collaborators

6 papers

cs.RO2025

Safe MPC Alignment with Human Directional Feedback

Zhixian Xie, Wenlong Zhang, Yi Ren +3

In safety-critical robot planning or control, manually specifying safety constraints or learning them from demonstrations can be challenging. In this article, we propose a certifia…

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…

cs.RO2025

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…