1 Biological inspiration and single artificial neurons

2016 ◽  
Vol 113 (8) ◽  
pp. E950-E957 ◽  
Author(s):  
Kaushik Jayaram ◽  
Robert J. Full

Jointed exoskeletons permit rapid appendage-driven locomotion but retain the soft-bodied, shape-changing ability to explore confined environments. We challenged cockroaches with horizontal crevices smaller than a quarter of their standing body height. Cockroaches rapidly traversed crevices in 300–800 ms by compressing their body 40–60%. High-speed videography revealed crevice negotiation to be a complex, discontinuous maneuver. After traversing horizontal crevices to enter a vertically confined space, cockroaches crawled at velocities approaching 60 cm⋅s−1, despite body compression and postural changes. Running velocity, stride length, and stride period only decreased at the smallest crevice height (4 mm), whereas slipping and the probability of zigzag paths increased. To explain confined-space running performance limits, we altered ceiling and ground friction. Increased ceiling friction decreased velocity by decreasing stride length and increasing slipping. Increased ground friction resulted in velocity and stride length attaining a maximum at intermediate friction levels. These data support a model of an unexplored mode of locomotion—“body-friction legged crawling” with body drag, friction-dominated leg thrust, but no media flow as in air, water, or sand. To define the limits of body compression in confined spaces, we conducted dynamic compressive cycle tests on living animals. Exoskeletal strength allowed cockroaches to withstand forces 300 times body weight when traversing the smallest crevices and up to nearly 900 times body weight without injury. Cockroach exoskeletons provided biological inspiration for the manufacture of an origami-style, soft, legged robot that can locomote rapidly in both open and confined spaces.


Designs ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 47 ◽  
Author(s):  
Jacquelyn Nagel ◽  
Linda Schmidt ◽  
Werner Born

Biological systems have evolved over billions of years and cope with changing conditions through the adaptation of morphology, physiology, or behavior. Learning from these adaptations can inspire engineering innovation. Several bio-inspired design tools and methods prescribe the use of analogies, but lack details for the identification and application of promising analogies. Further, inexperienced designers tend to have a more difficult time recognizing or creating analogies from biological systems. This paper reviews biomimicry literature to establish analogy categories as a tool for knowledge transfer between biology and engineering to aid bio-inspired design that addresses the common issues. Two studies were performed with the analogy categories. A study of commercialized products verifies the set of categories, while a controlled design study demonstrates the utility of the categories. The results of both studies offer valuable information and insights into the complexity of analogical reasoning and transfer, as well as what leads to biological inspiration versus imitation. The influence on bio-inspired design pedagogy is also discussed. The breadth of the analogy categories is sufficient to capture the knowledge transferred from biology to engineering for bio-inspired design. The analogy categories are a design method independent tool and are applicable for professional product design, research, and teaching purposes.


2019 ◽  
Vol 65 (3) ◽  
pp. 1-17
Author(s):  
Boualem REMINI ◽  
Yacine HAFIED ◽  
Nadir MAROUF ◽  
Mohamed BOUZIANE ◽  
Shiynkaruk LUBOMIR

2021 ◽  
Author(s):  
◽  
Carlton Downey

<p>Linear Genetic Programming (LGP) is a powerful problem-solving technique, but one with several significant weaknesses. LGP programs consist of a linear sequence of instructions, where each instruction may reuse previously computed results. This structure makes LGP programs compact and powerful, however it also introduces the problem of instruction dependencies. The notion of instruction dependencies expresses the concept that certain instructions rely on other instructions. Instruction dependencies are often disrupted during crossover or mutation when one or more instructions undergo modification. This disruption can cause disproportionately large changes in program output resulting in non-viable offspring and poor algorithm performance. Motivated by biological inspiration and the issue of code disruption, we develop a new form of LGP called Parallel LGP (PLGP). PLGP programs consist of n lists of instructions. These lists are executed in parallel, and the resulting vectors are summed to produce the overall program output. PLGP limits the disruptive effects of crossover and mutation, which allows PLGP to significantly outperform regular LGP. We examine the PLGP architecture and determine that large PLGP programs can be slow to converge. To improve the convergence time of large PLGP programs we develop a new form of PLGP called Cooperative Coevolution PLGP (CC PLGP). CC PLGP adapts the concept of cooperative coevolution to the PLGP architecture. CC PLGP optimizes all program components in parallel, allowing CC PLGP to converge significantly faster than conventional PLGP. We examine the CC PLGP architecture and determine that performance</p>


Author(s):  
Eduardo Sanchez ◽  
Daniel Mange ◽  
Moshe Sipper ◽  
Marco Tomassini ◽  
Andres Perez-Uribe ◽  
...  

2021 ◽  
Author(s):  
Balazs Bodo ◽  
Luis Lopes ◽  
Claudio Rossi ◽  
Giorgia Stasi ◽  
Christian Burlet ◽  
...  

&lt;p&gt;ROBOMINERS is developing an innovative approach for the exploitation of currently non-feasible mineral deposits. The approach entails the use of a robot-miner - a bio-inspired reconfigurable robot with a modular nature - in a new mining setting where the activities are nearly invisible and where mining presents less socio-environmental constraints, thus contributing to a more safe and sustainable supply of mineral raw materials.&lt;/p&gt;&lt;p&gt;The main aim is to design and develop a robotic prototype that is able to perform mining related tasks in settings including both abandoned, currently flooded mines not accessible anymore for conventional mining techniques; or places that have formerly been explored, but whose exploitation was considered as uneconomic due to the small-size of deposits, or their difficulty to access.&lt;/p&gt;&lt;p&gt;ROBOMINERS&amp;#8217; innovative approach combines the creation of a new mining ecosystem with novel ideas from other sectors, particularly robotics. At this point, work has been done to understand the best methods for the robotminer&amp;#8217;s development in 1) biological inspiration, 2) perception and localisation tools, 3) behaviour, navigation and control, 4) actuation methods, 5) modularity, 6)autonomy and resilience, and 7) the selective mining ability. All these aspects combined aim to provide the robotminer XXI Century tools for mineral exploration and exploitation of (currently) unfeasible deposits.&lt;/p&gt;&lt;p&gt;At the same time, for the vision of a new vision of a mining ecosystem, work is involving studies on 1) developing computer models and simulations, 2) data management and visualisation, 3) rock-mechanical and geotechnical characterisation studies, 4) analysing ground/rock support methods, bulk transportation methods, backfilling types and methods, and 5) sketching relevant upstream and downstream mining industry analogues for the ROBOMINERS concept.&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;After design and development, based on the previously mentioned studies, the robot-miner is set to be tested at targeted areas representatives which include abandoned and/or operating mines, small but high-grade mineral deposits, unexplored/explored non-economic occurrences and ultra depth, not&amp;#160; easily accessible environments. Possible candidates for testing purposes include mines in the regions of Cornwall (UK), mines in the Kupferschiefer Formation (e.g. Poland) or coal mines in Belgium.&lt;/p&gt;&lt;p&gt;When compared to usual mining methods the ROBOMINERS approach shows: 1) no presence of people in the mine, 2) less mining waste produced, 3) less mining infrastructure, 4) less investment, 5) possibility to explore currently uneconomic resources and 6) new underground small-sized mines, practically &amp;#8220;invisible&amp;#8221;. Altogether, ROBOMINERS can contribute to solve some of the main issues that make mining&amp;#8217;s social license to operate so difficult to get in Europe: land-use, environmental limitations, and socio-economic aspects.&lt;/p&gt;


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