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Award ID contains: 2221576

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  1. We propose a mechanism for low Reynolds num- ber walking (e.g., legged microscale robots). Whereas loco- motion for legged robots has traditionally been classified as dynamic (where inertia plays a role) or static (where the system is always statically stable), we introduce a new locomotion modality we call buoyancy enabled non-inertial dynamic walking in which inertia plays no role, yet the robot is not statically stable. Instead, falling and viscous drag play critical roles. This model assumes squeeze flow forces from fluid interactions combined with a well timed gait as the mechanism by which forward motion can be achieved from a reciprocating legged robot. Using two physical demonstrations of robots with Reynold’s number ranging from 0.0001 to 0.02 (a microscale robot in water and a centimeter scale robot in glycerol) we find the model qualitatively describes the motion. This model can help understand microscale locomotion and design new microscale walking robots including controlling forward and backwards motion and potentially steering these robots. 
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