mlsanityData to 7 Oct 2026

BodyGen: Advancing Towards Efficient Embodiment Co-Design

arXiv 2503.00533 ↗First posted 1 Mar 2025cs.RO cs.LG cs.SYcited by 9

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Abstract (arXiv)

Embodiment co-design aims to optimize a robot's morphology and control policy simultaneously. While prior work has demonstrated its potential for generating environment-adaptive robots, this field still faces persistent challenges in optimization efficiency due to the (i) combinatorial nature of morphological search spaces and (ii) intricate dependencies between morphology and control. We prove that the ineffective morphology representation and unbalanced reward signals between the design and control stages are key obstacles to efficiency. To advance towards efficient embodiment co-design, we propose BodyGen, which utilizes (1) topology-aware self-attention for both design and control, enabling efficient morphology representation with lightweight model sizes; (2) a temporal credit assignment mechanism that ensures balanced reward signals for optimization. With our findings, Body achieves an average 60.03% performance improvement against state-of-the-art baselines. We provide codes and more results on the website: https://genesisorigin.github.io.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 32 of its 46 references that are in the map. First posted on arXiv 1 Mar 2025.

Builds on

32 of 46 references.

References · 32

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  6. 2017Proximal Policy Optimization Algorithmscited by 14,441
  7. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  8. 2015Continuous control with deep reinforcement learningcited by 3,279
  9. 2015Trust Region Policy Optimizationcited by 2,503
  10. 2015High-Dimensional Continuous Control Using Generalized Advantage Estimationcited by 1,916
  11. 2018Self-Attention with Relative Position Representationscited by 1,112
  12. 2020On Layer Normalization in the Transformer Architecturecited by 906
20 more
  1. 2021Conflict-Averse Gradient Descent for Multi-task Learningcited by 441
  2. 2021Embodied Intelligence via Learning and Evolutioncited by 154
  3. 2020One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Controlcited by 114
  4. 2018Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Controlcited by 104
  5. 2022MetaMorph: Learning Universal Controllers with Transformerscited by 78
  6. 2019Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularitycited by 68
  7. 2020My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Controlcited by 68
  8. 2018Reinforcement Learning for Improving Agent Designcited by 55
  9. 2019Encoding word order in complex embeddingscited by 53
  10. 2022Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robotscited by 44
  11. 2019Neural Graph Evolution: Towards Efficient Automatic Robot Designcited by 34
  12. 2021Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Designcited by 34
  13. 2022AnyMorph: Learning Transferable Polices By Inferring Agent Morphologycited by 25
  14. 2023Universal Morphology Control via Contextual Modulationcited by 21
  15. 2021Learning Modular Robot Control Policiescited by 18
  16. 2021Multi-Objective Graph Heuristic Search for Terrestrial Robot Designcited by 18
  17. 2022Low-Rank Modular Reinforcement Learning via Muscle Synergycited by 16
  18. 2023Symmetry-Aware Robot Design with Structured Subgroupscited by 13
  19. 2020Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objectscited by 11
  20. 2024DittoGym: Learning to Control Soft Shape-Shifting Robotscited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 5.

9 papers.

  1. 2025RoboMoRe: LLM-based Robot Co-design via Joint Optimization of Morphology and Rewardcited by 4
  2. 2025House of Dextra: Cross-embodied Co-design for Dexterous Handscited by 4
  3. 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challengescited by 4
  4. 2026EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaborationcited by 2
  5. 2026Efficient Morphology-Control Co-Design via Stackelberg Proximal Policy Optimizationcited by 2
  6. 2025Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recoverycited by 1
  7. 2026Shape Your Body: Value Gradients for Multi-Embodiment Robot Designcited by 1
  8. 2026BRIDGE: An Open-Source Humanoid Platform via Morphology-Control Co-Design for Physical AIcited by 0
  9. 2026Bridging Body and Brain: Gene-Driven Morphology--Control Co-Designcited by 0