REVIEW 1 cited by
A Prompt-driven Task Planning Method for Multi-drones based on Large Language Model
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
With the rapid development of drone technology, the application of multi-drones is becoming increasingly widespread in various fields. However, the task planning technology for multi-drones still faces challenges such as the complexity of remote operation and the convenience of human-machine interaction. To address these issues, this paper proposes a prompt-driven task planning method for multi-drones based on large language models. By introducing the Prompt technique, appropriate prompt information is provided for the multi-drone system.
Forward citations
Cited by 1 Pith paper
-
RT-SHCUA: Real-Time Self-Hosted Computer-Use Agent for UAV Control
An architecture that mediates LLM computer-use agents for UAV control by compiling agent decisions into validated, time-bounded, evidence-logged skill invocations, with a prototype on OpenClaw/PX4/OP-TEE.
Discussion (0). Continue with ORCID to comment.