Vision-language navigation (VLN) models perform well but target compute-rich platforms, limiting deployment on memory- and power-constrained robotic edge devices. Compression alone does not establish whether a VLN model fits the memory, latency, and energy budgets of an edge platform while preserving navigation behavio...
Rithvik Jonna, Man Namgung, Aakash Gurram et al.· 0 citations
This work proposes Nutri-ATLAS, an Embodied Agent for Tabulated Lookup and Assistance for smarter nutrition in the real world that integrates graph-grounded nutrition reasoning, hardware-aware LLM selection, and robot-based evidence acquisition.
Utteja Kallakuri, Bo-Xun Hu, A. Butala et al.· 0 citations
LEAP-NBV is presented, a lightweight active-perception framework that runs foundation-model-driven Next-Best-View (NBV) planning on-board an edge device and reports measured on-device latency and energy.
Occlusion-Aware Next-Best-View Planning for Human-Centered Active Perception on Mobile Robots (OA-NBV), an occlusion-aware NBV pipeline that autonomously selects the next traversable viewpoint to obtain a more complete view of an occluded human.
Bo Hu, Chang-Ming Chang, J. Ge et al.· arXiv.org· 4 citations· ⚡1
This survey provides a comprehensive overview of techniques that enable GenAI deployment at the edge, covering software optimizations, hardware innovations, and system-level frameworks, with particular emphasis on hardware-focused approaches.
Mozhgan Navardi, Yuzhe Fu, Yueqian Lin et al.· ACM Computing Surveys· 0 citations
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