A Novel Approach to Increase the Locomotion Performance of Mobile Robots in Fields With Tall Grasses

Katsuaki Tanaka, Hiroyuki Ishii, Daisuke Kuroiwa, Yuya Okamoto, Eric Mossor, Hikaru Sugita, Qing Shi, Satoshi Okabayashi, Yusuke Sugahara, Atsuo Takanishi

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

One of the main problems faced by land-based mobile robots is their locomotion performance on rough outdoor terrain. We focused on the navigation of grassy areas such as riversides and forests. These have many types of obstacles, which make robot locomotion difficult. Several studies have been conducted on locomotive mechanisms for rough terrains that have performed well. However, most of these mechanisms cannot pass through grass taller than their own height while using a small number of actuators. We designed a novel mechanism that uses only two motors to ensure a high locomotive ability over a field with tall grasses. We also designed "Grassbreaker" by attaching an outer covering to a tiny mobile robot shaped like an icebreaker. We found that the robot's shape greatly influences its mobility in a tall grass field and that the robot continued to move forward while bending tall grasses such as reeds. The significant difference (p < 0.05) between the average speeds of Grassbreaker and the robot without the outer covering was confirmed in an experiment. The robot's new shape is significant not only because it fills a gap in previous research work but also because this method does not require any additional actuators such as conventional cutting and bending methods.

Original languageEnglish
Article number7353152
Pages (from-to)122-129
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume1
Issue number1
DOIs
Publication statusPublished - 2016 Jan

Keywords

  • Forestry
  • Legged locomotion
  • Mobile robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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