Pith. sign in

REVIEW 1 cited by

Cooperative Infrastructure Perception

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

arxiv 2207.08930 v2 pith:W6ITKELG submitted 2022-07-18 cs.RO

classification cs.RO
keywords perceptioninfrastructurecooperativeoutputsusedapproachsensorswhen
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Recent works have considered two qualitatively different approaches to overcome line-of-sight limitations of 3D sensors used for perception: cooperative perception and infrastructure-augmented perception. In this paper, motivated by increasing deployments of infrastructure LiDARs, we explore a third approach, cooperative infrastructure perception. This approach generates perception outputs by fusing outputs of multiple infrastructure sensors, but, to be useful, must do so quickly and accurately. We describe the design, implementation and evaluation of Cooperative Infrastructure Perception (CIP), which uses a combination of novel algorithms and systems optimizations. It produces perception outputs within 100 ms using modest computing resources and with accuracy comparable to the state-of-the-art. CIP, when used to augment vehicle perception, can improve safety. When used in conjunction with offloaded planning, CIP can increase traffic throughput at intersections.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Warping the Edge: Where Instant Mobility in 5G Meets Stateful Applications

    cs.NI 2024-12 conditional novelty 6.0 of 10

    EdgeWarp reduces edge application downtime during 5G mobility by predicting the target base station in advance and synchronizing application state in two steps, with measured reductions up to 15.4x on a testbed.

Pith tools