Knot So Simple: A Minimalistic Environment for Spatial Reasoning

2025/05/23 by Zizhao Chen, Yoav Artzi, Chen, Zizhao +1 · 1 voice
Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Robotics (cs.RO) #cs.AI #cs.CV #cs.LG #cs.RO

paper · pdf · doi:10.48550/arxiv.2505.18028

arxiv published 2025/05/23 · arxiv updated 2026/01/18

Abstract

We propose KnotGym, an interactive environment for complex, spatial reasoning and manipulation. KnotGym includes goal-oriented rope manipulation tasks with varying levels of complexity, all requiring acting from pure image observations. Tasks are defined along a clear and quantifiable axis of complexity based on the number of knot crossings, creating a natural generalization test. KnotGym has a simple observation space, allowing for scalable development, yet it highlights core challenges in integrating acute perception, spatial reasoning, and grounded manipulation. We evaluate methods of different classes, including model-based RL, model-predictive control, and chain-of-thought reasoning, and illustrate the challenges KnotGym presents. KnotGym is available at https://github.com/lil-lab/knotgym.

Citations

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Discussions

• ✨ Why it matters KnotGym gives us a lightweight yet expressive testbed for multi-modal long-horizon reasoning and planning. 📄 Paper: arxiv.org/abs/2505.18028 🔗 Website: lil-lab.github.io/knotgym Joi [bsky, 1 points, 1 comments]

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