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Future Developments in Neurorobotic Technology 3rd HBP Education Workshop Future Developments in Neurorobotic Technology Prof. Dr.-Ing. habil. Alois Knoll Technical University of Munich Department of Informatics Robotics and Embedded Systems http://neurorobotics.net/ Outline • Introduction to Neurorobotics • Current Research in Neurorobotics • The Neurorobotics Subproject of the Human Brain Project • The Neurorobotics Platform • The Future of Neurorobotic Technology • Get Involved! Introduction to Neurorobotics Definition & History What is Neurorobotics? Neurorobotics is an emerging interdisciplinary field of research at the intersection of state-of-the art research in robotics and in-silico neuroscience. It is about • building robot bodies with an embedded brain and embedded control systems by • mimicking the structure and function of the nervous systems of creatures. Basis Development of biologically accurate models of brains and bodies. Approach Let these robots live in both real and high-fidelity virtual environments, and observe their (developing/growing) skills to reverse-engineer the brain. 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 4 Why Link Brains to Robots? • Algorithms are embedded in hardware • Sensors and effectors operate in real-time • 850,000 neurons The brain is massively parallel, but does not 10,000 neurons suffer from the problems of parallel computing: dead-locks, non-determinism, race-conditions, … 1,000,000 neurons • … and decomposition into parallel tasks is self-organized/evolved • 75,000,000 neurons 200,000,000 neurons Architecture is scalable from thousands to Homo sapiens billions of “processors” • Performance is robust – with graceful degradation • Brains are extremely power and space efficient ~85,000,000,000 neurons, 1015 synapses (“peta-flop computer on 20 Watt”) • Calls for a “neurorobotics approach” 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 5 Goals of Neurorobotic Research Robotics Robotics Neuroscience Learning • Apply findings • Use robots as a • Leverage robotic from neuroscience tool for testing embodiment to hypotheses study and develop • Overcome the neurobiological limitations of • Full observability models of learning standard control of brain models architectures during interaction • Endow virtual with the realistic • Use neuromorphic brains with the environments hardware for robot desired behavior control tasks Provide an interdisciplinary experimental link 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 6 A Brief History of Neurorobotics 1950 William Grey Walter’s Tortoises Simple mobile robotic platforms with a “nervous system” of vacuum tubes capable of phototaxis and classical conditioning 1988 Feedback-Error-Learning Neural Network by Miyamoto et al. http://www.nsi.edu/ A hierarchical neural network model with brain-like ~nomad/darwinvii.html architecture and heterosynaptic plasticity is used to control the trajectory of a robotic manipulator 1990s Synthetic Neural Modeling and Brain-Based Devices by Krichmar, Edelman et al. Development of the Darwin series of robots (both virtual and physical) to study the neural bases of adaptive behavior 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 7 The Early Beginnings of (Neuro-)Robotics: William Grey Walter’s Tortoises Source: https://www.youtube.com/watch?v=lLULRlmXkKo 3rd HBP Education Workshop A Machine that Learns, pp60 – 63, W. Grey8 Walter doi:10.1038/scientificamerican0851-60 A Brief History of Neurorobotics 2003 Study on Active Vision by Suzuki, Floreano et al. A neurorobotics study demonstrates the importance of closed action-perception loops for the development of the visual system and thereby highlights how neurorobotics can advance machine learning Today Large-Scale Brain Simulation, Neuromorphic Hardware and Biomimetic Robotics The tools developed within the Human Brain Project and advances in biomimetic robotics are opening up a new era of neurorobotic research with highly realistic brain simulations and body morphologies 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 9 Neurorobotics is an Emerging Field of Research! 