2 citations · 2 across the 5 of their papers we have counts for
6 papers
FLEET: Formal Language-Grounded Scheduling for Heterogeneous Robot Teams
Corban Rivera, Grayson Byrd, Meghan Booker +6
Coordinating heterogeneous robot teams from free-form natural-language instructions is hard. Language-only planners struggle with long-horizon coordination and hallucination, while…
Constrained Natural Language Action Planning for Resilient Embodied Systems
Grayson Byrd, Corban Rivera, Bethany Kemp +5
Replicating human-level intelligence in the execution of embodied tasks remains challenging due to the unconstrained nature of real-world environments. Novel use of large language…
Beyond Rigid AI: Towards Natural Human-Machine Symbiosis for Interoperative Surgical Assistance
Lalithkumar Seenivasan, Jiru Xu, Roger D. Soberanis Mukul +6
Emerging surgical data science and robotics solutions, especially those designed to provide assistance in situ, require natural human-machine interfaces to fully unlock their poten…
EmbodiedRAG: Dynamic 3D Scene Graph Retrieval for Efficient and Scalable Robot Task Planning
Meghan Booker, Grayson Byrd, Bethany Kemp +2
Recent advances in Large Language Models (LLMs) have helped facilitate exciting progress for robotic planning in real, open-world environments. 3D scene graphs (3DSGs) offer a prom…
ConceptAgent: LLM-Driven Precondition Grounding and Tree Search for Robust Task Planning and Execution
Corban Rivera, Grayson Byrd, William Paul +12
Robotic planning and execution in open-world environments is a complex problem due to the vast state spaces and high variability of task embodiment. Recent advances in perception a…
Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models
Hao Ding, Lalithkumar Seenivasan, Hongchao Shu +7
Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning complex action sequences. Sound plann…