Light absorption enhancement and radiation hardening for triple junction solar cell through bioinspired nanostructures.

Multi-junction solar cells constitute the main source of power for space applications. However, exposure of solar cells to the space radiation environment significantly degrades their performance across the mission lifetime. Here, we seek to improve the radiation hardness of the triple junction solar cell, GaInP/Ga(In)As/Ge, by decreasing the thickness of the more sensitive middle junction. Thin junctions facilitate the collection of minority carriers and show slower degradation due to defects. However, thinning the junction decreases the absorption, and consequently, the expected photocurrent. To compensate for this loss, we examined two bioinspired surface patterns that exhibit anti-reflective and light-trapping properties: (a) the moth-eye structure which enables vision in poorly illuminated environments and (b) the patterns of the hard cell of a unicellular photosynthetic micro-alga, the diatoms. We parametrize and optimize the biomimetic structures, aiming to maximize the absorbed light by the solar cell while achieving significant reduction in the middle junction thickness. The density of the radiation-induced defects is independent of the junction thickness, as we demonstrate using Monte Carlo simulations, allowing the direct comparison of different combinations of middle junction thicknesses and light trapping structures. We incorporate the radiation effects into the solar cell model as a decrease in minority carrier lifetime and an increase in surface recombination velocity, and we quantify the gain in efficiency for different combinations of junction thickness and the light-trapping structure at equal radiation damage. Solar cells with thin junctions compensated by the light-trapping structures offer a promising approach to improve solar cell radiation hardness and robustness, with up to 2% higher end-of-life efficiency than the commonly used configuration at high radiation exposure.

Space Debris Removal: Learning to Cooperate and the Price of Anarchy.

In this paper we study space debris removal from a game-theoretic perspective. In particular we focus on the question whether and how self-interested agents can cooperate in this dilemma, which resembles a tragedy of the commons scenario. We compare centralised and decentralised solutions and the corresponding price of anarchy, which measures the extent to which competition approximates cooperation. In addition we investigate whether agents can learn optimal strategies by reinforcement learning. To this end, we improve on an existing high fidelity orbital simulator, and use this simulator to obtain a computationally efficient surrogate model that can be used for our subsequent game-theoretic analysis. We study both single- and multi-agent approaches using stochastic (Markov) games and reinforcement learning. The main finding is that the cost of a decentralised, competitive solution can be significant, which should be taken into consideration when forming debris removal strategies.

A Note on the Depth-from-Defocus Mechanism of Jumping Spiders.

Jumping spiders are capable of estimating the distance to their prey relying only on the information from one of their main eyes. Recently, it has been shown that jumping spiders perform this estimation based on image defocus cues. In order to gain insight into the mechanisms involved in this blur-to-distance mapping as performed by the spider and to judge whether inspirations can be drawn from spider vision for depth-from-defocus computer vision algorithms, we constructed a three-dimensional (3D) model of the anterior median eye of the Metaphidippus aeneolus, a well studied species of jumping spider. We were able to study images of the environment as the spider would see them and to measure the performances of a well known depth-from-defocus algorithm on this dataset. We found that the algorithm performs best when using images that are averaged over the considerable thickness of the spider's receptor layers, thus pointing towards a possible functional role of the receptor thickness for the spider's depth estimation capabilities.

Morphologic and Aerodynamic Considerations Regarding the Plumed Seeds of Tragopogon pratensis and Their Implications for Seed Dispersal.

Tragopogon pratensis is a small herbaceous plant that uses wind as the dispersal vector for its seeds. The seeds are attached to parachutes that increase the aerodynamic drag force and increase the total distance travelled. Our hypothesis is that evolution has carefully tuned the air permeability of the seeds to operate in the most convenient fluid dynamic regime. To achieve final permeability, the primary and secondary fibres of the pappus have evolved with complex weaving; this maximises the drag force (i.e., the drag coefficient), and the pappus operates in an "optimal" state. We used computational fluid dynamics (CFD) simulations to compute the seed drag coefficient and compare it with data obtained from drop experiments. The permeability of the parachute was estimated from microscope images. Our simulations reveal three flow regimes in which the parachute can operate according to its permeability. These flow regimes impact the stability of the parachute and its drag coefficient. From the permeability measurements and drop experiments, we show how the seeds operate very close to the optimal case. The porosity of the textile appears to be an appropriate solution to achieve a lightweight structure that allows a low terminal velocity, a stable flight and a very efficient parachute for the velocity at which it operates.

Biomimetics on seed dispersal: survey and insights for space exploration.

