Tetsu Akegawa — accepted AI-conference papers

2022

Loading an Autonomous Large-Scale Dump Truck: Path Planning Based on Motion Data from Human-Operated Construction Vehicles

Tetsu Akegawa, Kazunori Ohno, Shotaro Kojima, Naoto Miyamoto, Taro Suzuki, Tomohiro Komatsu +4

IROS 2022poster

A large-scale dump truck that automatically transports earth and sand in cooperation with a human-operated backhoe is of interest to the construction industry. A human-operated dump truck generally drives slightly past the desired loading position and then backs up to it for loading the sediment. Th…

Cited by 2 Source ↗Scholar ↗

2021

Semantic Mapping of Construction Site From Multiple Daily Airborne LiDAR Data

Thomas Westfechtel, Kazunori Ohno, Tetsu Akegawa, Kento Yamada, Ranulfo Plutarco Bezerra Neto, Shotaro Kojima +9

RA-L 2021

Semantic maps are an important tool to provide robots with high-level knowledge about the environment, enabling them to better react to and interact with their surroundings. However, as a single measurement of the environment is solely a snapshot of a specific time, it does not necessarily reflect t

Cited by 9 Source ↗Scholar ↗