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SelSta - A Biologically Inspired Approach for Self-Stabilizing Humanoid Robot Walking

Abstract : In this paper we elaborate a study on self-stabilizing humanoid robot that achieves run-time self-stabilization and energy optimized walking gait pattern parameters on different kinds of flat surfaces. The algorithmic approach named SelSta uses biologically inspired notions that introduce robustness into the self-stabilizing functionality of the humanoid robot. The approach has been practically tested on our S2-HuRo humanoid robot and the results from the tests demonstrate that it can be successfully used on humanoid robots to achieve autonomic optimized stabilization of their walking on different kinds of flat surfaces.
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Bojan Jakimovski, Michael Kotke, Martin Hörenz, Erik Maehle. SelSta - A Biologically Inspired Approach for Self-Stabilizing Humanoid Robot Walking. 7th IFIP TC 10 Working Conference on Distributed, Parallel and Biologically Inspired Systems (DIPES) / 3rd IFIP TC 10 International Conference on Biologically-Inspired Collaborative Computing (BICC) / Held as Part of World Computer Congress (WCC) , Sep 2010, Brisbane, Australia. pp.302-313, ⟨10.1007/978-3-642-15234-4_29⟩. ⟨hal-01054490⟩

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