Connectionists: IJCNN-2020SS: Neural Mechanisms for Artificial and Natural Locomotions

[Felipe Maia Galvao Franca]

(IJCNN-28 https://wcci2020.org/ijcnn-sessions, the site of manuscript
submission is at the end of this page)



Organisers: Zhijun Yang, Vaibhav Gandhi, Felipe M.G. França, Mehmet
Karamanoglu



There are evidences showing that walking with adaptive gait patterns may be
an acquired characteristic possessed by legged animals and humans. A baby
animal or infant usually experiences an inept process to learn walking
before becoming fully adaptive to a complex terrain. This learning process
starts with reflexes reflecting involuntary responses to stimuli. It may
involve a complex sequence of activities for sensorimotor integration,
synchronization and coordination of cortical neurons and muscles. After the
relevant cortical regions are well acquainted with the external world, the
animals are considered as trained and represent the most capable walking
machine in nature.Many theoretical and experimental approaches have been
proposed intending to decipher the mechanisms underlying the natural
locomotion while presenting its artificial intelligence (AI) counterpart.
For instance, the finite state machine (FSM), in both deterministic and
probabilistic variants, are traditionally used to model the gait pattern
generation and transition. Recent years have seen the interest in this area
of research growing rapidly thanks to the emergence of new computing
methodologies using spiking neurons and neuronal populations, with the
neuron complexity ranging from the simplest integrate-and-firing type to
the classic Hodgkin-Huxley type. A special Izhikevich neuron can display an
abundant spectrum of real neuron activities. These methods show great
potential in modelling the natural locomotion models in this relatively new
research field. On the other hand, the modern technology provides us means
of implementing the theoretic models by using high performance computing
(HPC) techniques such as dedicated neuromorphic circuits, GPUs, FPGAs as
well as deep learning tools.


Scope and Topics
This special session brings together the new research works from academics
and industry related researchers in this prevalent area. The workshop aims
to promote the applications of multidisciplinary methods in investigating
and exploiting the neural mechanisms of natural locomotion. We invite
papers on both theory and applications of the broad area of neural control
for natural locomotion. The artificial locomotion systems, built upon the
mechanisms underlying the natural locomotion systems, are particularly
welcome. The topics of interest include, but are not limited to, the
following.



     • Neuroscience studies of natural locomotion and control

     • Novel mathematic models for gait pattern generation and transition

     • Central pattern generation models and applications

     • Somatosensory system, sensorimotor interaction and impacts on
locomotion

     • Machine learning and deep learning methods applicable for motion
control

     • Neuromorphic hardware implementation, parallel computing platforms
using state-of-the-

       art hardware such as GPU or FPGA for neural control of locomotion

     • Software frameworks, such as robot operating system (ROS),
applicable for robot control

     • Bayesian inference and hidden Markov models for decision making on
robot motion

     • Novel finite state machine methods, implementation and applications
in robotics

     • State-of-the-art robot projects using leading edge hardware and/or
software



Important Dates
31 Jan 2020                           Paper Submission Deadline

15 Mar 2020                          Paper Acceptance Notification Date

15 April 2020                          Final Paper Submission and Early
Registration Deadline

19-24 July 2020                     IEEE WCCI 2020, Glasgow, Scotland, UK



For more information, e.g., the manuscript format and submission, please
refer to the conference official website https://wcci2020.org/.



Please submit your manuscript by clicking on the following link. You need
an easychair account to submit your work.



https://easychair.org/conferences/?conf=ssnmanlijcnn2020

Any questions or comments on submitting your manuscripts? Please send email
to: z.yang at mdx.ac.uk

-- 
–––––––––––––––––––––––––––––––
Felipe M. G. França, PhD
Invited Professor of Computer Science and Engineering
Systems Engineering and Computer Science Program, COPPE
Universidade Federal do Rio de Janeiro
P.O. Box 68511, 21941-972, Rio de Janeiro, RJ, Brazil
felipe at ieee.org
felipe at cos.ufrj.br
–––––––––––––––––––––––––––––––
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