in which order, and how to perform these actions.

Motivation Robots for acting to robotics agency Robotics agency The experience of agency refers to the experience of being in control both of one s own actions and, through them, of events in the external world. Acting on the outer world Subjective experience How to proceed The experience of agency - Patrick Haggard and Manos Tsakiris, 2009 MUECAS, LOKI and URSUS RoboLab Step-by-step!!

Motivation The simulation theory Open problem We would like to develop a software structure that endows a robot with this subjective experience. One possibility Intention Mental simulation of action and behaviour Anticipation Sensory Confirmation Mental simulation of perception (imagination) The current status of the simulation theory of cognition, G. Hesslow, Brain Research, 2011

Goal Making robots to imagine for acting Putting a virtual robot inside of a virtual world The problem of modeling itself and the outer world At perception level: there is a representational gap 1 between outer items and inner models At situational level: there is a need of models and of mechanisms to drive these models At deliberative level: the course of action should be reactively adapted to the dynamic scenario 2 1 Generic model abstraction from examples, Y. Keselman and S. Dickinson, CVPR, 1:856 863, 2001 2 Towards performing everyday manipulation activities, M. Beetz et al, Robotics and Autonomous Systems, 2010

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

The simulation theory of cognition Foundations simulation of movement precedes and plans for upcoming physical action and activates the same cortical and subcortical structures that are responsible for motor execution - Keith D. Markman, William M.P. Klein, and Julie A. Suhr The common coding hypothesis 1 : Actions are coded in terms of the perceivable effects they will generate Associations between motor patterns and sensory effects can then be used backward to retrieve a movement by anticipating its effects Perception-action codes are also accessible during action observation, and perception activates action representations to the degree that the perceived and the represented actions are similar 1 Prinz, W. (2003). Experimental approaches to action. In J. Roessler & N. Eilan (Eds.), Agency and self-awareness (pp. 175 187). Oxford, England: Oxford University Press.

The simulation theory of cognition Foundations simulation of movement precedes and plans for upcoming physical action and activates the same cortical and subcortical structures that are responsible for motor execution - Keith D. Markman, William M.P. Klein, and Julie A. Suhr The simulation theory of cognition 1 : Motor structures are activated when behaviours are simulated, as during normal overt action but suppressing its execution Internal activation of sensory cortex simulate perception in a way that resembles its normal activation during perception of external stimuli Overt and simulated actions can elicit perceptual simulation of their most probable consequences (anticipation) 1 G. Hesslow (2011) The current status of the simulation theory of cognition, Brain Research

The simulation theory of cognition Engineering Body movement at the brain. The motor cortex: Primary motor cortex (Area 4): A map of the human body muscles Premotor cortex (Area 6): Body postures (optimal position for a movement) Supplementary motor area (Area 6): Movement planning and initiation on the basis of past experience. Anticipation Somatosensory cortex : A map of the human body sensing Posterior Parietal Cortex (Area 5): Coding space / spatial attention to body movements Posterior Parietal Cortex (Area 7): Visual information (from MT or V5) integration The parietal lobes and the prefrontal areas represent the highest level of integration in the motor control hierarchy: they take the decision of what action to accomplish.

The simulation theory of cognition Engineering Basal ganglia Domain Knowledge Plan library Prefrontal cortex Transformational planner (movement plan)

The simulation theory of cognition Engineering Basal ganglia Domain Knowledge Plan library Prefrontal cortex Transformational planner (movement plan) SMA + Cerebelum Situational planner (whole body pose)

The simulation theory of cognition Engineering Basal ganglia Domain Knowledge Plan library Prefrontal cortex Transformational planner (movement plan) SMA + Cerebelum Situational planner (whole body pose) PMC + brainstem + spinal cord Physics-based planner (motor commands)

The simulation theory of cognition Engineering Basal ganglia Domain Knowledge Plan library Prefrontal cortex Transformational planner (movement plan) Deep State Hybrid representation Sensing SMA + Cerebelum Situational planner (whole body pose) PMC + brainstem + spinal cord Physics-based planner (motor commands) The operation of each hierarchical level in the motor control system is extremely dependent on the sensory information that it receives. It can be considered that the motor system must really be considered in sensorimotor terms.

