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The muscles of the forearm that move the wrist, hand, and digits are numerous and diverse. They can be classified into two groups based on their location and function — the anterior and posterior compartment muscles.
Anterior Compartment
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A 3D-printed neuromorphic humanoid hand for grasping unknown objects.

Chao Bao1, Tae-Ho Kim1, Amirhossein Hassanpoor Kalhori1

  • 1Additive Manufacturing Laboratory, School of Mechatronic Systems Engineering, Simon Fraser University, Surrey V3T 0A3, Canada.

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|April 8, 2022
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Summary
This summary is machine-generated.

This study introduces a 3D neuromorphic humanoid hand that mimics reflex arcs for rapid, unconscious responses. This energy-saving, in-memory computing system offers a novel approach for artificial intelligence in robotics.

Keywords:
AutomationComputer hardwareManufacturingRoboticsSensor system

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Area of Science:

  • Robotics and Artificial Intelligence
  • Neuroscience and Neuromorphic Engineering
  • Materials Science and 3D Printing

Background:

  • Conventional von Neumann architecture processors are energy-intensive.
  • Neuromorphic systems offer energy-saving in-memory computing capabilities.
  • Mimicking biological systems can lead to more efficient and responsive artificial intelligence.

Purpose of the Study:

  • To develop a 3D neuromorphic humanoid hand capable of artificial unconscious responses.
  • To integrate bioinspired signal perception and processing with a biomimetic reflex arc.
  • To demonstrate an intelligent robotic hand that can adapt its grip force without conventional control.

Main Methods:

  • Fabrication of a 3D humanoid hand using multi-axis robot 3D printing technology.
  • Integration of 3D-printed pressure sensors and a portable neuromorphic device.
  • Implementation of a system that mimics the biological reflex arc for signal management.

Main Results:

  • The 3D neuromorphic hand successfully mimics reflex arc functions for quick responses.
  • The system manages complex spatiotemporal information for bioinspired signal perception and processing.
  • The hand can hold unknown objects with automatically adjusted gripping force, bypassing traditional processors.

Conclusions:

  • The proposed 3D neuromorphic humanoid hand represents a novel approach to artificial unconscious responses.
  • This system demonstrates the potential of neuromorphic engineering for energy-efficient and adaptive robotics.
  • The biomimetic design offers a pathway towards more intelligent and responsive artificial agents.