TY - GEN
T1 - Path Planning of the Turning Back of an Autonomous Large-Scale Six-Wheeled Dump Truck for Loading/Leaving Sediment Based on Backhoe Work
AU - Akegawa, Tetsu
AU - Ohno, Kazunori
AU - Kojima, Shotaro
AU - Yamada, Kento
AU - Go, Wiru
AU - Suzuki, Taro
AU - Kiribayashi, Seiga
AU - Komatsu, Tomohiro
AU - Miyamoto, Naoto
AU - Suzuki, Takahiro
AU - Shibata, Yukinori
AU - Asano, Kimitaka
AU - Nagatani, Keiji
AU - Tadokoro, Satoshi
N1 - Funding Information:
This research was partially supported by the NEDO/Development of integration technology at the core of next-generation artificial intelligence and robots, research and development on automation of sediment transport at local small and medium-sized construction sites using robot technology and AI. Grand Number: 18065741.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - There is an urgent need to automate earthmoving activities for large-scale six-wheeled dump trucks using retrofitted sensors and driving robots. A dump truck stops at a loading position with its bed facing the backhoe to fill the bed with sediment quickly. It also stops with its bed facing the leaving position. Therefore, it is necessary to plan ahead to safely and accurately enter and exit those working positions. However, existing path planners did not generate a path with a turning point that is suitable for large-scale six-wheeled dump truck loading sediment. In this paper, we propose an online pathplanning method with the following main features. First, a path is planned to move the dump truck forward and/or backward to the working position to load and/or leave sediment. Second, when a new working position is designated, a path from the turning position to the new goal position is automatically established. We verified the proposed method using a simulator of the dump truck (3.5 m × 11 m), showing that it is possible to properly account for the turning radius of the dump truck. The result reveals that it is possible to replan with a working position shift of 4.8 m or 33° from a 25 m distance and that the time required for replanning can be shortened to ≤ 7.56 s. We also confirmed that the large-scale autonomous dump truck can automatically stop at the loading position in cooperation with a humanoperated backhoe 10 out of 10 times with a stopping accuracy of 0.57 m and 5.29°.
AB - There is an urgent need to automate earthmoving activities for large-scale six-wheeled dump trucks using retrofitted sensors and driving robots. A dump truck stops at a loading position with its bed facing the backhoe to fill the bed with sediment quickly. It also stops with its bed facing the leaving position. Therefore, it is necessary to plan ahead to safely and accurately enter and exit those working positions. However, existing path planners did not generate a path with a turning point that is suitable for large-scale six-wheeled dump truck loading sediment. In this paper, we propose an online pathplanning method with the following main features. First, a path is planned to move the dump truck forward and/or backward to the working position to load and/or leave sediment. Second, when a new working position is designated, a path from the turning position to the new goal position is automatically established. We verified the proposed method using a simulator of the dump truck (3.5 m × 11 m), showing that it is possible to properly account for the turning radius of the dump truck. The result reveals that it is possible to replan with a working position shift of 4.8 m or 33° from a 25 m distance and that the time required for replanning can be shortened to ≤ 7.56 s. We also confirmed that the large-scale autonomous dump truck can automatically stop at the loading position in cooperation with a humanoperated backhoe 10 out of 10 times with a stopping accuracy of 0.57 m and 5.29°.
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U2 - 10.1109/SII52469.2022.9708879
DO - 10.1109/SII52469.2022.9708879
M3 - Conference contribution
AN - SCOPUS:85126178652
T3 - 2022 IEEE/SICE International Symposium on System Integration, SII 2022
SP - 511
EP - 518
BT - 2022 IEEE/SICE International Symposium on System Integration, SII 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE/SICE International Symposium on System Integration, SII 2022
Y2 - 9 January 2022 through 12 January 2022
ER -