ملخص
In the past few decades, bioinspired hexapod walking robots have attracted increasing attention, mainly due to their potential to efficiently traverse rough terrains. Recently, neuromorphic (brain-inspired) robotic control has been shown to outperform conventional control paradigms in stochastic environments. In this work, we propose a neuromorphic adaptive body leveling algorithm for a hexapod walking robot during transversal over multi-leveled terrain. We demonstrate adaptive control with distributed accelerator-driven neuro-integrators with only a few thousand spiking neurons. We further propose a framework for the integration of MuJoCo, a modeling environment, and Nengo, a spiking neural networks compiler, for efficient evaluation of neuromorphic control over high degrees of freedom robotic systems in realistic physics-driven scenarios.
اللغة الأصلية | الإنجليزيّة |
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عنوان منشور المضيف | BioCAS 2021 - IEEE Biomedical Circuits and Systems Conference, Proceedings |
ناشر | Institute of Electrical and Electronics Engineers Inc. |
رقم المعيار الدولي للكتب (الإلكتروني) | 9781728172040 |
المعرِّفات الرقمية للأشياء | |
حالة النشر | نُشِر - 2021 |
الحدث | 2021 IEEE Biomedical Circuits and Systems Conference, BioCAS 2021 - Virtual, Online, ألمانيا المدة: ٦ أكتوبر ٢٠٢١ → ٩ أكتوبر ٢٠٢١ |
سلسلة المنشورات
الاسم | BioCAS 2021 - IEEE Biomedical Circuits and Systems Conference, Proceedings |
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!!Conference
!!Conference | 2021 IEEE Biomedical Circuits and Systems Conference, BioCAS 2021 |
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الدولة/الإقليم | ألمانيا |
المدينة | Virtual, Online |
المدة | ٦/١٠/٢١ → ٩/١٠/٢١ |
ملاحظة ببليوغرافية
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