mlsanityData to 14 Oct 2026

RLCAD: Reinforcement Learning Training Gym for Revolution Involved CAD Command Sequence Generation

arXiv 2503.18549 ↗First posted 24 Mar 2025cs.LG cs.AIcited by 7

On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation

Abstract (arXiv)

A CAD command sequence is a typical parametric design paradigm in 3D CAD systems where a model is constructed by overlaying 2D sketches with operations such as extrusion, revolution, and Boolean operations. Although there is growing academic interest in the automatic generation of command sequences, existing methods and datasets only support operations such as 2D sketching, extrusion,and Boolean operations. This limitation makes it challenging to represent more complex geometries. In this paper, we present a reinforcement learning (RL) training environment (gym) built on a CAD geometric engine. Given an input boundary representation (B-Rep) geometry, the policy network in the RL algorithm generates an action. This action, along with previously generated actions, is processed within the gym to produce the corresponding CAD geometry, which is then fed back into the policy network. The rewards, determined by the difference between the generated and target geometries within the gym, are used to update the RL network. Our method supports operations beyond sketches, Boolean, and extrusion, including revolution operations. With this training gym, we achieve state-of-the-art (SOTA) quality in generating command sequences from B-Rep geometries.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods. Builds on 27 of its 42 references that are in the map. First posted on arXiv 24 Mar 2025.

Builds on

27 of 42 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024ZSL-RPPO: Zero-Shot Learning for Quadrupedal Locomotion in Challenging Terrains using Recurrent Proximal Policy Optimization4 Mar

Other references · 26

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2017Proximal Policy Optimization Algorithmscited by 15,215
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  5. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  6. 2017Deep reinforcement learning from human preferencescited by 3,912
  7. 2014Conditional Generative Adversarial Netscited by 2,162
  8. 2015High-Dimensional Continuous Control Using Generalized Advantage Estimationcited by 2,026
  9. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  10. 2022PaLI: A Jointly-Scaled Multilingual Language-Image Modelcited by 766
  11. 2020Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classificationcited by 506
  12. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 470
14 more
  1. 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperationcited by 391
  2. 2018ABC: A Big CAD Model Dataset For Geometric Deep Learningcited by 341
  3. 2021DeepCAD: A Deep Generative Network for Computer-Aided Design Modelscited by 271
  4. 2019Stabilizing Transformers for Reinforcement Learningcited by 270
  5. 2024Reinforcement learningcited by 247
  6. 2022SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebookscited by 125
  7. 2024BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometrycited by 103
  8. 2023Hierarchical Neural Coding for Controllable CAD Model Generationcited by 86
  9. 2024CAD-MLLM: Unifying Multimodality-Conditioned CAD Generation With MLLMcited by 81
  10. 2024CAD-Recode: Reverse Engineering CAD Code from Point Cloudscited by 66
  11. 2024CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attentioncited by 64
  12. 2024Generating CAD Code with Vision-Language Models for 3D Designscited by 62
  13. 2023SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operationscited by 46
  14. 2024Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Promptscited by 23

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 5.

7 papers.

  1. 2025cadrille: Multi-modal CAD Reconstruction with Reinforcement Learningcited by 16
  2. 2026Pointer-CAD: Unifying B-Rep and Command Sequences via Pointer-based Edges & Faces Selectioncited by 11
  3. 2025CReFT-CAD: Boosting Orthographic Projection Reasoning for CAD via Reinforcement Fine-Tuningcited by 8
  4. 2026FllumaOne: A Code-Native Multimodal CAD Dataset with Executable Programs and Kernel-Validated Feature Historiescited by 1
  5. 2026Pointer-CAD v2: Plan-Then-Construct CAD Generation with Dimension-Aware Parametric Precisioncited by 1
  6. 2026Memory-Augmented Reinforcement Learning Agent for CAD Generationcited by 0
  7. 2026Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025From Intent to Execution: Multimodal Chain-of-Thought Reinforcement Learning for Precise CAD Code Generation
  2. 2025ReCAD: Reinforcement Learning Enhanced Parametric CAD Model Generation with Vision-Language Models
  3. 2020Modeling 3D Shapes by Reinforcement Learning
  4. 2026RL-Lock: Reinforcement Learning for Generating Interlocking Assemblies
  5. 2025CME-CAD: Heterogeneous Collaborative Multi-Expert Reinforcement Learning for CAD Code Generation
  6. 2026Draw it like Euclid: Teaching transformer models to generate CAD profiles using ruler and compass construction steps
  7. 2025GACO-CAD: Geometry-Augmented and Conciseness-Optimized CAD Model Generation from Single Image
  8. 2026Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration