"Overview of the results
The main outcome of this project is a modular spiking implementation of the cerebellar-like circuit that was embedded in three novel bio-inspired control architectures that embed forward and/or inverse internal models: the feed-forward, recurrent, and composite control schemes. Modular stands for the creation of distinct cerebellar microcircuits that are responsible for the learning of the internal model of a robot module or robot joints. Depending on the internal model, inverse or forward, the microcircuits receive varied sensorimotor information that are integrated towards giving motor or sensory outcomes. The architectures were tested on both a physical and real robot to perform a task with changing kinematics and dynamics conditions. The composite architecture combines the advantages of forward and inverse models and the learning of the latter is improved by the prediction error of the first. Tests showed that the architectures have different adaptation scales based on the disturbances and contexts. Different modular robotic configurations were tested for the validation and generalization of the control and learning mechanisms both in manipulation and locomotion tasks within the NRP developed in the framework of the Human Brain Project. The NRP integrates all the tools necessary for embedding artificial brain models to robotic systems. In particular, it facilitates the coordination between spiking neural networks and continuous time system. Moreover, the platform resulted to be a convenient framework for accelerating the experimental set up and analyses thanks to all the available plugins.
Main dissemination activities
• School of Brain Cells & Circuits “Camillo Golgi”, Ettore Majorana Foundation and Centre for Scientific Culture. Lecture title: Integration of cerebellar models into robotic control loops. Erice (Italy), 11-15 December 2018.
• Participation at the ICT Networking Dinner in Vienna, Austria, December 3, 2018. ROBOINSIGHTS’18 The First Global annual NEW Technology Conference & Expo, Elsinore, Denmark, 26-27 Sept. 2018. Talk: ""Neuro-Robotics, connecting body, environment and brain"".
• Participation at the workshop organized by the Technical University of Munich (TUM) for discussing the current work on bio-inspired motor control schemes within the HBP. Munich, Germany, August 20-21, 2018.
• 4th EU-Japan Workshop on Neurorobotics, Embodiment of Informatics with Neurorobotics. Talk title: Using robots for understanding the cerebellar role in sensorimotor control, AIST Tokyo Waterfront, Tokyo, April 18-20, 2018.
• BioModular project was mentioned and acknowledged during the talk presented by Marie Claire Capolei and Carlos Corchado Miralles (research assistants at DTU for HBP). Talk title: “The Human Brain Project - how robotics can exploit brain science”, H.C. Ørsted Institute, Copenhagen, Denmark, March 19, 2018.
Summary of the exploitable results.
-A spiking cerebellar network model with granular and molecular layers and PC-DCN-IO cells was implemented and tested.
-An optimal input-space representation for the granular layer by means of a machine learning engine was provided.
-Bio-inspired control loops were built and tested with a physical robot and neuromorphic hardware SpiNNaker to perform tasks controlled by the cerebellar machine learning network.
-Learning of forward and inverse internal models of the robot was encoded inside an ULM embedded into the bio-inspired control loops to adapt the corrections and make predictions.
-The forward and inverse internal models were combined and embedded in a composite architecture.
-Different modular robotic configurations were tested for the validation of the bio-inspired control architecture in manipulation and locomotion tasks within the Neurorobotics Platform. The inclusion of input from vision was evaluated to enhance the learning and so, the behavior of the control process."
