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No abstract available.

Distributed reconfiguration is an important problem in multi-robot systems such as mobile sensor nets and metamorphic robot systems. In this work, we present a scalable distributed reconfiguration algorithm, hierarchical median decomposition, to achieve arbitrary target configurations. Our algorithm is built on top of a novel distributed median consensus estimator. The algorithms presented are fully distributed and do not require global communication. We show results from simulations in an open source multi-robot simulator.

When exploring computing elements made from technologies other than complementary metal-oxide-semiconductor, it is imperative to investigate circuits and systems assuming realistic physical implementation constraints. This paper looks at molecular quantum-dot cellular automata (QCA) devices within this context. With molecular QCA, physical coplanar wire crossings may be very difficult to fabricate in the near to midterm. Here, we consider how this will affect interconnect. We introduce a novel technique to remove wire crossings in a given design in order to facilitate the self-assembly of real circuits - thus, providing meaningful and functional design targets for both physical and computer scientists. The proposed methodology eliminates all wire crossings with minimal logic gate/node duplications. Simulation results based on existing QCA circuits and other benchmarks are presented, and suggest that further investigation is needed.

Quantum-dot Cellular Automata (QCA) is a novel computing mechanism that can represent binary information based on spatial distribution of electron charge configuration in chemical molecules. In this paper, we present partitioning and placement algorithms for a large-scale automatic QCA layout. The purpose of zone partitioning is to initially partition a given circuit such that a single clock potential modulates the interdot barriers in all of the QCA cells within each zone. We then place these zones during our placement step. We identify several objectives and constraints that will enhance the buildability of QCA circuits and use them in our optimization process. The results are intended to define what is computationally interesting and could actually be built within a set of predefined constraints.

When exploring computing elements made from technologies other than CMOS, it is imperative to investigate the effects of physical implementation constraints. This paper focuses on molecular quantum-dot cellular automata circuits. For these circuits, it is very difficult for chemists to fabricate wire crossings (at least in the near future). A novel technique is introduced to remove wire crossings in a given circuit to facilitate the self assembly of real circuits - thus providing meaningful and functional design targets for both physical and computer scientists. The technique eliminates all wire crossings with minimal logic gate/node duplications. Experimental results based on existing QCA circuits and other benchmarks are quite encouraging, and suggest that further investigation is needed.

Quantum-dot Cellular Automata (QCA) is a novel computing mechanism that can represent binary information based on spatial distribution of an electron charge configuration in chemical molecules. In this article, we present the first partitioning and placement algorithm for automatic QCA layout. We identify several objectives and constraints that will enhance the buildability of QCA circuits. The results are intended to: (1) define what is computationally interesting and could actually be built within a set of predefined constraints, (2) project what designs will be possible as additional constructs become realizable, and (3) provide a vehicle that we can use to compare QCA systems to silicon-based systems.

Quantum-dot Cellular Automata (QCA) is a novel computing mechanism that can represent binary information based on spatial distribution of electron charge configuration in chemical molecules. It has the potential to allow for circuits and systems with functional densities that are better than end of the roadmap CMOS, but also imposes new constraints on system designers. In this paper we develop the first cell-level placement of QCA circuits, where the given circuit is assumed to be partitioned into 4-phase asynchronous QCA timing zones. We formulate the QCA cell placement in each timing zone as a unidirectional geometric embedding of k-layered bipartite graphs. We then present an analytical and a stochastic solution for minimizing the wire crossings and wire length in these placement solutions.

This paper details nano-scale devices being researched by physical scientists to build computational systems. It also reviews some existing system design work that uses the devices to be discussed. It concludes with a discussion of how the authors believe system-level research can best be used to positively affect actual device development. This work has led to a more thorough design methodology that address whether or not computationally interesting and buildable circuits are possible with the quantum-dot cellular automata (QCA), while also providing significant wins over end-of-the-roadmap CMOS.

Move Value Estimation for Robot Teams (MVERT) is a robot action selection algorithm for teams performing multiple competing tasks. The goal of MVERT is to select actions for robot team members to maximize the team's joint utility toward overall mission progress in a computationally efficient manner. MVERT is fully distributed, with each robot using information about other teammates to select its action with the greatest value. MVERT selects actions for a robot team to perform multi-task exploration and dynamic target observation. Successful action selection is demonstrated in simulation for exploration and in simulation and on robots for dynamic target observation.