4 citations · 4 across the 7 of their papers we have counts for
7 papers
Belief Consistency Between Foundation-Model Evidence and Geometric Perception in Persistent Robotic Maps
Christoffer Heckman, Harel Biggie, Brendan Crowe +1
Persistent maps used by autonomous robots increasingly fuse a geometric perception stack whose assertions are well-characterized with a foundation-model channel that produces seman…
SceneGraphGrounder: Zero-Shot 3D Visual Grounding via Structured Scene Graph Matching
Xuefei Sun, Xujia Zhang, Brendan Crowe +2
Zero-shot 3D visual grounding requires localizing objects in unstructured environments from free-form natural language. Recent vision-language model (VLM) approaches achieve promis…
Octree Diffusion for Semantic Scene Generation and Completion
Xujia Zhang, Brendan Crowe, Christoffer Heckman
The completion, extension, and generation of 3D semantic scenes are an interrelated set of capabilities that are useful for robotic navigation and exploration. Existing approaches…
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…
Robust Maximum Entropy Behavior Cloning
Mostafa Hussein, Brendan Crowe, Marek Petrik +1
Imitation learning (IL) algorithms use expert demonstrations to learn a specific task. Most of the existing approaches assume that all expert demonstrations are reliable and trustw…