105 citations · 227 across the 23 of their papers we have counts for
26 papers
DORA: Divergence-Oriented Data-Relay Algorithm for Partially Connected Robot Teams
Jonathan Diller, Fernando Cladera, Camillo Jose Taylor +1
Teams of unmanned aerial vehicles (UAVs) deployed for search and monitoring missions frequently operate as partially connected networks, forcing each robot to trade off exploring t…
Actively Resolving Contextual Uncertainty for Underspecified Tasks in Natural Language
Zachary Ravichandran, Jonathan Diller, Fernando Cladera +3
Foundation models provide robots with the ability to interpret natural language and reason about environmental context, yet most language-conditioned policies assume that goals are…
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…
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…
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…
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…
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…
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…
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…
EvMAPPER: High Altitude Orthomapping with Event Cameras
Fernando Cladera, Kenneth Chaney, M. Ani Hsieh +2
Traditionally, unmanned aerial vehicles (UAVs) rely on CMOS-based cameras to collect images about the world below. One of the most successful applications of UAVs is to generate or…
AgriNeRF: Neural Radiance Fields for Agriculture in Challenging Lighting Conditions
Samarth Chopra, Fernando Cladera, Varun Murali +1
Neural Radiance Fields (NeRFs) have shown significant promise in 3D scene reconstruction and novel view synthesis. In agricultural settings, NeRFs can serve as digital twins, provi…
Spatio-Temporal Metric-Semantic Mapping for Persistent Orchard Monitoring: Method and Dataset
Jiuzhou Lei, Ankit Prabhu, Xu Liu +5
Monitoring orchards at the individual tree or fruit level throughout the growth season is crucial for plant phenotyping and horticultural resource optimization, such as chemical us…
Air-Ground Collaboration with SPOMP: Semantic Panoramic Online Mapping and Planning
Ian D. Miller, Fernando Cladera, Trey Smith +2
Mapping and navigation have gone hand-in-hand since long before robots existed. Maps are a key form of communication, allowing someone who has never been somewhere to nonetheless n…
Challenges and Opportunities for Large-Scale Exploration with Air-Ground Teams using Semantics
Fernando Cladera, Ian D. Miller, Zachary Ravichandran +5
One common and desirable application of robots is exploring potentially hazardous and unstructured environments. Air-ground collaboration offers a synergistic approach to addressin…
Towards Understanding Underwater Weather Events in Rivers Using Autonomous Surface Vehicles
Alice K. Li, Yue Mao, Sandeep Manjanna +10
Climate change has increased the frequency and severity of extreme weather events such as hurricanes and winter storms. The complex interplay of floods with tides, runoff, and sedi…
TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards
Derek Cheng, Fernando Cladera Ojeda, Ankit Prabhu +6
Data collection for forestry, timber, and agriculture currently relies on manual techniques which are labor-intensive and time-consuming. We seek to demonstrate that robotics offer…
EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields
Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera +7
We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid an…
Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications
Fernando Cladera, Zachary Ravichandran, Ian D. Miller +3
Multi-robot collaboration in large-scale environments with limited-sized teams and without external infrastructure is challenging, since the software framework required to support…
EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks
Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco +6
Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to sta…
SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain
Yuezhan Tao, Yuwei Wu, Beiming Li +4
We address the problem of efficient 3-D exploration in indoor environments for micro aerial vehicles with limited sensing capabilities and payload/power constraints. We develop an…
Active Metric-Semantic Mapping by Multiple Aerial Robots
Xu Liu, Ankit Prabhu, Fernando Cladera +4
Traditional approaches for active mapping focus on building geometric maps. For most real-world applications, however, actionable information is related to semantically meaningful…
Stronger Together: Air-Ground Robotic Collaboration Using Semantics
Ian D. Miller, Fernando Cladera, Trey Smith +2
In this work, we present an end-to-end heterogeneous multi-robot system framework where ground robots are able to localize, plan, and navigate in a semantic map created in real tim…
Large-scale Autonomous Flight with Real-time Semantic SLAM under Dense Forest Canopy
Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda +8
Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilit…
Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors
Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler +1
This paper presents a Dynamic Vision Sensor (DVS) based system for reasoning about high speed motion. As a representative scenario, we consider the case of a robot at rest reacting…