Pith. sign in

REVIEW

RoboGolf: Mastering Real-World Minigolf with a Reflective Multi-Modality Vision-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

arxiv 2406.10157 v5 pith:YM2QQPYM submitted 2024-06-14 cs.RO cs.AI

classification cs.ROcs.AI
keywords reflectiverobogolfexemplaryframeworkminigolfreal-worldactionadditionally
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Minigolf is an exemplary real-world game for examining embodied intelligence, requiring challenging spatial and kinodynamic understanding to putt the ball. Additionally, reflective reasoning is required if the feasibility of a challenge is not ensured. We introduce RoboGolf, a VLM-based framework that combines dual-camera perception with closed-loop action refinement, augmented by a reflective equilibrium loop. The core of both loops is powered by finetuned VLMs. We analyze the capabilities of the framework in an offline inference setting, relying on an extensive set of recorded trajectories. Exemplary demonstrations of the analyzed problem domain are available at https://jity16.github.io/RoboGolf/

Discussion (0). Continue with ORCID to comment.

Pith tools