5 papers
ViLAM: Distilling Vision-Language Reasoning into Attention Maps for Social Robot Navigation
Mohamed Elnoor, Kasun Weerakoon, Gershom Seneviratne +3
We introduce ViLAM, a novel method for distilling vision-language reasoning from large Vision-Language Models (VLMs) into spatial attention maps for socially compliant robot naviga…
Empowering Dynamic Urban Navigation with Stereo and Mid-Level Vision
Wentao Zhou, Xuweiyi Chen, Vignesh Rajagopal +3
The success of foundation models in language and vision motivated research in fully end-to-end robot navigation foundation models (NFMs). NFMs directly map monocular visual input t…
DR. Nav: Semantic-Geometric Representations for Proactive Dead-End Recovery and Navigation
Vignesh Rajagopal, Kasun Weerakoon Kulathun Mudiyanselage, Gershom Devake Seneviratne +5
We present DR. Nav (Dead-End Recovery-aware Navigation), a novel approach to autonomous navigation in scenarios where dead-end detection and recovery are critical, particularly in…
BehAV: Behavioral Rule Guided Autonomy Using VLMs for Robot Navigation in Outdoor Scenes
Kasun Weerakoon, Mohamed Elnoor, Gershom Seneviratne +5
We present BehAV, a novel approach for autonomous robot navigation in outdoor scenes guided by human instructions and leveraging Vision Language Models (VLMs). Our method interpret…
Robot Navigation Using Physically Grounded Vision-Language Models in Outdoor Environments
Mohamed Elnoor, Kasun Weerakoon, Gershom Seneviratne +5
We present a novel autonomous robot navigation algorithm for outdoor environments that is capable of handling diverse terrain traversability conditions. Our approach, VLM-GroNav, u…