Papers
7
Total Citations
51
H-Index
3
About
Eric Halbach’s research career is defined by a pioneering drive to make heavy machinery intelligent, autonomous, and practical. His primary focus lies in robotic earthmoving, where he has made foundational contributions to automated wheel loader control. His most influential work, "Job Planning and Supervisory Control for Automated Earthmoving Using 3D Graphical Tools" (2013, 20 citations), established a framework for translating complex worksite geometry into actionable machine commands. Halbach further advanced the field with his end-to-end Neural Network pile loading controller, trained by demonstration (2019, 18 citations), a landmark paper that showed how learning from human operators could enable a robotic loader to autonomously dig and scoop material with remarkable effectiveness. Beyond earthmoving, his work spans simulation development for robotic tasks, entropy-based coordination for multi-robot maintenance fleets, and even agricultural robotics, including a weeding robot for seedling removal (2024). Halbach’s impact is seen in his blend of rigorous simulation, practical job planning, and machine learning—paving the way for autonomous construction and agricultural vehicles that can operate safely and efficiently in unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Neural Network Pile Loading Controller Trained by Demonstration18 citations · 2019
- 3Development of a simulator for modeling robotic earth-moving tasks5 citations · 2007
- 4A Weeding Robot for Seedling Removal2 citations · 2024
- 5
- 6
- 7High-Level Job Planning for Automated Earthmoving2 citations · 2016