While the original goal for developing robots is replacing humans in dangerous and tedious tasks, the final target shall be completely mimicking the human cognitive and motor behavior. Hence, building detailed computational models for the human brain is one of the reasonable ways to attain this. The cerebellum is one of the key players in our neural system to guarantee dexterous manipulation and coordinated movements as concluded from lesions in that region. Studies suggest that it acts as a forward model providing anticipatory corrections for the sensory signals based on observed discrepancies from the reference values. While most studies consider providing the teaching signal as error in joint-space, few studies consider the error in task-space and even fewer consider the spiking nature of the cerebellum on the cellular-level. In this study, a detailed cellular-level forward cerebellar model is developed, including modeling of Golgi and Basket cells which are usually neglected in previous studies. To preserve the biological features of the cerebellum in the developed model, a hyperparameter optimization method tunes the network accordingly. The efficiency and biological plausibility of the proposed cerebellar-based controller is then demonstrated under different robotic manipulation tasks reproducing motor behavior observed in human reaching experiments.


    Access

    Download


    Export, share and cite



    Title :

    A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-Based Manipulation Tasks


    Contributors:

    Publication date :

    2021-01-01


    Remarks:

    Zahra , O , Navarro-Alarcon , D & Tolu , S 2021 , ' A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-Based Manipulation Tasks ' , International Journal of Neural Systems . https://doi.org/10.1142/S0129065721500283



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Brain-Inspired Spiking Neural Network Controller for a Neurorobotic Whisker System

    Antonietti A. / Geminiani A. / Negri E. et al. | BASE | 2022

    Free access

    Vision Based Robotic Interception in Industrial Manipulation Tasks

    Ahmet Denker / Tuğrul Adıgüzel | BASE | 2007

    Free access

    Forming a sparse representation for visual place recognition using a neurorobotic approach

    Colomer, Sylvain / Cuperlier, Nicolas / Bresson, Guillaume et al. | IEEE | 2021