Intrinsic and environmental factors modulating autonomous robotic search under high uncertainty.

Autonomous robotic search problems deal with different levels of uncertainty. When uncertainty is low, deterministic strategies employing available knowledge result in most effective searches. However, there are domains where uncertainty is always high since information about robot location, environment boundaries or precise reference points is unattainable, e.g., in cave, deep ocean, planetary exploration, or upon sensor or communications impairment. Furthermore, latency regarding when search targets move, appear or disappear add to uncertainty sources. Here we study intrinsic and environmental factors that affect low-informed robotic search based on diffusive Brownian, naive ballistic, and superdiffusive strategies (Lévy walks), and in particular, the effectiveness of their random exploration. Representative strategies were evaluated considering both intrinsic (motion drift, energy or memory limitations) and extrinsic factors (obstacles and search boundaries). Our results point towards minimum-knowledge based modulation approaches that can adjust distinct spatial and temporal aspects of random exploration to lead to effective autonomous search under uncertainty.

BtM, a Low-cost Open-source Datalogger to Estimate the Water Content of Nonvascular Cryptogams.

Communities of nonvascular cryptogams, such as mosses or lichens, are an important part of the Earth's biodiversity, contributing to the regulation of the carbon and nitrogen cycles in many ecosystems. Being poikilohydric organisms, they do not actively control their internal water content and need a humid environment to activate their metabolism. Therefore, studying water relationships of nonvascular cryptogams is crucial to understand both their diversity patterns and their functions in the ecosystems. We present the BtM datalogger, a low-cost open-source platform for the study of the water content of nonvascular cryptogams. The datalogger is designed to measure ambient temperature, humidity, and conductance from up to eight samples simultaneously. We provide a design for a printed circuit board (PCB), a detailed protocol to assemble the components, and the required source code. All this makes the assembly of the BtM datalogger accessible to any research group, even to those without previous specialized knowledge. Therefore, the design presented here has the potential to help popularize the use of this type of device among ecologists and field biologists.