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 10 Current Research in Neurorobotics An Overview Neuromorphic Sensors and Computation for Robot Control A Mobile Robot Platform with SpiNNaker and Silicon Retinas • On-board SpiNNaker system (48 chips, 864 cores, simulates up to 250000 neurons for less than 40 Watt) • Two silicon retinas (eDVS sensors) for spike-based neuromorphic stereo vision • Programmable via C, PyNN and Nengo Applications • Trajectory stabilization via optical flow • Stimulus tracking • Learning by demonstration Source: Conradt, Galluppi, Stewart TUM (2014) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 12 Locomotion with Central Pattern Generators Animal Locomotion • Animals are able to move seamlessly in their specific environments • Basic motion primitives are implemented by Central Pattern Generators (CPGs, oscillatory neural circuits in the spinal Source: https://www.youtube.com/watch?v=01j9SyNhavI cords of vertebrates) • High-level control through top- Animals can even down modulation from the live and move brain without a cortex → Animal locomotion control as Source: an inspiration for robotics https://en.wikipedia.org/wiki/Mi ke_the_Headless_Chicken Source: Ijspeert (2008) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 13 Locomotion with Central Pattern Generators Case Study: A Salamander Robot • Modular biomimetic robot with four legs and an actuated spine • The movements for locomotion are generated by a CPG model which is implemented as a network of coupled nonlinear oscillators • The robot is capable of both salamander-like walking and swimming • Tool for both robotics and neuroscience Source: Ijspeert et al. (2007, 2013, 2015) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 14 A Salamander Robot Driven by CPGs (Ijspeert et al.) Source: http://biorob2.epfl.ch/utils/movieplayer.php?id=256 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 15 Neuromuscular Modeling and Simulation • A detailed musculoskeletal model of the human body enables highly realistic embodiment for brain simulations • Muscles, tendons and ligaments are modeled as wires which are attached to the bones • The resulting mechanical model has 155 degrees of freedom (most industrial robots have only 6 degrees of freedom!) • Adding a neural simulation of the nervous system yields a neuromuscular model Source: Nakamura et al. (2005, 2006) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 16 Example: Neuromuscular Simulation of the Biceps Stretch Reflex • Simulation with pools of Integrate-and- Fire Neurons is connected to a realistic musculoskeletal simulation • Neural architecture based on the spine Two motor neurons pools control biceps and triceps Two sensory neuron pools encode velocities of biceps and triceps One pool of interneurons for inhibitory disynaptic connections • Neural and musculoskeletal parameters are derived from experimental results Source: Sreenivasa, Murai, Nakamura (2013) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 17 Cognitive Developmental Robotics “Cognitive developmental robotics (CDR) aims to provide new understanding of how human’s higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions. The core idea of CDR is “physical embodiment” that enables information structuring through interaction with the environment, including other agents.” Asada et al., 2009 • Interdisciplinary field of research including artificial intelligence, robotics, neuroscience, cognitive science, developmental psychology, … • Assumption of distinct phases for individual and social development • Only concerned with ontogenetic timescales (= single individual) and not with phylogenetic timescales (= evolution of a species) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 18 Example: Simulation of Early Fetal Development Fetus Simulation with Spiking The analysis of simulation results Neural Networks suggests the dependence of body map development on • the environment • the nervous system • fetal movements Simulation of a human fetus in a realistic environment with a nervous system consisting of spiking neurons. Source: Yamada, Fujii & Kuniyoshi (2013) 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 19 A Robot Baby (Kuniyoshi et al.) Source: https://www.youtube.com/watch?v=dMCAQXyKcSc 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 20 The Neurorobotics Subproject of the Human Brain Project (SP10) Shaping the Future of Neurorobotics Our Motivation Mankind has long dreamed of autonomous robots which possess a wide variety of skills, including … • Perception, “Out-of-the box”- navigation and recognition of arbitrary environments • Attending to, aiding and safe working with others • Goal-oriented behavior, learning, decision making • Sense of self, Consciousness 3rd HBP Education Workshop Future Developments in Neurorobotic Technology 22 Our Motivation But these robot should also have even more properties, like … • fault tolerance • low energy consumption • lightweight, cheap, compliant mechanics, compact design, ... The ultimate dream/goal is to build robots with superhuman flexibility and adaptivity.
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