Generative Evolutionary Design of Voxel-Based Soft Robots with Provable Optimality

arXiv:2609.29491 · cs.RO, cs.AI · Submitted 2026-08-24 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-08-24

Updated: 2026-08-24

Code: https://github.com/xh621/MISCO

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Generative Model — 14× in this paper · explained in 2 episodes
• Generative Models — 10× in this paper · explained in 2 episodes
• Average Convergence Rate — 8× in this paper
• Ablation — 7× in this paper · explained in 1 episode
• Neural Cellular Automata — 7× in this paper
• Perplexity — 6× in this paper · explained in 3 episodes
• Bayesian Optimization — 5× in this paper · explained in 3 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Genetic Algorithm — 5× in this paper
• Ablation study — 4× in this paper · explained in 1 episode
• Objective Function — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Theoretical Guarantees — 4× in this paper · explained in 2 episodes
• Adaptability — 3× in this paper · explained in 1 episode
• Sample Efficiency — 3× in this paper · explained in 4 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Bayesian Optimization (BO) — 2× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Compositional Pattern Producing Network — 2× in this paper
• Fidelity — 2× in this paper · explained in 2 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Acquisition Function — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Hamming Distance — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Morphological Diversity Score — 1× in this paper
• Morphological Hamming Distance — 1× in this paper
• Morphological Variance — 1× in this paper
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Variational Autoencoder (VAE) — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design
• Auto-Encoding Variational Bayes
• Evolution and learning in differentiable robots
• Proximal Policy Optimization Algorithms
• HeteroMorpheus: Universal Control Based on Morphological Heterogeneity Modeling

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