Autonomous Restructuring of Asteroids into Rotating Space Stations

Asteroid restructuring uses robotics, self replication, and mechanical automatons to autonomously restructure an asteroid into a large rotating space station. The restructuring process makes structures from asteroid oxide materials; uses productive self-replication to make replicators, helpers, and products; and creates a multiple floor station to support a large population. In an example simulation, it takes 12 years to autonomously restructure a large asteroid into the space station. This is accomplished with a single rocket launch. The single payload contains a base station, 4 robots (spiders), and a modest set of supplies. Our simulation creates 3000 spiders and over 23,500 other pieces of equipment. Only the base station and spiders (replicators) have advanced microprocessors and algorithms. These represent 21st century technologies created and trans-ported from Earth. The equipment and tools are built using in-situ materials and represent 18th or 19th century technologies. The equipment and tools (helpers) have simple mechanical programs to perform repetitive tasks. The resulting example station would be a rotating framework almost 5 kilometers in diameter. Once completed, it could support a population of over 700,000 people. Many researchers identify the high launch costs, the harsh space environment, and the lack of gravity as the key obstacles hindering the development of space stations. The single probe addresses the high launch cost. The autonomous construction eliminates the harsh space environment for construction crews. The completed rotating station provides radiation protection and centripetal gravity for the first work crews and colonists.Comment: 65 pages, 53 figures, 25 tables; Version 2 includes editorial changes, improved dumbbell stability details, and reference updates and addition

Conformal Additive Manufacturing and Cooperative Robotic Repair and Diagnosis

In the past several years exponential growth has occurred in many industries, including additive manufacturing (AM) and robotics, enabling fascinating new technologies and capabilities. As these technologies mature, the need for higher-level abilities becomes more apparent. For instance, even with current, commercial state-of-the-art technology in AM it is impossible to deposit material onto a nonplanar surface. This limitation prevents the ability to fully encase objects for packaging, to create objects with hollow features or voids, and even to retrofit or repair preexisting items. These limitations can be addressed by the introduction of a conformal AM (CAM) process or more concretely the process in which material is deposited normal to the surface of an object as opposed to solely planar layers. Therefore, one of the main contributions of this work is the development of two novel methods to generate layers from an initial object to a desired object for use in two- and three-dimensional CAM processes. The first method is based on variable offset curves and subject to mild convexity conditions for both the initial and desired object. The second method reparametrizes solutions to Laplace's equation and does not suffer from these limitations. A third method is then presented that alters solutions from the previous methods to incorporate hollow features or voids into the layer generation process. Although these hollow features must obey mild convexity conditions, the location and number of said features is not limited. Examples of all three layering methods are provided in both two- and three-dimensions. Interestingly, these same methods can also be applied to determine the collision-free configuration space in certain robot motion planning applications. However, ultimately, the most compelling application may be in the repair of damaged items. Given an accurate model of a damaged item, these techniques, in conjunction with fused deposition modeling devices embedded on robotic arms, can be leveraged to restore a damaged item to its original condition. In a separate but similar vein, although robotic systems are becoming more capable each day, their designs still lack almost any semblance of a repair mechanism. This issue is increasingly important in situations where robotic systems are deployed to isolated or even hostile environments as human intervention is limited or impossible. The second half of this work focuses on solving this issue by introducing the Hexagonal Distributed Modular Robot (HexDMR) System which is capable of autonomous team repair and diagnosis. In particular, agents of the HexDMR system are composed of heterogeneous modules with different capabilities that may be replaced when damaged. The remainder of this work discusses the design of each of these modules in detail. Additionally, all possible non-isomorphic functional representations of a single agent are enumerated and a case study is provided to compare the performance between two possible iterations. Then, the repair procedures for an agent in the system are outlined and verified through experiments. Finally, a two-step diagnosis procedure based on both qualitative and quantitative measures is introduced. The particle filter based quantitative portion of this procedure is verified through simulation for two separate robot configurations, while the entire procedure is validated through experiments