research-article

Sigma-Delta Networks for Robot Arm Control

Authors:

Wallace Lawson,

Anthony Harrison,

J. Gregory TraftonAuthors Info & Claims

NICE '23: Proceedings of the 2023 Annual Neuro-Inspired Computational Elements Conference

Pages 35 - 40

https://doi.org/10.1145/3584954.3584964

Published: 12 April 2023 Publication History

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Abstract

Our autonomous robot, Bight, can be a reliable teammate that is capable of assisting in performing routine maintenance tasks on a Naval vessel. In this paper, we consider the task of maintaining the electrical panel. A vital first step is putting the robot into the correct position to view all of the parts of the electrical panel. The robot can get close, but the arm of the robot will need to move to where it can see everything. Here, we propose to solve this using a sigma delta spiking network that is trained using deep Q learning. Our approach is able to successfully solve this problem at varying distances. While we show how this works on this specific problem, we believe this approach to be general enough to be applied to any similar problem.

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Cited By

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Amaya CEames EPalinauskas GPerzylo ASandamirskaya Yvon Arnim A(2024)Neuromorphic force-control in an industrial task: validating energy and latency benefits2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10802430(717-724)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IROS58592.2024.10802430

Index Terms

Sigma-Delta Networks for Robot Arm Control
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Robotics
      1. Robotic autonomy
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Reinforcement learning
    2. Machine learning approaches
      1. Neural networks

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NICE '23: Proceedings of the 2023 Annual Neuro-Inspired Computational Elements Conference

April 2023

124 pages

ISBN:9781450399470

DOI:10.1145/3584954

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

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Published: 12 April 2023

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NICE 2023

NICE 2023: Neuro-Inspired Computational Elements Conference

April 11 - 14, 2023

TX, San Antonio, USA

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Amaya CEames EPalinauskas GPerzylo ASandamirskaya Yvon Arnim A(2024)Neuromorphic force-control in an industrial task: validating energy and latency benefits2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10802430(717-724)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IROS58592.2024.10802430

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Abstract

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Recommendations

Humanoid robot control using depth camera

Simulating CALUMA CAssino Low-cost hUMAnoid robot carrying a load

Design of the ATRON lattice-based self-reconfigurable robot

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