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Autonomous maze navigation is appealing yet challenging in soft robotics for exploring priori unknown unstructured environments, as it often requires human-like brain that integrates onboard power, sensors, and control for computational intelligence. Here, we report harnessing both geometric and materials intelligence in liquid crystal elastomer–based self-rolling robots for autonomous escaping from complex multichannel mazes without the need for human-like brain. The soft robot powered by environmental thermal energy has asymmetric geometry with hybrid twisted and helical shapes on two ends. Such geometric asymmetry enables built-in active and sustained self-turning capabilities, unlike its symmetric counterparts in either twisted or helical shapes that only demonstrate transient self-turning through untwisting. Combining self-snapping for motion reflection, it shows unique curved zigzag paths to avoid entrapment in its counterparts, which allows for successful self-escaping from various challenging mazes, including mazes on granular terrains, mazes with narrow gaps, and even mazes with in situ changing layouts.
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Transport in mazes; simple geometric representations to guide the design of engineered systems
Although engineers can control the internal geometry of materials down to the micro-scale, it is unclear what configuration is ideal for a given transport process. We explore the use of mazes as abstract representations of two-phase systems. Mazes can be easily generated using many different algorithms and then represented as graphs for analysis. The three, dimensionless graph parameters of effective tortuous resistance, average tortuosity, and minimum-cut-size were derived and then correlated to the maze’s effective transport property (e.g., permeability), average residence time, and robustness, respectively. It was shown that by tuning the settings of the maze algorithm, one can obtain desired maze performance. Finally, a composite maze was constructed and shown to mimic the geometry and permeability of a real commercial membrane. In principle, a surrogate maze geometry can be optimized/tuned for a given transport process and then used to guide the rational design of the engineered system it represents.
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- Award ID(s):
- 1603318
- PAR ID:
- 10337418
- Date Published:
- Journal Name:
- Chemical engineering science
- Volume:
- 250
- ISSN:
- 0009-2509
- Page Range / eLocation ID:
- 117416
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.ces.2021.117416
