collaborators

6 papers

cs.RO2026

LMPath: Language-Mediated Priors and Path Generation for Aerial Exploration

Jonathan A. Diller, Fernando Cladera, Camillo J. Taylor +1

Traditional autonomous UAV search missions rely on geometric coverage patterns that ignore the semantic context of the target, leading to significant time waste in large-scale envi…

cs.LG2026

Retrieval Mechanisms Surpass Long-Context Scaling in Time Series Forecasting

Rishi Ahuja, Kumar Prateek, Simranjit Singh +1

Time Series Foundation Models (TSFMs) have borrowed the long context paradigm from natural language processing under the premise that feeding more history into the model improves f…

cs.RO2025

Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence

Zachary Ravichandran, Fernando Cladera, Ankit Prabhu +5

Heterogeneous robot teams operating in realistic settings often must accomplish complex missions requiring collaboration and adaptation to information acquired online. Because robo…

cs.RO2025

Distilling On-device Language Models for Robot Planning with Minimal Human Intervention

Zachary Ravichandran, Ignacio Hounie, Fernando Cladera +3

Large language models (LLMs) provide robots with powerful contextual reasoning abilities and a natural human interface. Yet, current LLM-enabled robots typically depend on cloud-ho…

cs.RO2025

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities

Zachary Ravichandran, Fernando Cladera, Jason Hughes +5

The integration of foundation models (FMs) into robotics has enabled robots to understand natural language and reason about the semantics in their environments. However, existing F…

cs.RO2025

Air-Ground Collaboration for Language-Specified Missions in Unknown Environments

Fernando Cladera, Zachary Ravichandran, Jason Hughes +6

As autonomous robotic systems become increasingly mature, users will want to specify missions at the level of intent rather than in low-level detail. Language is an expressive and…