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Space exploration is facing a new era in view of the planned missions to the Moon and Mars. The development and the in-flight validation of new technologies, including analytical and diagnostic platforms, is pivotal for exploring and inhabiting these extreme environments. In this context, biosensors and lab-on-chip devices can play an important role in many situations, such as the analysis of biological samples for assessing the impact of deep space conditions on man and other biological systems, environmental and food safety monitoring, and the search of molecular indicators of past or present life in extra-terrestrial environments. Small satellites such as CubeSats are nowadays increasingly exploited as fast and low-cost platforms for conducting in-flight technology validation. Herein, we report the development of a fully autonomous lab-on-chip platform for performing chemiluminescence-based bioassays in space. The device was designed to be hosted onboard the AstroBio CubeSat nanosatellite, with the aim of conducting its in-flight validation and evaluating the stability of (bio) molecules required for bioassays in a challenging radiation environment. An origami-like microfluidic paperbased analytical format allowed preloading all the reagents in the dried form on the paper substrate, thus simplifying device design and analytical protocols, facilitating autonomous assay execution, and enhancing the stability of reagents. The chosen approach should constitute the first step to implement a mature technology with the aim to conduct life science research in space (e.g., for evaluation the effect of deep space conditions on living organisms or searching molecular evidence of life) more easily and at lower cost than previously possible.

Moving in an unstructured environment such as soil requires approaches that are constrained by the physics of this complex medium and can ensure energy efficiency and minimize friction while exploring and searching. Among living organisms, plants are the most efficient at soil exploration, and their roots show remarkable abilities that can be exploited in artificial systems. Energy efficiency and friction reduction are assured by a growth process wherein new cells are added at the root apex by mitosis while mature cells of the root remain stationary and in contact with the soil. We propose a new concept of root-like growing robots that is inspired by these plant root features. The device penetrates soil and develops its own structure using an additive layering technique: each layer of new material is deposited adjacent to the tip of the device. This deposition produces both a motive force at the tip and a hollow tubular structure that extends to the surface of the soil and is strongly anchored to the soil. The addition of material at the tip area facilitates soil penetration by omitting peripheral friction and thus decreasing the energy consumption down to 70% comparing with penetration by pushing into the soil from the base of the penetration system. The tubular structure provides a path for delivering materials and energy to the tip of the system and for collecting information for exploratory tasks.

The growth process of roots consists of many activities, such as exploring the soil volume, mining minerals, avoiding obstacles and taking up water to fulfil the plant's primary functions, that are performed differently, depending on environmental conditions. Root movements are strictly related to a root decision strategy, which helps plants to survive under stressful conditions by optimizing energy consumption. In this work, we present a novel image-analysis tool to study the kinematics of the root tip (apex), named analyser for root tip tracks (ARTT). The software implementation combines a segmentation algorithm with additional software imaging filters in order to realize a 2D tip detection. The resulting paths, or tracks, arise from the sampled tip positions through the acquired images during the growth. ARTT allows work with no markers and deals autonomously with new emerging root tips, as well as handling a massive number of data relying on minimum user interaction. Consequently, ARTT can be used for a wide range of applications and for the study of kinematics in different plant species. In particular, the study of the root growth and behaviour could lead to the definition of novel principles for the penetration and/or control paradigms for soil exploration and monitoring tasks. The software capabilities were demonstrated by experimental trials performed with Zea mays and Oryza sativa.