The simulation theory of cognition Engineering Basal ganglia Domain Knowledge Plan library Prefrontal cortex Transformational planner (movement plan) Deep State Hybrid representation Sensing SMA + Cerebelum Situational planner (whole body pose) PMC + brainstem + spinal cord Physics-based planner (motor commands) The operation of each hierarchical level in the motor control system is extremely dependent on the sensory information that it receives. It can be considered that the motor system must really be considered in sensorimotor terms.

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Cognitive architecture Deep State Representation Models 3D graphics engine Deep State Hybrid representation Putting a virtual robot inside of a virtual world The problem of modeling itself and the outer world At perception level: there is a representational gap between outer items and inner models At situational level: there is a need of models and of mechanisms to drive these models At deliberative level: the course of action should be reactively adapted to the dynamic scenario Links to planners

Cognitive architecture Deep State Representation Models Deep State Hybrid representation PELEA (University Carlos III Madrid) 3D graphics engine EXECUTIVE Links to planners PERCEPTION (Proprioceptive, vision )

Cognitive architecture Deep State Representation Models Deep State Hybrid representation PELEA (University Carlos III Madrid) 3D graphics engine EXECUTIVE Links to planners PERCEPTION (Proprioceptive, vision )

Cognitive architecture A global view Deep State Hybrid representation PELEA (University Carlos III Madrid) EXECUTIVE Deep State Hybrid representation Planner + Executive PERCEPTIION BEHAVIOURS

Cognitive architecture An illustrative example Acting on the outer world Acting on the inner world

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Experimental scenarios Rehabilitation robotics URSUS, the antecessor of THERAPIST RoboLab Neuro-rehabilitation therapy pursuits the recovery of damaged neuronal areas and/or muscles from the repetitive practice of certain motor or cognitive activities. The patient's recovery directly depends on the adherence to neuro-rehabilitation therapy. Within this project, we are working on the definition of new neuro-rehabilitation therapies through the development of THERAPIST, a robot that will perform as an innovative trainer in motor deficit therapies.

Experimental scenarios Rehabilitation robotics URSUS, the antecessor of THERAPIST RoboLab In order to engage patients in social interactions, our therapist robot should be able to emanate responses at human interaction rates, and exhibit a pro-active behaviour This behaviour implies that the internal architecture of the robot should not only be able to perceive and act. It should also be able to perform off-line reasoning. Perceive the outer world Update the inner DSR Simulate an ACTION Simulate a PERCEPTION ACT Anticipation cancels out the inherent delays of physical systems

Experimental scenarios Vendor robotics Working on large environments, the goal of the Adapta project is to use interactive panel to capture the people attention and to show them publicity contents. Our aim is to incorporate to this scenario a Gualzru, a robot that is able to engage with people through expressions, dialogue, gestures and that tries to convince pedestrians to come to an interactive stand panel where publicity contents are shown.

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Motivation and goals The simulation theory of cognition Making robots to imagine for acting On-going experimental scenarios Rehabilitation robotics Vendor robotics Conclusions and future work

Conclusions and future work Deep state representations coupled with a hierarchy of planners could provide the necessary structure to implement internal simulation systems Further complexity can be achieved with a self-similar architecture, where low-level behaviors are themselves organized as a composition of DSR, planners and behaviors. Is there a correspondence in the brain? A big challenge is to handle the complexity of very large distributed computational systems implementing cognitive architectures. Integration of models of attention for action/perception focusing. New design tools working at increasing levels of abstraction are needed, i e. domain specific languages, specialized frameworks Evaluate the extension of the temporal scale of emulation (to the future an past)

Towards the development of cognitive robots Antonio Bandera Grupo de Ingeniería de Sistemas Integrados Universidad de Málaga, Spain Pablo Bustos RoboLab Universidad de Extremadura, Spain