On-line Optimal Ranging Sensor Deployment for Robotic Exploration

<div>Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).</div>

On-line Optimal Ranging Sensor Deployment for Robotic Exploration

<div>Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).</div>

Towards a Biomanufactory on Mars

A crewed mission to and from Mars may include an exciting array of enabling biotechnologies that leverage inherent mass, power, and volume advantages over traditional abiotic approaches. In this perspective, we articulate the scientific and engineering goals and constraints, along with example systems, that guide the design of a surface biomanufactory. Extending past arguments for exploiting stand-alone elements of biology, we argue for an integrated biomanufacturing plant replete with modules for microbial in situ resource utilization, production, and recycling of food, pharmaceuticals, and biomaterials required for sustaining future intrepid astronauts. We also discuss aspirational technology trends in each of these target areas in the context of human and robotic exploration missions.

Mars and the ESA Science Programme - the case for Mars polar science

Current plans within the European Space Agency (ESA) for the future investigation of Mars (after the ExoMars programme) are centred around participation in the Mars Sample Return (MSR) programme led by NASA. This programme is housed within the Human and Robotic Exploration (HRE) Directorate of ESA. This White Paper, in response to the Voyage 2050 call, focuses on the important scientific objectives for the investigation of Mars outside the present HRE planning. The achievement of these objectives by Science Directorate missions is entirely consistent with ESA’s Science Programme. We illustrate this with a theme centred around the study of the Martian polar caps and the investigation of recent (Amazonian) climate change produced by known oscillations in Mars’ orbital parameters. Deciphering the record of climate contained within the polar caps would allow us to learn about the climatic evolution of another planet over the past few to hundreds of millions of years, and also addresses the more general goal of investigating volatile-related dynamic processes in the Solar System.

Astrobiology (Overview)

Astrobiology seeks to understand the origin, evolution, distribution, and future of life in the universe and thus to integrate biology with planetary science, astronomy, cosmology, and the other physical sciences. The discipline emerged in the late 20th century, partly in response to the development of space exploration programs in the United States, Russia, and elsewhere. Many astrobiologists are now involved in the search for life on Mars, Europa, Enceladus, and beyond. However, research in astrobiology does not presume the existence of extraterrestrial life, for which there is no compelling evidence; indeed, it includes the study of life on Earth in its astronomical and cosmic context. Moreover, the absence of observed life from all other planetary bodies requires a scientific explanation, and suggests several hypotheses amenable to further observational, theoretical, and experimental investigation under the aegis of astrobiology. Despite the apparent uniqueness of Earth’s biosphere— the “n = 1 problem”—astrobiology is increasingly driven by large quantities of data. Such data have been provided by the robotic exploration of the Solar System, the first observations of extrasolar planets, laboratory experiments into prebiotic chemistry, spectroscopic measurements of organic molecules in extraterrestrial environments, analytical advances in the biogeochemistry and paleobiology of very ancient rocks, surveys of Earth’s microbial diversity and ecology, and experiments to delimit the capacity of organisms to survive and thrive in extreme conditions.

Stereo vision-based visual odometry for planetary exploration

The ability to localize an unmanned vehicle is an essential requirement for extraterrestrial robotic exploration missions. The goal of this thesis is to develop a visual odometry algorithm capable of operating in real-time and in natural unstructured environments. Accuracy, repeatability and computational cost were the primary considerations during the development of the algorithm. The resulting visual odometry algorithm can operate in real-time and provides the foundations for further development. More commonly used approaches for localization include the use of inertial measurement units (IMU) or wheel odometry, which are prone to drift and slippage respectively, making them unreliable for long duration missions. Visual odometry also experiences error accumulation, however, it offers the possibility of mitigating this problem through techniques such as loop closing and bundle adjustment. The performance of the Iterative Closest Point (ICP) algorithm in conjunction within the visual odometer was also evaluated and shown to have improved overall localization performance.

Stereo vision-based visual odometry for planetary exploration

The ability to localize an unmanned vehicle is an essential requirement for extraterrestrial robotic exploration missions. The goal of this thesis is to develop a visual odometry algorithm capable of operating in real-time and in natural unstructured environments. Accuracy, repeatability and computational cost were the primary considerations during the development of the algorithm. The resulting visual odometry algorithm can operate in real-time and provides the foundations for further development. More commonly used approaches for localization include the use of inertial measurement units (IMU) or wheel odometry, which are prone to drift and slippage respectively, making them unreliable for long duration missions. Visual odometry also experiences error accumulation, however, it offers the possibility of mitigating this problem through techniques such as loop closing and bundle adjustment. The performance of the Iterative Closest Point (ICP) algorithm in conjunction within the visual odometer was also evaluated and shown to have improved overall localization performance.