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Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound
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A modular planar robotic manipulandum with end-point torque control.

Ian S Howard1, James N Ingram, Daniel M Wolpert

  • 1Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB21PZ, UK. ish22@cam.ac.uk

Journal of Neuroscience Methods
|May 20, 2009
PubMed
Summary

Researchers developed a versatile robotic system (vBOT) for studying human motor control, including novel variants for dynamic learning, stiffness, and object manipulation tasks. This system enhances motor control research by simulating object properties and tool use through precise force and torque application.

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Area of Science:

  • Robotics
  • Neuroscience
  • Biomechanics
  • Human Motor Control

Background:

  • Robotic manipulanda are crucial for studying human arm motor control, enabling force application based on arm state.
  • Existing designs often focus on motor learning or stiffness, with limited end-point torque control for object simulation and tool use studies.

Purpose of the Study:

  • To introduce a modular, general-purpose two-dimensional planar manipulandum (vBOT) optimized for dynamic learning paradigms.
  • To present variants (WristBOT and StiffBOT) addressing limitations in torque control and stiffness studies.
  • To evaluate the performance of the vBOT system and its variants.

Main Methods:

  • Development of a modular, two-dimensional planar manipulandum (vBOT) with a carbon fibre arm and timing pulley system.
  • Introduction of WristBOT with a cable drive for torque application and StiffBOT with a rigid arm for stiffness studies.
  • Performance evaluation of vBOT variants for effective end-point mass, viscosity, and stiffness.

Main Results:

  • The vBOT design minimizes intrinsic dynamics without active compensation.
  • WristBOT enables torque application for object manipulation, and StiffBOT is suitable for stiffness studies.
  • Subjects demonstrated perception of object orientation via haptic feedback from rotational dynamics using WristBOT.

Conclusions:

  • The vBOT system and its variants offer a versatile platform for diverse motor control research, including dynamic learning, stiffness, and object interaction.
  • The WristBOT variant successfully facilitates object manipulation tasks, highlighting the importance of haptic feedback in perceiving object properties.
  • This robotic system advances the investigation of neural control mechanisms, biomechanics, and human interaction with virtual or real objects.