Particle Computation: Complexity, Algorithms, and Logic

We investigate algorithmic control of a large swarm of mobile particles (such as robots, sensors, or building material) that move in a 2D workspace using a global input signal (such as gravity or a magnetic field). We show that a maze of obstacles to the environment can be used to create complex systems. We provide a wide range of results for a wide range of questions. These can be subdivided into external algorithmic problems, in which particle configurations serve as input for computations that are performed elsewhere, and internal logic problems, in which the particle configurations themselves are used for carrying out computations. For external algorithms, we give both negative and positive results. If we are given a set of stationary obstacles, we prove that it is NP-hard to decide whether a given initial configuration of unit-sized particles can be transformed into a desired target configuration. Moreover, we show that finding a control sequence of minimum length is PSPACE-complete. We also work on the inverse problem, providing constructive algorithms to design workspaces that efficiently implement arbitrary permutations between different configurations. For internal logic, we investigate how arbitrary computations can be implemented. We demonstrate how to encode dual-rail logic to build a universal logic gate that concurrently evaluates and, nand, nor, and or operations. Using many of these gates and appropriate interconnects, we can evaluate any logical expression. However, we establish that simulating the full range of complex interactions present in arbitrary digital circuits encounters a fundamental difficulty: a fan-out gate cannot be generated. We resolve this missing component with the help of 2x1 particles, which can create fan-out gates that produce multiple copies of the inputs. Using these gates we provide rules for replicating arbitrary digital circuits.Comment: 27 pages, 19 figures, full version that combines three previous conference article

ChatGPT for Robotics: Design Principles and Model Abilities

This paper presents an experimental study regarding the use of OpenAI's ChatGPT for robotics applications. We outline a strategy that combines design principles for prompt engineering and the creation of a high-level function library which allows ChatGPT to adapt to different robotics tasks, simulators, and form factors. We focus our evaluations on the effectiveness of different prompt engineering techniques and dialog strategies towards the execution of various types of robotics tasks. We explore ChatGPT's ability to use free-form dialog, parse XML tags, and to synthesize code, in addition to the use of task-specific prompting functions and closed-loop reasoning through dialogues. Our study encompasses a range of tasks within the robotics domain, from basic logical, geometrical, and mathematical reasoning all the way to complex domains such as aerial navigation, manipulation, and embodied agents. We show that ChatGPT can be effective at solving several of such tasks, while allowing users to interact with it primarily via natural language instructions. In addition to these studies, we introduce an open-sourced research tool called PromptCraft, which contains a platform where researchers can collaboratively upload and vote on examples of good prompting schemes for robotics applications, as well as a sample robotics simulator with ChatGPT integration, making it easier for users to get started with using ChatGPT for robotics

Spatial cell firing during virtual navigation of open arenas by head-restrained mice

We present a mouse virtual reality (VR) system which restrains head-movements to horizontal rotations, compatible with multi-photon imaging. This system allows expression of the spatial navigation and neuronal firing patterns characteristic of real open arenas (R). Comparing VR to R: place and grid, but not head-direction, cell firing had broader spatial tuning; place, but not grid, cell firing was more directional; theta frequency increased less with running speed; whereas increases in firing rates with running speed and place and grid cells' theta phase precession were similar. These results suggest that the omni-directional place cell firing in R may require local-cues unavailable in VR, and that the scale of grid and place cell firing patterns, and theta frequency, reflect translational motion inferred from both virtual (visual and proprioceptive) and real (vestibular translation and extra-maze) cues. By contrast, firing rates and theta phase precession appear to reflect visual and proprioceptive cues alone

The influences of various mixed dielectric fluids on the performance electrical discharge machining of AISI D2 hardened steel

This research mainly explores the influence of various mixed dielectric fluids on the performance of electrical discharge machining of AISI D2 hardened steels. In this investigation, four types of dielectric fluids such as pure kerosene, kerosene and chromium powder mixed, kerosene and Span-20 surfactant and the combination of kerosene with chromium powder and Span-20 surfactant were studied. The obtained results illustrated that the addition of chromium powder and Span-20 surfactant in the dielectric fluid obtained high material removal rate, low electrode wear rate and good surface finish. The presence of chromium powder will stabilize the gap distance between electrodes which promotes the occurrence of multiple discharges in one input pulse and particle agglomeration is reduced after Span-20 surfactant molecules cover the surface of debris and carbon dregs in kerosene solution. Combination of kerosene with chromium and Span-20 surfactant were found significant to improve the effects of carbon accumulation and drag discharge, and reduce unstable concentrated discharge

