Publications by authors named "A C Mondini"

There are many examples in nature in which the ability to detect is combined with decision-making, such as the basic survival instinct of plants and animals to search for food. We can technically translate this innate function via the use of robotics with integrated sensors and artificial intelligence. However, the integration of sensing capabilities into robotics has traditionally been neglected due to the significant associated technical challenges.

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Article Synopsis
  • Energy harvesting techniques can utilize small natural motions, like leaves swaying in the wind, especially when combined with artificial materials that create mechanical contact with the leaves.
  • We developed and tested four designs of artificial leaves with different flexibility, measuring their contact area and the electricity produced under low wind speeds, achieving significant voltage and current outputs.
  • The study shows that optimizing the balance between flexible and rigid elements in artificial leaves enhances energy conversion efficiency, making them suitable for powering sensors in precision agriculture and environmental monitoring.
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Self-growing robots are an emerging solution in soft robotics for navigating, exploring, and colonizing unstructured environments. However, their ability to grow and move in heterogeneous three-dimensional (3D) spaces, comparable with real-world conditions, is still developing. We present an autonomous growing robot that draws inspiration from the behavioral adaptive strategies of climbing plants to navigate unstructured environments.

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Continuous and distributed monitoring of environmental parameters may pave the way for developing sustainable strategies to tackle climate challenges. State-of-the-art technologies, made with electronic systems, are often costly, heavy, and generate e-waste. Here, we propose a new generation of self-deployable, biocompatible, and luminescent artificial flying seeds for wireless, optical, and eco-friendly monitoring of environmental parameters (i.

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Background: In recent years, the state of Mato Grosso has presented one of the highest dengue incidence rates in Brazil. The meeting of the Amazon, Cerrado and Pantanal biomes results in a large variation of rainfall and temperature across different regions of the state. In addition, Mato Grosso has been undergoing intense urban growth since the 1970s, mainly due to the colonization of the Mid-North and North regions.

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