4 citations · 7 across the 13 of their papers we have counts for
14 papers
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…
EvoPlan: Evolutionary Neuro-Symbolic Robot Planning with Spatio-Temporal Guarantees
Bhavya Sai Nukapotula, Samin Moosavi, Haoze Wang +4
LLM-based robot planners are fluent but cannot guarantee that their plans are executable or safe. Classical PDDL planners can guarantee these properties, but only after the problem…
REBAR: Reference Ethical Benchmark for Autonomy Readiness
Jonathan Diller, David Barnes, Rebekah Bogdanoff +14
As autonomous systems grow more advanced, objective metrics to evaluate their ethical and legal compliance are critical for informing end users of their limitations and ensuring ac…
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…
Real-Time Glass Detection and Reprojection using Sensor Fusion Onboard Aerial Robots
Malakhi Hopkins, Varun Murali, Vijay Kumar +1
Autonomous aerial robots are increasingly being deployed in real-world scenarios, where transparent obstacles present significant challenges to reliable navigation and mapping. The…
Gaussian Splatting as a Unified Representation for Autonomy in Unstructured Environments
Dexter Ong, Yuezhan Tao, Varun Murali +3
In this work, we argue that Gaussian splatting is a suitable unified representation for autonomous robot navigation in large-scale unstructured outdoor environments. Such environme…
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…
Robotic Monitoring of Colorimetric Leaf Sensors for Precision Agriculture
Malakhi Hopkins, Alice Kate Li, Shobhita Kramadhati +8
Common remote sensing modalities (RGB, multispectral, hyperspectral imaging or LiDAR) are often used to indirectly measure crop health and do not directly capture plant stress indi…
ATLAS Navigator: Active Task-driven LAnguage-embedded Gaussian Splatting
Dexter Ong, Yuezhan Tao, Varun Murali +3
We address the challenge of task-oriented navigation in unstructured and unknown environments, where robots must incrementally build and reason on informative metric-semantic maps…
SPINE: Online Semantic Planning for Missions with Incomplete Natural Language Specifications in Unstructured Environments
Zachary Ravichandran, Varun Murali, Mariliza Tzes +2
As robots become increasingly capable, users will want to describe high-level missions and have robots infer the relevant details. Because pre-built maps are difficult to obtain in…
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…
RT-GuIDE: Real-Time Gaussian Splatting for Information-Driven Exploration
Yuezhan Tao, Dexter Ong, Varun Murali +3
We propose a framework for active mapping and exploration that leverages Gaussian splatting for constructing dense maps. Further, we develop a GPU-accelerated motion planning algor…
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…