الملخص
Precise, high-speed control remains challenging for robots with complex actuation dynamics. Learning directly on hardware is further constrained by the cost of real-world interaction. We present an online model-based reinforcement learning framework that learns a probabilistic dynamics ensemble model from scratch for sampling-based model predictive control. A precision-gated contouring objective conditions the progress reward on path accuracy, prioritizing precision over speed. In a data-driven excavator simulator, the framework achieves higher sample efficiency than the evaluated model-based reinforcement learning baselines. We validate the framework by learning directly on an 11.5-ton Menzi Muck M445 hydraulic excavator, without demonstrations or simulation pretraining. After 20 minutes of interaction, the controller reaches tracking accuracy comparable to prior learned controllers trained on 100-150 minutes of data. After 40 minutes, it sustains sub-centimeter mean path error at high operating speeds.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Canales, C., Nan, F., Hutter, M., & Ruiz-del-Solar, J. (2026). Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control. https://omanscience.com/ar/articles/precision-at-speed-sample-efficient-online-model-based-reinforcement-learning-for-hydraulic-excavator-control
MLA 9
Canales, Claudio, et al. "Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control." https://omanscience.com/ar/articles/precision-at-speed-sample-efficient-online-model-based-reinforcement-learning-for-hydraulic-excavator-control.
شيكاغو (المؤلف–التاريخ)
Canales, Claudio, Fang Nan, Marco Hutter, and Javier Ruiz-del-Solar. 2026. "Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control." https://omanscience.com/ar/articles/precision-at-speed-sample-efficient-online-model-based-reinforcement-learning-for-hydraulic-excavator-control.
هارفارد
Canales, C., Nan, F., Hutter, M. and Ruiz-del-Solar, J. (2026) 'Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control', Available at: https://omanscience.com/ar/articles/precision-at-speed-sample-efficient-online-model-based-reinforcement-learning-for-hydraulic-excavator-control.
فانكوفر
Canales C, Nan F, Hutter M, Ruiz-del-Solar J. Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control. https://omanscience.com/ar/articles/precision-at-speed-sample-efficient-online-model-based-reinforcement-learning-for-hydraulic-excavator-control
IEEE
C. Canales, F. Nan, M. Hutter, and J. Ruiz-del-Solar, "Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control," https://omanscience.com/ar/articles/precision-at-speed-sample-efficient-online-model-based-reinforcement-learning-for-hydraulic-excavator-control.