2026-08-20 マサチューセッツ工科大学(MIT)
“This is a more intuitive way to command the machine,” says Hermano Krebs. Krebs sees the interface as a faster way to train excavator operators, as well as a new way to physically operate the machines, both on-site and remotely. Image: Courtesy of the researchers
＜関連情報＞
- https://news.mit.edu/2026/mit-engineers-design-better-controller-operating-construction-diggers-0820
- https://ascelibrary.org/doi/10.1061/JCCEE5.CPENG-7488
掘削機オペレーターのための包括的なトレーニングプラットフォーム：仮想環境におけるジョイントスペースおよびワールドスペースインターフェースを用いたトレーニング A Comprehensive Training Platform for Excavator Operators: Training with Joint-Space and World-Space Interfaces in Virtual Environments
H. Ishida, M. Alencastre-Miranda, T. Hoshino, A. Martinez Guerra, S. Jeong, D. Suzuki, J. Buzzatto, E. Bamani Beeri, D. Usui, S. Tsukahara, and H. I. Krebs
Journal of Computing in Civil Engineering Published:Aug 17, 2026
DOI:https://doi.org/10.1061/JCCEE5.CPENG-7488
Abstract
We developed a comprehensive hydraulic excavator training simulator to evaluate and train operator skills using both traditional joysticks (JS) and a novel world-space interface (WSI). The simulator features multiple virtual environments modeled after real construction sites, each with varying levels of difficulty to train and assess naive operators. The simulator accurately reproduces the excavator’s motion dynamics, including its hydraulic behavior, mass, and inertia. To simulate the environment dynamics in real time, we employed the Unity3D physics engine to interact with solids (e.g., when removing fallen rocks) and assets with modified shaders to simulate digging or dumping dirt. The novel WSI is a scaled version of the excavator’s linkage, affording a more intuitive control scheme to a naive operator. We conducted two complementary studies: (1) evaluating training effectiveness with traditional joysticks, and (2) comparing performance between joysticks and the WSI. Results showed that naive subjects could improve their performance with joysticks after 7 training days. Naive subjects’ posttraining performance was not significantly different from that of expert operators for simple tasks such as digging and dumping. The use of the WSI resulted in 37% faster cycle times than the joystick interface at first use, closely approximating the posttraining performance of naive operators.
