The workshop to introduce Neurorobotics Platform (NRP) was held on the SSSA with participation of M.Sc. and Ph.D. students. During the workshop, two instructors from the development and research teams provided introductory information on Human Brain Project and, specifically, SP-10 Neurorobotics Platform features including open source technologies used in the NRP (e.g., ROS and Gazebo), development cycles and graphical user interface for the first time users. After the introduction, the users installed the NRP by either following instruction from the HBP Neurorobotics repository or via the bootable flash disks in order to install the NRP for a hands-on session.
The users followed the instructions from tutorial_baseball_exercise to create an experiment as a first demo and to get familiarity with the NRP concepts such as transfer functions, Brain-Body interface, closed-loop engine, to mention a few. This session ended with successfully solving the tutorial requirements with the assistance of the instructor. In the last part of the workshop, the participants discussed to integrate their own on-going project to the NRP. One of the participants expresses his ideas on integration Cerebellar model to the NRP:
My objective is to study the computational characteristics of the cerebellum, responsible for precise motor control in biological agents. Currently, a rate based model of the cerebellum has been implemented to produce accurate saccades in the primate type oculomotor system. My plan is to convert this model into a full spike based cerebellar model in the NEST simulator and apply this control model on the iCub gazebo. The NRP is definitely poised to provide me with this functionality.
Another participant expressed his plan to integrate a continuum robot, I-SUPPORT, to the NRP:
My on-going works with the NRP to create an I-SUPPORT robot model using an OpenSim muscle model to simulate the behavior of the McKibben's present in the robotic arm.
The last project idea:
The experiments on invariant object recognition and multi-modal object representation by integrating the Hierarchical Temporal Memory, many (deep) layered networks and Spiking Neural Nets to the NRP.
The workshop closed with the evaluation of each session and discussions on the requirements for the each proposed projects.