Seeds provide the vital genetic link and dispersal agent between successive generations of plants. Without seed dispersal as a means of reproduction, many plants would quickly die out. Because plants lack any sort of mobility and remain in the same spot for their entire lives, they rely on seed dispersal to transport their offspring throughout the environment. This can be accomplished either collectively or individually; in any case as seeds ultimately abdicate their movement, they are at the mercy of environmental factors. Thus, seed dispersal strategies are characterized by robustness, adaptability, intelligence (both behavioral and morphological), and mass and energy efficiency (including the ability to utilize environmental sources of energy available): all qualities that advanced engineering systems aim at in general, and in particular those that need to enable complex endeavors such as space exploration. Plants evolved and adapted their strategy according to their environment, and taken together, they enclose many desirable characteristics that a space mission needs to have. Understanding in detail how plants control the development of seeds, fabricate structural components for their dispersal, build molecular machineries to keep seeds dormant up to the right moment and monitor the environment to release them at the right time could provide several solutions impacting current space mission design practices. It can lead to miniaturization, higher integration and packing efficiency, energy efficiency and higher autonomy and robustness. Consequently, there would appear to be good reasons for considering biomimetic solutions from plant kingdom when designing space missions, especially to other celestial bodies, where solid and liquid surfaces, atmosphere, etc constitute and are obviously parallel with the terrestrial environment where plants evolved. In this paper, we review the current state of biomimetics on seed dispersal to improve space mission design.

Autonomous spacecraft landing through human pre-attentive vision.

In this work, we exploit a computational model of human pre-attentive vision to guide the descent of a spacecraft on extraterrestrial bodies. Providing the spacecraft with high degrees of autonomy is a challenge for future space missions. Up to present, major effort in this research field has been concentrated in hazard avoidance algorithms and landmark detection, often by reference to a priori maps, ranked by scientists according to specific scientific criteria. Here, we present a bio-inspired approach based on the human ability to quickly select intrinsically salient targets in the visual scene; this ability is fundamental for fast decision-making processes in unpredictable and unknown circumstances. The proposed system integrates a simple model of the spacecraft and optimality principles which guarantee minimum fuel consumption during the landing procedure; detected salient sites are used for retargeting the spacecraft trajectory, under safety and reachability conditions. We compare the decisions taken by the proposed algorithm with that of a number of human subjects tested under the same conditions. Our results show how the developed algorithm is indistinguishable from the human subjects with respect to areas, occurrence and timing of the retargeting.

The impact of expertise on brain computer interface based salient image retrieval.

Autonomous decision making modules in computer vision application allow recognition and classification of different objects, persons, and events in images and video sequences and also make it possible to classify different sensor readings (e.g. images) according to their scientific saliencies. In this paper, we propose a new approach to create the training set for these algorithms by retrieving salient images using electroencephalogram (EEG) and brain computer interface (BCI) and rapid image presentation. To this end, two groups of subjects, namely, expert and novice subjects were asked to participate in our experiments. We show that a relatively high retrieval accuracy can be achieved for most of the subjects. Furthermore, to assess the impact of expertise on the retrieval process, we study their EEG signals separately and show that there is a clear difference in their brainwaves while observing salient images.

Brain-machine interfaces for space applications.

In human space flight, astronauts are the most precious "payload" and astronaut time is extremely valuable. Astronauts operate under unusual and difficult conditions since the absence of gravity makes some of simple tasks tedious and cumbersome. Therefore, computer interfaces for astronauts are generally designed first for safety and then for functionality. In addition to general constraints like mass, volume, robustness, technological solutions need to enhance their functionality and efficiency while not compromising safety. Brain-machine interfaces show promising properties in this respect. It is however not obvious that devices developed for functioning on-ground can be used as hands-free interfaces for astronauts. This paper intends to address the potential of brain-machine interfaces for space applications, to review expected issues related with microgravity effects on brain activities, to highlight those research directions on brain-machine interfaces with the perceived highest potential impact on future space applications, and to embed these into long-term plans with respect to human space flight. We conclude by suggesting research and development steps considered necessary to include brain-machine interface technology in future architectures for human space flight.

Brain-machine interfaces for space applications-research, technological development, and opportunities.

Recent advances in brain research and brain-machine interfaces suggest these devices could play a central role in future generation computer interfaces. Successes in the use of brain machine interfaces for patients affected by motor paralysis, as well as first developments of games and gadgets based on this technology have matured the field and brought brain-machine interfaces to the brink of more general usability and eventually of opening new markets. In human space flight, astronauts are the most precious "payload" and astronaut time is extremely valuable. Astronauts operate under difficult and unusual conditions since the absence of gravity renders some of the very simple tasks tedious and cumbersome. Therefore, computer interfaces are generally designed for safety and functionality. All improvements and technical aids to enhance their functionality and efficiency, while not compromising safety or overall mass requirements, are therefore of great interest. Brain machine interfaces show some interesting properties in this respect. It is however not obvious that devices developed for functioning on-ground can be used as hands-free interfaces for astronauts. This chapter intends to highlight the research directions of brain machine interfaces with the perceived highest potential impact on future space applications, and to present an overview of the long-term plans with respect to human space flight. We conclude by suggesting research and development steps considered necessary to include brain-machine interface technology in future architectures for human space flight.