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

Published: 18 Jun 2024, Last Modified: 05 Sept 2024MFM-EAI@ICML2024 PosterEveryoneRevisionsBibTeXCC BY 4.0
Keywords: MiniGolf, VLM, Real-World Robotics
TL;DR: We introduce RoboGolf to master real-world minigolf game, a VLM based framework that combines dual-camera perception and closed-loop control, augmented by a reflective equilibrium loop.
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://robogolfvlm.github.io/.
Submission Number: 7
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