18 citations · 59 across the 30 of their papers we have counts for
5 papers · 1 filter
BIT-Nav: Brain-Inspired Trajectory Memory for Embodied Navigation
Rithvik Jonna, Aakash Gurram, Man Namgung +2
Vision-Language Models (VLMs) for embodied navigation rely on selecting a fixed number of frames from a growing trajectory history. As episodes extend, this selection grows increas…
Embodied Foundation Models at the Edge: A Survey of Deployment Constraints and Mitigation Strategies
Utkarsh Grover, Ravi Ranjan, Mingyang Mao +9
Deploying foundation models in embodied edge systems is fundamentally a systems problem, not just a problem of model compression. Real-time control must operate within strict size,…
OA-NBV: Occlusion-Aware Next-Best-View Planning for Human-Centered Active Perception on Mobile Robots
Boxun Hu, Chang Chang, Jiawei Ge +4
We naturally step sideways or lean to see around the obstacle when our view is blocked, and recover a more informative observation. Enabling robots to make the same kind of viewpoi…
EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment
Mikolaj Walczak, Romina Aalishah, Wyatt Mackey +5
Deep reinforcement learning agents are often fragile while humans remain adaptive and flexible to varying scenarios. To bridge this gap, we present EDEN, a biologically inspired na…
ATLASv2: LLM-Guided Adaptive Landmark Acquisition and Navigation on the Edge
Mikolaj Walczak, Uttej Kallakuri, Tinoosh Mohsenin
Autonomous systems deployed on edge devices face significant challenges, including resource constraints, real-time processing demands, and adapting to dynamic environments. This wo…