{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T08:53:25Z","timestamp":1775120005127,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Autonomous navigation in subterranean mines is hindered by deformable terrain, dust-laden visibility, and densely packed, safety-critical machinery. We propose a systems-oriented navigation framework that embeds semantic priorities into reactive planning for energy-aware autonomy in Robot Operating System (ROS). A lightweight Convolutional Neural Network (CNN) detector fuses RGB-D and LiDAR data to classify obstacles like humans, haul trucks, and debris, writing risk-weighted virtual LaserScans to the local planner so obstacles are evaluated by relevance rather than geometry. By integrating class-specific inflation layers in costmaps within a cyber\u2013physical systems architecture, the system ensures ISO-compliant separation without sacrificing throughput. In Gazebo experiments with three obstacle classes and 60 runs, high-risk clearance increased by 34%, collisions dropped to zero, mission time remained statistically unchanged, and estimated kinematic effort increased by 6% relative to a geometry-only baseline. These results demonstrate effective systems integration and a favorable safety\u2013efficiency trade-off in industrial cyber\u2013physical environments, providing a reproducible reference for scalable deployment in real-world unstructured mining environments.<\/jats:p>","DOI":"10.3390\/systems13090799","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T15:10:46Z","timestamp":1757603446000},"page":"799","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Semantic Priority Navigation for Energy-Aware Mining Robots"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7197-8928","authenticated-orcid":false,"given":"Claudio","family":"Urrea","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, Faculty of Engineering, University of Santiago of Chile, Las Sophoras 165, Estaci\u00f3n Central, Santiago 9170020, Chile"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3552-1709","authenticated-orcid":false,"given":"Kevin","family":"Valencia-Arag\u00f3n","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Faculty of Engineering, University of Santiago of Chile, Las Sophoras 165, Estaci\u00f3n Central, Santiago 9170020, Chile"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1958-7289","authenticated-orcid":false,"given":"John","family":"Kern","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Faculty of Engineering, University of Santiago of Chile, Las Sophoras 165, Estaci\u00f3n Central, Santiago 9170020, Chile"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"ref_1","unstructured":"Ali, D., Iqbal, S., and Ahmad, N. 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