2 citations · 3 across the 7 of their papers we have counts for
8 papers
SGM-SLAM: Scene Graph Matching for Data-Efficient Distributed SLAM
Yewei Huang, Tixiao Shan, Abhinav Rajvanshi +4
We introduce a data-efficient distributed Simultaneous Localization and Mapping (SLAM) framework for multi-robot operation in GPS-denied and communication-constrained environments.…
SayCoNav: Utilizing Large Language Models for Adaptive Collaboration in Decentralized Multi-Robot Navigation
Abhinav Rajvanshi, Pritish Sahu, Tixiao Shan +2
Adaptive collaboration is critical to a team of autonomous robots to perform complicated navigation tasks in large-scale unknown environments. An effective collaboration strategy s…
Graph2Nav: 3D Object-Relation Graph Generation to Robot Navigation
Tixiao Shan, Abhinav Rajvanshi, Niluthpol Mithun +1
We propose Graph2Nav, a real-time 3D object-relation graph generation framework, for autonomous navigation in the real world. Our framework fully generates and exploits both 3D obj…
DUDA: Distilled Unsupervised Domain Adaptation for Lightweight Semantic Segmentation
Beomseok Kang, Niluthpol Chowdhury Mithun, Abhinav Rajvanshi +2
Unsupervised Domain Adaptation (UDA) is essential for enabling semantic segmentation in new domains without requiring costly pixel-wise annotations. State-of-the-art (SOTA) UDA met…
GFM4MPM: Towards Geospatial Foundation Models for Mineral Prospectivity Mapping
Angel Daruna, Vasily Zadorozhnyy, Georgina Lukoczki +1
Machine Learning (ML) for Mineral Prospectivity Mapping (MPM) remains a challenging problem as it requires the analysis of associations between large-scale multi-modal geospatial d…
Uncertainty Propagation through Trained Deep Neural Networks Using Factor Graphs
Angel Daruna, Yunye Gong, Abhinav Rajvanshi +2
Predictive uncertainty estimation remains a challenging problem precluding the use of deep neural networks as subsystems within safety-critical applications. Aleatoric uncertainty…
Unsupervised Domain Adaptation for Semantic Segmentation with Pseudo Label Self-Refinement
Xingchen Zhao, Niluthpol Chowdhury Mithun, Abhinav Rajvanshi +2
Deep learning-based solutions for semantic segmentation suffer from significant performance degradation when tested on data with different characteristics than what was used during…
SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments
Abhinav Rajvanshi, Karan Sikka, Xiao Lin +3
Semantic reasoning and dynamic planning capabilities are crucial for an autonomous agent to perform complex navigation tasks in unknown environments. It requires a large amount of…