activity
20192025
most citedEV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks

26 citations · 49 across the 18 of their papers we have counts for

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17 papers · 1 filter

cs.RO2025

A Multi-Robot Platform for Robotic Triage Combining Onboard Sensing and Foundation Models

Jason Hughes, Marcel Hussing, Edward Zhang +24

This report presents a heterogeneous robotic system designed for remote primary triage in mass-casualty incidents (MCIs). The system employs a coordinated air-ground team of unmann…

cs.RO2025

HALO: High-Altitude Language-Conditioned Monocular Aerial Exploration and Navigation

Yuezhan Tao, Dexter Ong, Fernando Cladera +4

We demonstrate real-time high-altitude aerial metric-semantic mapping and exploration using a monocular camera paired with a global positioning system (GPS) and an inertial measure…

cs.RO2025

Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence

Zachary Ravichandran, Fernando Cladera, Ankit Prabhu +6

While heterogeneous teams have typically been designed for well-specified missions with known semantics, generative intelligence, i.e., large language models (LLMs) and vision lang…

cs.RO2025

Adaptive Per-Tree Canopy Volume Estimation Using Mobile LiDAR in Structured and Unstructured Orchards

Ali Abedi, Fernando Cladera, Mohsen Farajijalal +1

We present a real-time system for per-tree canopy volume estimation using mobile LiDAR data collected during routine robotic navigation. Unlike prior approaches that rely on static…

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…