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Aerial Track-Guided Autonomous Soft Ring Robot.

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  • 1Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA.

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Summary
This summary is machine-generated.

An autonomous soft robot navigates 3D tracks using constant light. This twisted ring robot, inspired by aerial trams, moves linearly by curling around threads, overcoming obstacles and carrying heavy loads.

Keywords:
liquid crystal elastomerssoft machine

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Area of Science:

  • Robotics
  • Materials Science
  • Soft Robotics

Background:

  • Soft robots offer unique advantages in complex environments due to their flexibility.
  • Precise motion control in 3D space remains a significant challenge for soft robotic systems.
  • Existing soft robots often require complex spatiotemporal control of actuation sources for navigation.

Purpose of the Study:

  • To develop an autonomous soft robot capable of navigating pre-defined tracks in 3D space.
  • To achieve motion control using constant photothermal actuation without complex external control.
  • To demonstrate the robot's adaptability and load-carrying capacity on diverse tracks.

Main Methods:

  • Fabrication of a soft twisted ring robot from liquid crystal elastomers.
  • Utilizing constant infrared light for photothermal actuation, inducing self-flipping motion.
  • Employing screw theory to translate rotary motion into linear movement along thread-based tracks.

Main Results:

  • The soft ring robot autonomously navigated various 3D tracks (circular, polygonal, spiral) under constant photothermal actuation.
  • The robot demonstrated obstacle negotiation (e.g., knots) and the ability to ascend/descend steep slopes (up to 80°).
  • The robot successfully transported loads exceeding 12 times its own weight and adapted to tracks of varying materials and sizes.

Conclusions:

  • The developed soft twisted ring robot offers a novel, autonomous locomotion strategy for 3D environments.
  • The photothermal actuation and screw-based mechanism provide robust and adaptable navigation capabilities.
  • This approach overcomes limitations of complex control systems and demonstrates potential for versatile soft robotic applications.