SAFARI: Semantic- And Frontier-driven Autonomous Risk Inspection
Overview
This paper introduces SAFARI, a framework that unifies semantic object detection with frontier-based exploration to enable risk-aware autonomous mapping in hazardous environments. Evaluated across 11 missions on a quadruped platform at three field sites, the system achieved 98.7% coverage of accessible areas and operated without human intervention for 97.6% of mission time, detecting objects as small as 15cm. Ablation studies highlight the importance of object-size awareness and safety-aware path planning for effective hazardous-object search.
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Event evidence and corrections
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Control: reported autonomous
“arXiv:2610.41456v1 Announce Type: new Abstract: Robotic exploration can reduce human exposure to hazardous environments by autonomously searching unknown areas for objects of interest while constructing a complete, risk-aware map. However, existing autonomous exploration approaches typically prioritize geometric coverage or information gain, without explicitly coupling semantic object detection and the risk associate”
Exact source · revision 1Source owner not reported
Reported quantity · minimum_detected_object_size_cm: 15 other · Basis not reported
“tion and planning with both geometric and semantic evidence. We evaluated SAFARI in 11 missions across three field sites on a quadruped platform. The framework achieved an average coverage of 98.7% of the accessible mission area, without operator intervention for 97.6% of mission time, and detected objects with characteristic dimensions as small as 15cm. Lastly, through ablation studies and a detailed analysis of sys”
Exact source · revision 1Source owner not reported
Reported quantity · mission_count: 11 other · reported trials
“tion and planning with both geometric and semantic evidence. We evaluated SAFARI in 11 missions across three field sites on a quadruped platform. The framework achieved an average coverage of 98.7% of the accessible mission area, without operator intervention for 97.6% of mission time, and detected objects with characteristic dimensions as small as 15cm. Lastly, through ablation studies and a detailed analysis of sys”
Exact source · revision 1Source owner not reported
Reported quantity · field_sites_count: 3 other · reported trials
“tion and planning with both geometric and semantic evidence. We evaluated SAFARI in 11 missions across three field sites on a quadruped platform. The framework achieved an average coverage of 98.7% of the accessible mission area, without operator intervention for 97.6% of mission time, and detected objects with characteristic dimensions as small as 15cm. Lastly, through ablation studies and a detailed analysis of sys”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalSAFARI: Semantic- And Frontier-driven Autonomous Risk Inspection
This paper introduces SAFARI, a framework that unifies semantic object detection with frontier-based exploration to enable risk-aware autonomous mapping in hazardous environments. Evaluated across 11 missions on a quadruped platform at three field sites, the system achieved 98.7% coverage of accessible areas and operated without human intervention for 97.6% of mission time, detecting objects as small as 15cm. Ablation studies highlight the importance of object-size awareness and safety-aware path planning for effective hazardous-object search.
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