AI RESEARCH
AURASeg: Attention-guided Upsampling with Residual-Assistive Boundary Refinement for Onboard Robot Drivable-Area Segmentation
arXiv CS.CV
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ArXi:2510.21536v4 Announce Type: replace-cross Free space ground segmentation is essential to navigate autonomous robots, recognize drivable zones, and traverse efficiently. Fine-grained features remain challenging for existing segmentation models, particularly for robots in indoor, outdoor and road-scene environments. These difficulties arise from ineffective multi-scale processing, sub-optimal boundary refinement, and limited feature representation.