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Neuro-Inspired Sensorimotor Models for Autonomous Robots

About the Research

We are developing neuro-inspired methods for computing sensorimotor models of robotic systems. This work is done in collaboration DTU Denmark and supported by the France/HK Joint Research Scheme under grant F-PolyU503/18, and by PolyU under grants 4-ZZHJ and G-YBYT.


Related Papers

  • O. Zahra, D. Navarro-Alarcon, and S. Tolu. 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 (IJNS) (accepted), 2021 [pdf]

  • O. Zahra, S. Tolu and D. Navarro-Alarcon. Differential Mapping Spiking Neural Network for Sensor-Based Robot Control, Bioinspiration & Biomimetics, vol. 16, no. 3, pp. 036008 2021. [pdf]

  • D. Navarro-Alarcon, O. Zahra, C. Trejo, E. Olguin-Diaz and V. Parra-Vega. Computing Pressure-Deformation Maps for Braided Continuum Robots, Frontiers in Robotics and AI, vol. 6, pp. 1–4, 2019. [pdf]

  • O. Zahra, D. Navarro-Alarcon and S. Tolu. Vision-Based Control for Robots by a Fully Spiking Neural System Relying on Cerebellar Predictive Learning, submitted to IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. [pdf]

  • O. Zahra and D. Navarro-Alarcon. A Self-Organizing Network with Varying Density Structure for Characterizing Sensorimotor Transformations in Robotic Systems. 20th Towards Autonomous Robotic Systems Conference (TAROS), pp. 167–178, 2019. [pdf]

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