A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-based Manipulation Tasks
Omar Zahra, David Navarro-Alarcon, Silvia Tolu

TL;DR
This paper develops a biologically detailed spiking cerebellar model integrated with a robot arm to explore neural-motor interactions during vision-based manipulation, aiming to mimic human motor behavior.
Contribution
It introduces a cellular-level cerebellar model including Golgi and Basket cells, optimized for biological plausibility, and demonstrates its effectiveness in robotic manipulation tasks.
Findings
Model reproduces human-like reaching behavior
Biological features are preserved through hyperparameter tuning
Effective in various vision-based manipulation tasks
Abstract
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 behaviour. 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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