Towards heterotic computing with droplets in a fully automated droplet-maker platform

The control and prediction of complex chemical systems is a difficult problem due to the nature of the interactions, transformations and processes occurring. From self-assembly to catalysis and self-organization, complex chemical systems are often heterogeneous mixtures that at the most extreme exhibit system-level functions, such as those that could be observed in a living cell. In this paper, we outline an approach to understand and explore complex chemical systems using an automated droplet maker to control the composition, size and position of the droplets in a predefined chemical environment. By investigating the spatio-temporal dynamics of the droplets, the aim is to understand how to control system-level emergence of complex chemical behaviour and even view the system-level behaviour as a programmable entity capable of information processing. Herein, we explore how our automated droplet-maker platform could be viewed as a prototype chemical heterotic computer with some initial data and example problems that may be viewed as potential chemically embodied computations

Microgravity: A Teacher's Guide With Activities in Science, Mathematics, and Technology

The purpose of this curriculum supplement guide is to define and explain microgravity and show how microgravity can help us learn about the phenomena of our world. The front section of the guide is designed to provide teachers of science, mathematics, and technology at many levels with a foundation in microgravity science and applications. It begins with background information for the teacher on what microgravity is and how it is created. This is followed with information on the domains of microgravity science research; biotechnology, combustion science, fluid physics, fundamental physics, materials science, and microgravity research geared toward exploration. The background section concludes with a history of microgravity research and the expectations microgravity scientists have for research on the International Space Station. Finally, the guide concludes with a suggested reading list, NASA educational resources including electronic resources, and an evaluation questionnaire

New Behavioral Insights Into Home Range Orientation of the House Mouse (Mus musculus)

Home-range orientation is a necessity for an animal that maintains an area of daily activity. The ability to navigate efficiently among goals not perceived at the starting point requires the animal to rely on place recognition and vector knowledge. These two components of navigation allow the animal to dynamically update its current position and link that position with the locomotor distance and direction needed to reach a goal. In order to use place knowledge and vector knowledge the animal must learn and remember relevant spatial information obtained from the environment and from internal feedback. The research in this dissertation focuses on behavioral components of topographic orientation, using the house mouse as a model species. Specifically, this research made important discoveries in three main areas: 1) locomotor exploration behavior, 2) the use of learned spatial information for compass orientation, and 3) testable hypotheses based on the controversial cognitive map. In Chapter 1, I used a radial arm maze to find a systematic locomotor component to exploration behavior, which is typically described as random movement. Exploration refers to the learning process that occurs as an animal acquires relevant spatial information for home-range orientation. I predicted that this process must have a systematic component; and the results revealed that in a radial arm maze, mice avoided exploring a place explored one and two visits prior. Therefore, locomotor exploration does have a systematic component. In Chapter 2, I trained mice to navigate to their home within a circular arena, with access to a visual beacon and an enriched visual background. The mice showed that to navigate home, they preferred to rely on the extra-arena (background) cues for compass direction. However, when these extra-arena cues became unreliable, the mice showed flexibility in their preference by ignoring the visual background and instead relying on the visual beacon to locate home. This flexibility in cue use negates a popular theory, called the snapshot theory, which does not allow for such flexibility in navigation. To further study the use of compass cues in mice, in Chapter 3, I utilized a plus-maze to manipulate both allothetic (environmental) and idiothetic (internal) cues. The purpose was to determine which cue type predominated the directional choice of mice at the maze intersection while both leaving and returning home. Previous studies have ignored the potential difference in cue use during the complete roundtrip an animal would make within its home range. The results show that mice relied on different cues for the outward path and the homing path of a familiar complex roundtrip. Finally, I developed two testable hypotheses and a valid experimental design that can be used to test house mice, and other animals, for the so-called cognitive map. An animal that has a cognitive map would be able to compute a novel shortcut to a goal relying exclusively on the flexibility of such a map, and not from the other two options of novel shortcutting: guidance orientation or path integration. Thus by designing my experiments to eliminate the potential for the mice to rely on a guiding cue to direct them home, and by eliminating the ability to compute a shortcut by summing the vectors previously walked, I was able to test mice for a truly novel, map-based shortcut home. These two hypotheses were named viewpoint extrapolation and viewpoint interpolation and require pure visual exploration to acquire the necessary place and vector knowledge. Both experiments showed that mice were not capable of using pure visual exploration and therefore these studies provide no evidence that mice have a cognitive map. Overall, my research provides evidence that mice do have a mental route-based map and to build such a mental map, locomotor exploration is necessary and sufficient for acquiring relevant spatial knowledge to later use to efficiently navigate