Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recovery

• URL: http://arxiv.org/abs/2510.22336v2
• Date: Wed, 05 Nov 2025 15:01:29 GMT
• Title: Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recovery
• Authors: Bo Yue, Sheng Xu, Kui Jia, Guiliang Liu,
• Abstract summary: We propose RoboCraft, a scalable humanoid co-design framework for fall recovery.<n>A shared policy pretrained across multiple designs is progressively finetuned on high-performing morphologies.<n>Experiments show that RoboCraft achieves an average performance gain of 44.55% on seven public humanoid robots.
• Score: 55.951691393378354
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Humanoid robots represent a central frontier in embodied intelligence, as their anthropomorphic form enables natural deployment in humans' workspace. Brain-body co-design for humanoids presents a promising approach to realizing this potential by jointly optimizing control policies and physical morphology. Within this context, fall recovery emerges as a critical capability. It not only enhances safety and resilience but also integrates naturally with locomotion systems, thereby advancing the autonomy of humanoids. In this paper, we propose RoboCraft, a scalable humanoid co-design framework for fall recovery that iteratively improves performance through the coupled updates of control policy and morphology. A shared policy pretrained across multiple designs is progressively finetuned on high-performing morphologies, enabling efficient adaptation without retraining from scratch. Concurrently, morphology search is guided by human-inspired priors and optimization algorithms, supported by a priority buffer that balances reevaluation of promising candidates with the exploration of novel designs. Experiments show that RoboCraft achieves an average performance gain of 44.55% on seven public humanoid robots, with morphology optimization drives at least 40% of improvements in co-designing four humanoid robots, underscoring the critical role of humanoid co-design.

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