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- "With a computational eBiobot model in hand, we then tackled the problem of optimizing the scaffold to maximize its forward walking speed. To do this, we coupled Elastica with the Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES), a method specialized for dealing with nonlinear, nonconvex continuous optimization problems. Coupled with Elastica, CMA-ES was demonstrated as an efficient design tool for a range of engineering and biohybrid applications."
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Mirzae, Y., Dubrovski, O., Kenneth, O., Morozov, K. I., & Leshansky, A. M. (2018). Geometric constraints and optimization in externally driven propulsion. Science robotics, 3(17), eaas8713. [ pdf ]
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Slavkov, I., Carrillo-Zapata, D., Carranza, N., Diego, X., Jansson, F., Kaandorp, J., Hauert, S., & Sharpe, J. (2018). Morphogenesis in robot swarms. Science robotics, 3(25), eaau9178. [ pdf ]
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Yan, X., Zhou, Q., Vincent, M., Deng, Y., Yu, J., Xu, J., Xu, T., Tang, T., Bian, L., Wang, Y. J., Kostarelos, K., & Zhang, L. (2017). Multifunctional biohybrid magnetite microrobots for imaging-guided therapy. Science robotics, 2(12), eaaq1155. [ pdf ]
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