EVPeriscope: Extended Perception across Aerial and Ground Vehicles with Event-based Propeller Tracking

EVPeriscope: Extended Perception across Aerial and Ground Vehicles with Event-based Propeller Tracking

|Authors: Dexter Ong, Vijay Kumar, Pratik Chaudhari

|Venue: arXiv preprint | Year: 2026

|arXiv: 2609.11920v1

Abstract

Reliable relative localization between aerial and ground robots is a key requirement for tightly coordinated heterogeneous teams. This can be difficult to do using conventional frame-based cameras and fiducial markers because they are sensitive to motion blur, lighting variations, and payload constraints. This paper presents EVPeriscope, an event-based perception system that enables detection, localization and control of a quadrotor using an upward-facing event camera on a ground robot by detecting the high-frequency visual signature of its propellers. This system allows the quadrotor to function as an extended perception system for the ground robot when onboard sensors exhibit degradation or occlusion. We demonstrate the capabilities of this marsupial ground-aerial system via experiments in challenging field conditions with wind speeds of up to 15 mph, in both daylight and at night. We show that the system supports localization and closed-loop navigation through dense foliage where the ground robot’s sensors are occluded. Our control system for the quadrotor operates at 200 Hz entirely with onboard sensing and computation. More details and experiment videos can be found on the project page: https://ongdexter.github.io/evperiscope.

Key Contributions

• Reliable relative localization between aerial and ground robots is a key requirement for tightly …
• This can be difficult to do using conventional frame-based cameras and fiducial markers because t…
• This paper presents EVPeriscope, an event-based perception system that enables detection, localiz…
• This system allows the quadrotor to function as an extended perception system for the ground robo…
• We demonstrate the capabilities of this marsupial ground-aerial system via experiments in challen…

Topics

• vision
• reinforcement-learning
• planning
• control

Code & Data

• GitHub repository: https://github.com/grasp-lyrl/evperiscope

BibTeX

@article{Ong2026_260911920v1,
  title     = {EVPeriscope: Extended Perception across Aerial and Ground Vehicles with Event-based Propeller Tracking},
  author    = {Dexter Ong and Vijay Kumar and Pratik Chaudhari},
  year      = {2026},
  eprint    = {2609.11920v1},
  archivePrefix = {arXiv},
  primaryClass  = {cs.RO},
  url       = {https://arxiv.org/abs/2609.11920v1}
}