Pith. sign in

REVIEW

Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations

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 2102.08761 v1 pith:X4QWP5KT submitted 2021-02-14 cs.RO cs.NI

classification cs.ROcs.NI
keywords visualizationaerialautonomousdeeplearningmobilityreinforcementsimulations
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is used and additional buildings are introduced for urban environment. On top of the implementation, DRL algorithms are used and we confirm it works well in terms of trajectory and 3D visualization.

Discussion (0). Continue with ORCID to comment.

Pith tools