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Object-of-Interest Perception in a Reconfigurable Rolling-Crawling Robot.

Archana Semwal1, Melvin Ming Jun Lee1, Daniela Sanchez1

  • 1Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore.

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|July 27, 2022
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Summary
This summary is machine-generated.

Researchers developed a perception system for a reconfigurable robot inspired by huntsman spiders. This system enables the robot to identify pathways and select optimal locomotion modes, enhancing its maneuverability in complex environments.

Keywords:
computer visiondeep learningenvironment perceptionlocomotion modeobject-of-interestshape reconfigurable robots

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Area of Science:

  • Robotics
  • Computer Vision
  • Biomimetics

Background:

  • Reconfigurable robots require sophisticated perception systems to adapt locomotion to diverse environments.
  • The huntsman spider (Cebrenus Rechenburgi) exhibits versatile locomotion, serving as inspiration for robotic development.

Purpose of the Study:

  • To develop and validate an object-of-interest perception system for a reconfigurable rolling-crawling robot.
  • To enable the robot to identify appropriate locomotion modes (rolling or crawling) based on environmental perception.

Main Methods:

  • A reconfigurable robot, Scorpio, with rolling and crawling capabilities was utilized.
  • A Pyramid Scene Parsing Network (PSPNet) was trained on a custom dataset distinguishing unobstructed and obstructed paths.
  • The framework was evaluated using mean Intersection over Union (mIOU) in offline and real-time tests.

Main Results:

  • The trained PSPNet achieved mIOU scores of 72.28% (offline) and 70.63% (online).
  • The proposed framework outperformed semantic segmentation benchmarks (HRNet, Deeplabv3) in mIOU and speed.
  • The system demonstrated stable robot maneuverability and accurate locomotion mode selection in complex pathways.

Conclusions:

  • The developed perception framework effectively guides locomotion mode selection in reconfigurable robots.
  • Biomimetic approaches, inspired by spiders, can lead to advanced robotic capabilities.
  • The system offers enhanced accuracy and efficiency for robots navigating varied terrains.