TY - JOUR
T1 - Revisiting Scaling Laws for Robotic Mobility in Granular Media
AU - Thoesen, Andrew
AU - McBryan, Teresa
AU - Green, Marko
AU - Mick, Darwin
AU - Martia, Justin
AU - Marvi, Hamid
N1 - Funding Information:
Manuscript received September 10, 2019; accepted December 31, 2019. Date of publication January 22, 2020; date of current version January 31, 2020. This letter was recommended for publication by Associate Editor S. Rathinam and Editor D. Song upon evaluation of the reviewers’ comments. This work was supported by the Arizona State University. (Corresponding author: Hamidreza Marvi.) The authors are with the School for Engineering of Matter, Transport, and Energy, Ira A. Fulton Schools of Engineering, Arizona State University Tempe, AZ 85287, USA (e-mail: andrew.thoesen@gmail.com; mcbryan.teresa@ gmail.com; mkgreencccc@gmail.com; dpmick@asu.edu; jmartia@asu.edu; hmarvi@asu.edu).
Funding Information:
The authors would like to thank members of the BIRTH Lab for their assistance and Arizona State University for funding.
Publisher Copyright:
© 2016 IEEE.
PY - 2020/4
Y1 - 2020/4
N2 - The development, building, and testing of robotic vehicles for applications in deformable media can be costly. Typical approaches rely on full-sized builds empirically evaluating performance metrics such as drawbar pull and slip. Recently developed granular scaling laws offer a new opportunity for terramechanics as a field. Using non-dimensional analysis on the wheel characteristics and treating the terrain as a deformable continuum, the performance of a larger, more massive wheel may be predicted from a smaller one. This allows for new wheel design approaches. However, robot-soil interaction and specific characteristics of the soil or robot dynamics may create discrepancies in prediction. In particular, we find that for a lightweight rover (2-5 kg), the scaling laws significantly overpredicted mechanical power requirements. To further explore the limitations of the current granular scaling laws, a pair of differently sized grousered wheels were tested at three masses and a pair of differently sized sandpaper wheels were tested at two masses across five speeds. Analysis indicates similar error for both designs, a mass dependency for all five pairs that explains the laws' overprediction, and a speed dependency for both of the heaviest sets. The findings create insights for using the laws with lightweight robots in granular media and generalizing granular scaling laws.
AB - The development, building, and testing of robotic vehicles for applications in deformable media can be costly. Typical approaches rely on full-sized builds empirically evaluating performance metrics such as drawbar pull and slip. Recently developed granular scaling laws offer a new opportunity for terramechanics as a field. Using non-dimensional analysis on the wheel characteristics and treating the terrain as a deformable continuum, the performance of a larger, more massive wheel may be predicted from a smaller one. This allows for new wheel design approaches. However, robot-soil interaction and specific characteristics of the soil or robot dynamics may create discrepancies in prediction. In particular, we find that for a lightweight rover (2-5 kg), the scaling laws significantly overpredicted mechanical power requirements. To further explore the limitations of the current granular scaling laws, a pair of differently sized grousered wheels were tested at three masses and a pair of differently sized sandpaper wheels were tested at two masses across five speeds. Analysis indicates similar error for both designs, a mass dependency for all five pairs that explains the laws' overprediction, and a speed dependency for both of the heaviest sets. The findings create insights for using the laws with lightweight robots in granular media and generalizing granular scaling laws.
KW - Field robots
KW - mining robotics
KW - space robotics and automation
KW - wheeled robots
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U2 - 10.1109/LRA.2020.2968031
DO - 10.1109/LRA.2020.2968031
M3 - Article
AN - SCOPUS:85079602161
SN - 2377-3766
VL - 5
SP - 1319
EP - 1325
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 2
M1 - 8966282
ER -