Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques

Implementation of Hardware-Based Expert Systems and Comparison of Their Performance to Software-Based Expert Systems

Expert systems are a form of highly understandable artificial intelligence that allow humans to trace the decision-making processes that are used. While they are typically software implemented and use an iterative algorithm for rule-fact network processing, this is not the only possible implementation approach. This paper implements and evaluates the use of hardware-based expert systems. It shows that they work accurately and can be developed to parallel software implementations. It also compares the processing speed of software and hardware-based expert systems, showing that hardware-based systems typically operate two orders of magnitude faster than the software ones. The potential applications that hardware-based expert systems can be used for and the capabilities that they can provide are discussed.

Are There Biomimetic Lessons from Genetic Regulatory Networks for Developing a Lunar Industrial Ecology?

We examine the prospect for employing a bio-inspired architecture for a lunar industrial ecology based on genetic regulatory networks. The lunar industrial ecology resembles a metabolic system in that it comprises multiple chemical processes interlinked through waste recycling. Initially, we examine lessons from factory organisation which have evolved into a bio-inspired concept, the reconfigurable holonic architecture. We then examine genetic regulatory networks and their application in the biological cell cycle. There are numerous subtleties that would be challenging to implement in a lunar industrial ecology but much of the essence of biological circuitry (as implemented in synthetic biology, for example) is captured by traditional electrical engineering design with emphasis on feedforward and feedback loops to implement robustness.

Viscoelastic Properties of Cell Structures Manufactured Using a Photo-Curable Additive Technology-PJM

This research paper reviews the test results involving viscoelastic properties of cellular structure models made with the PolyJet Matrix-PJM additive technology. The designed test specimens were of complex cellular structure and made of three various photo-curable polymer resin types. Materials were selected taking into account the so-called "soft" and "tough" material groups. Compressive stress relaxation tests were conducted in accordance with the recommendations of standard ISO 3384, and the impact of the geometric structure shape and material selection on viscoelastic properties, as well as the most favorable geometric variants of the tested cellular structure models were determined. Mathematica and Origin software was used to conduct a statistical analysis of the test results and determine five-parameter functions approximating relaxation curves. The most favorable rheological was adopted and its mean parameters determined, which enables to match both printed model materials and their geometry in the future, to make a component with a specific rheological response. Furthermore, the test results indicated that there was a possibility of modelling cellular structures within the PJM technology, using support material as well.

Simulation and Analysis of Self-Replicating Robot Decision-Making Systems

Self-replicating robot systems (SRRSs) are a new prospective paradigm for robotic exploration. They can potentially facilitate lower mission costs and enhance mission capabilities by allowing some materials, which are needed for robotic system construction, to be collected in situ and used for robot fabrication. The use of a self-replicating robot system can potentially lower risk aversion, due to the ability to potentially replenish lost or damaged robots, and may increase the likelihood of mission success. This paper proposes and compares system configurations of an SRRS. A simulation system was designed and is used to model how an SRRS performs based on its system configuration, attributes, and operating environment. Experiments were conducted using this simulation and the results are presented.

Evolution of Complex Niche-Constructing Behaviors and Ecological Inheritance of Adaptive Structures in a Physically Grounded Environment

Niche construction is a process in which organisms modify the selection pressures on themselves and others through their ecological activities, and ecological inheritance is the consequence of niche construction inherited through generations. However, it is still unclear how such mutual interactions between robots or embodied agents and their physical environments can yield complex and divergent evolutionary processes or an open-ended evolution. Our purpose is to clarify what kind of complex and various niche-constructing behaviors evolve in a physically grounded environment under various conditions of ecological inheritance of constructed structures and spatial relationships. We focus on a predator-prey relationship, and constructed an evolutionary model in which a prey creature has to avoid predation through the construction of a structure composed of objects in a 2D physically simulated environment supported by a physics engine. We used a deep auto-encoder to extract the defining feature of adaptive structures automatically. The results in the case of no ecological inheritance revealed that the number of available resources can affect the diversity of emerging adaptive structures. Also, in the case with ecological inheritance, it was found that combinations of two types of ecological inheritance, which are the inheritance of adaptive structures and birthplace, can have strong effects on the diversity of emerging structures and the adaptivity of the population. We expect that findings in evolutionary simulations of niche-constructing behavior might contribute to evolutionary design of robotic builders or robot fabrication, especially when we assume physically simulated environments.