ReviewCyborg and bionic systems (Washington, D.C.)2026
Energy as a Common Currency for Understanding Embodied Evolution.
Review in Cyborg and bionic systems (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
4 authors.
Funding
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Abstract
Unlike living organisms, which persist by balancing energy intake, expenditure, and maintenance, embodied robots are often evaluated primarily by task performance, even when morphology, control, and environment jointly determine what can be sustained over time. This task-centered evaluation supports engineering benchmarks but can obscure embodied costs, limit comparability across heterogeneous embodiments, and weaken biological interpretation when robots and simulations are used as model systems. This Review synthesizes biological energetics and biomechanics to argue that open-system energy accounting provides a common currency for embodied evolution. Under this framing, adaptive success (fitness) is interpreted as persistence under energetic constraint, enabling commensurate comparison of regulation, structural adaptation, and structural plasticity across environments with different energetic structure. A minimal accounting framework and an illustrative experimental paradigm are presented to show how shared accounting yields interpretable differences between adaptive responses beyond task semantics. This paper concludes by discussing implications for interpreting morphological and control complexity and by outlining open challenges and future directions for energy-aware embodied evolution using robots as controlled platforms for biology-facing hypothesis testing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.