6 papers
VLM-GLoc: Vision-Language Model Enhanced Monte Carlo Localization for Robust Semantic Global Localization in Cluttered Quasi-Static Environments
Shivendra Agrawal, Bradley Hayes
Global localization in geometrically aliased, quasi-static environments such as grocery stores, offices, schools, and hospitals poses a significant challenge for mobile robots. Gro…
GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology
Shivendra Agrawal, Bradley Hayes
Navigating complex, densely packed environments like retail stores, warehouses, and hospitals poses a significant spatial grounding challenge for humans and embodied AI. In these s…
RF-Modulated Adaptive Communication Improves Multi-Agent Robotic Exploration
Lorin Achey, Breanne Crockett, Christoffer Heckman +1
Reliable coordination and efficient communication are critical challenges for multi-agent robotic exploration of environments where communication is limited. This work introduces A…
Robust Robotic Exploration and Mapping Using Generative Occupancy Map Synthesis
Lorin Achey, Alec Reed, Brendan Crowe +2
We present a novel approach for enhancing robotic exploration by using generative occupancy mapping. We implement SceneSense, a diffusion model designed and trained for predicting…
Online Diffusion-Based 3D Occupancy Prediction at the Frontier with Probabilistic Map Reconciliation
Alec Reed, Lorin Achey, Brendan Crowe +2
Autonomous navigation and exploration in unmapped environments remains a significant challenge in robotics due to the difficulty robots face in making commonsense inference of unob…
SceneSense: Diffusion Models for 3D Occupancy Synthesis from Partial Observation
Alec Reed, Brendan Crowe, Doncey Albin +3
When exploring new areas, robotic systems generally exclusively plan and execute controls over geometry that has been directly measured. When entering space that was previously obs…