NDLI: Controlling articulated robots in task-space with spiking silicon neurons

Content Provider	IEEE Xplore Digital Library
Author	Menon, S. Fok, S. Neckar, A. Khatib, O. Boahen, K.
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA (Fok, S.; Neckar, A.) \|\| Dept. of Bioeng., Stanford Univ., Stanford, CA, USA (Boahen, K.) \|\| Dept. of Comput. Sci., Stanford Univ., Stanford, CA, USA (Menon, S.; Khatib, O.)
Abstract	Emulating how humans coordinate articulated limbs within the brain's power budget promises to accelerate progress in building autonomous biomimetic robots. Here, we used a neuromorphic approach - low-power analog silicon spiking neurons - to control an articulated robot in real-time. We obtained a closed-form control function that computes robot motor torques given the robot's joint angles (state) and desired end-effector forces; factorized the function into a set of sub-functions over five unique three-dimensional domains; and regressed each sub-function on to the steady-state spiking responses of one out of five silicon spiking-neuron pools. The spiking pools controlled a three degree-of-freedom robot's motor torques in real-time and performed reaches to arbitrary locations in space with less than 2 cm root-mean-square trajectory tracking error (of an analytical controller). The controller is compliant and can draw shapes with a pen on a dynamically perturbed surface while remaining stable. Using force control resulted in linear responses to perturbations in end-effector coordinates (task-space), which effectively filtered noise due to neuron spikes. Factorizing the controller reduced the neural regression's complexity to cubic in the dynamic range of the robot's state and desired forces. Doing so made acquiring spiking responses for regression tractable in time (~2-3 min), and enabled reliable trajectory tracking with only 1280 neurons. This is the first time a neuromorphic system has achieved realtime manipulation for an articulated robot with three or more degrees-of-freedom.
Starting Page	181
Ending Page	186
File Size	2050657
Page Count	6
File Format	PDF
ISBN	9781479931262
ISSN	21551774
e-ISBN	9781479931286
DOI	10.1109/BIOROB.2014.6913773
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-12
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neuromorphics Robot kinematics Neurons Trajectory Joints Field programmable gate arrays
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in