REVIEW 2 cited by
EvMAPPER: High Altitude Orthomapping with Event Cameras
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
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 orthomosaics or orthomaps, in which a series of images are integrated together to develop a larger map. However, the use of CMOS-based cameras with global or rolling shutters mean that orthomaps are vulnerable to challenging light conditions, motion blur, and high-speed motion of independently moving objects under the camera. Event cameras are less sensitive to these issues, as their pixels are able to trigger asynchronously on brightness changes. This work introduces the first orthomosaic approach using event cameras. In contrast to existing methods relying only on CMOS cameras, our approach enables map generation even in challenging light conditions, including direct sunlight and after sunset.
Forward citations
Cited by 2 Pith papers
-
Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities
A closed-loop LLM planning framework was field-tested on ground and aerial robots for kilometer-scale missions, including an onboard UAV planner built from a distilled small language model.
-
Air-Ground Collaboration for Language-Specified Missions in Unknown Environments
A drone and a ground robot coordinated by an LLM planner over an intermittently shared semantic map complete seven natural-language missions in unknown outdoor environments.
Discussion (0). Continue with ORCID to comment.