The purpose of this paper is to discuss the problem of engineering tools for scientific discovery within the context of the use of engineering techniques and methods for space exploration. Two research articles are compared and contrasted. What the articles share in common—though they differ in their applications and treatments of this commonality—is the notion of using autonomous systems in cooperation with one another, sometimes in conjunction with the notion from engineering of ‘swarm-based techniques’, to achieve complex and largely non-autonomous goals.
The central thesis of the first article is that systems engineering is posed a difficult and important problem in applying the relatively novel approach known as ‘swarm-based systems’ (Hinchey et. al. 2005). A ‘swarm’ in this sense consists of a large number of relatively simple objects that have local interactions with one another. These interactions combine to yield a kind of emergent complex behavior which in a clear sense goes beyond the mere summation of the individual interactions themselves. Some ‘swarms’, thus defined, are intelligent in the sense that they can learn. The authors of the article are of course concerned with a specifically engineered notion of swarm, which include what they call ‘agent swarms’, ‘swarm simulations’, ‘swarm intelligence’, and ‘swarm robotics’ (Hinchey et. al. 2005, sec. 2).
Having provided examples of swarm engineering that include NASA swarm-based missions, as well as the integration of swarm theory into artificial neural network paradigms for studying cognition, the authors conclude that swarm techniques and the resulting technologies are promising tools for exploring space, enabling scientific observational missions that would be unavailable in missions confined to a single, autonomous spacecraft.
The second article discussed here takes a different approach, though one that is largely compatible due to its appearing to form part of the same long-term research program. Here the emphasis is not on the abstract notion of a swarm, but rather centers more directly on the idea of autonomous and autonomic systems (Truszkowski et. al. 2006,). An autonomous system, as understood in the context of space research and exploration, is one that enables certain crucial functions of spacecraft and associated entities to be done without external assistance. Such functions include maintenance and repair of a spacecraft, and the loaded of propellants such as fuel. The related notion of an autonomic system is one that is essentially self-regulating, in the way that the human autonomic nervous system regulates itself.
The authors of the second article are primarily concerned to detail the advantages of autonomy (and autonomicity) for mission systems in space exploration. The advantages of autonomy include reduced operations cost and adaptability concerning the achievement of the particular goals the functionality of a mission system is designed to achieve. Autonomicity promises, at least in theory, to make possible certain missions into space that are of what the authors call ‘higher order’ than missions previously made or flown (Truszkowski et. al. 2006, 279-80).
The use of swarm technologies and methods is complementary with, but distinct from, investigation of the possibilities concerning autonomy and autonomicity in space travel and research. The first group of authors discussed here are concerned to detail the possible benefits of swarm technology. These benefits include use of the kind of emergent complexity that has become familiar with the advent of so-called ‘chaos theory’, which is essentially the study of how minute variations within the initial conditions of a transtemporal system can produce wildly divergent final or mid-term conditions (Boccaletti et. al. 2000). By contrast, the second group of authors are concerned to explain and extol and virtues of the utilization of autonomous and autonomic engineering systems for space exploration. They point out that ideally NASA would be able to launch a spacecraft and then simply passively receive data from the craft, without the necessity of in-flight directions or terrestrial personnel helping to make corrections.
The two proposals are fully compatible, although they are distinct. Indeed, in certain cases—especially the use of nano-technologies in the engineering of swarm systems (Hinchey et. al. 2005, sec. 3.1)—there may be no question but that, ultimately, the systems at least approximate the twin goals of autonomy and autonomicity.
The conclusion of the paper is that swarm-based engineering techniques and methods are promising tools for ultimately contributing innovative ways for exploring and researching space. Additionally, the twin goals of autonomy and autonomicity for exploratory spacecraft have important advantages for the same sort of exploration and research, advantages that have yet to be fully realized. Although they are distinct phenomena, both swarm-engineering-techniques and the goals of full autonomy and autonomicity work well together, and in theory could be used in tandem to improve our ability to explore and research space. Though the articles selected were published relatively early in the advent of these new ideas and technologies, both swarm-engineering and autonomy and autonomicity continue to be studied and debated today.
- Boccaletti, S., Grebogi, C., Lai, Y. C., Mancini, H., & Maza, D. (2000). The control of chaos: theory and applications. Physics reports, 329(3), 103-197.
- Hinchey, M. G., Rash, J. L., Truszkowski, W., Rouff, C., & Sterritt, R. (2005). Autonomous and Autonomic Swarms. Software Engineering Research and Practice, June, 36-44.
- NAE Grand Challenges for Engineering (http://www.engineeringchallenges.org).
- Truszkowski, W. F., Hinchey, M. G., Rash, J. L., & Rouff, C. (2006). Autonomous and autonomic systems: a paradigm for future space exploration missions. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, volume 36(3), 279-291.