FlexiFly: Interfacing the Physical World with Foundation Models Empowered by Reconfigurable Drone Systems
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Abstract (arXiv)
Foundation models (FM) have shown immense human-like capabilities for generating digital media. However, foundation models that can freely sense, interact, and actuate the physical domain is far from being realized. This is due to 1) requiring dense deployments of sensors to fully cover and analyze large spaces, while 2) events often being localized to small areas, making it difficult for FMs to pinpoint relevant areas of interest relevant to the current task. We propose FlexiFly, a platform that enables FMs to ``zoom in'' and analyze relevant areas with higher granularity to better understand the physical environment and carry out tasks. FlexiFly accomplishes by introducing 1) a novel image segmentation technique that aids in identifying relevant locations and 2) a modular and reconfigurable sensing and actuation drone platform that FMs can actuate to ``zoom in'' with relevant sensors and actuators. We demonstrate through real smart home deployments that FlexiFly enables FMs and LLMs to complete diverse tasks up to 85% more successfully. FlexiFly is critical step towards FMs and LLMs that can naturally interface with the physical world.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 8 of its 57 references that are in the map. First posted on arXiv 19 Mar 2024.
Builds on
8 of 57 references.
References · 8
- 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
- 2023ChatGPT for Robotics: Design Principles and Model Abilitiescited by 296
- 2023Text2Motion: From Natural Language Instructions to Feasible Planscited by 223
- 2023Penetrative AI: Making LLMs Comprehend the Physical Worldcited by 64
- 2023Transferring Foundation Models for Generalizable Robotic Manipulationcited by 18
- 2024Self-Adapting Large Visual-Language Models to Edge Devices across Visual Modalitiescited by 7
- 2023MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systemscited by 4
- 2022Reconfigurable Drone System for Transportation of Parcels With Variable Mass and Sizecited by 1
Built on by
Citing papers per year: 2025: 2; 2026: 1.
3 papers.
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- 2026RadioMaster: Multi-Agent System for Autonomous Radio Signal Generation1 Jun 2026
- 2025UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs8 Jun 2025
- 2025TDBench: A Benchmark for Top-Down Image Understanding with Reliability Analysis of Vision-Language Models1 Apr 2025