Keisuke Okumura 교수

In order to confirm the reliability of a continuous-energy Monte Carlo burn-up calculation code MVP- BURN, it was applied to the burn-up benchmark problems for a high conversion LWR lattice and a BWR lattice with burnable poison rods. The results of MVP-BURN have shown good agreements with those of a deterministic code SRAC95 for burn-up changes of infinite neutron multiplication factor, conversion ratio, power distribution, and number densities of major fuel nuclides. Serious propagation of sta

In the Multi-Agent Path Finding (MAPF) problem, a set of agents moving on a graph must reach their own respective destinations without inter-agent collisions. In practical MAPF applications such as navigation in automated warehouses, where occasionally there are hundreds or more agents, MAPF must be solved iteratively online on a lifelong basis. Such scenarios rule out simple adaptations of offline compute-intensive optimal approaches; and scalable sub-optimal algorithms are hence appealing for

The need for the protocol conversion has been recognized with the proliferation of heterogeneous networks. From a formal viewpoint, we regard that problem as generating a protocol which satisfies the properties of the conversion. In this paper, we prove that, one can determine whether a converter exists, for some protocol classes, given protocols in the form of communicating finite automata, Moreover, we give a construction method for such a converter for those classes, and derive an upper bound

Visible-to-UV photon upconversion based on triplet-triplet annihilation (TTA-UC) sensitized by lead halide perovskite nanocrystals is demonstrated for the first time. The surface modification of nanocrystals with energy transmitter ligands plays a key role in the effective triplet sensitization, resulting in high TTA-UC efficiency over 4%. This work proves the promising potential of perovskite nanocrystals as a versatile, next-generation triplet sensitizer. The first example of visible-to-UV pho

We propose a novel complete algorithm for multi-agent pathfinding (MAPF) called lazy constraints addition search for MAPF (LaCAM). MAPF is a problem of finding collision-free paths for multiple agents on graphs and is the foundation of multi-robot coordination. LaCAM uses a two-level search to find solutions quickly, even with hundreds of agents or more. At the low-level, it searches constraints about agents' locations. At the high-level, it searches a sequence of all agents' locations, followin

The Multi-agent Path Finding (MAPF) problem consists in all agents having to move to their own destinations while avoiding collisions. In practical applications to the problem, such as for navigation in an automated warehouse, MAPF must be solved iteratively. We present here a novel approach to iterative MAPF, that we call Priority Inheritance with Backtracking (PIBT). PIBT gives a unique priority to each agent every timestep, so that all movements are prioritized. Priority inheritance, which ai

In order to confirm the reliability of a continuous-energy Monte Carlo burn-up calculation code MVP- BURN, it was applied to the burn-up benchmark problems for a high conversion LWR lattice and a BWR lattice with burnable poison rods. The results of MVP-BURN have shown good agreements with those of a deterministic code SRAC95 for burn-up changes of infinite neutron multiplication factor, conversion ratio, power distribution, and number densities of major fuel nuclides. Serious propagation of sta

An efficient approach is described for solving a protocol conversion problem by a formal method. It is assumed that protocol entities are modeled by automata and that the required services of the conversion system are known. It is shown that an adapter can be generated if and only if an adapter exists. A method for verifying the liveness of the conversion system is examined, and it is used to construct a proper converter that has desirable properties, such as bounded queues, and deadlock- and un

This study extends the recently-developed LaCAM algorithm for multi-agent pathfinding (MAPF). LaCAM is a sub-optimal search-based algorithm that uses lazy successor generation to dramatically reduce the planning effort. We present two enhancements. First, we propose its anytime version, called LaCAM*, which eventually converges to optima, provided that solution costs are accumulated transition costs. Second, we improve the successor generation to quickly obtain initial solutions. Exhaustive expe

We study the iterative refinement of path planning for multiple robots, known as multi-agent pathfinding (MAPF). Given a graph, agents, their initial locations, and destinations, a solution of MAPF is a set of paths without collisions. Iterative refinement for MAPF is desirable for three reasons: 1) optimization is intractable, 2) sub-optimal solutions can be obtained instantly, and 3) it is anytime planning, desired in online scenarios where time for deliberation is limited. Despite the high de

We propose a method to predict the dose rate distribution in a primary containment vessel of Unit 1 of the Fukushima Daiichi Nuclear Power Station (1F) using numerical calculations and measured data.

Typical Multi-agent Path Finding (MAPF) solvers assume that agents move synchronously, thus neglecting the reality gap in timing assumptions, e.g., delays caused by an imperfect execution of asynchronous moves. So far, two policies enforce a robust execution of MAPF plans taken as input: either by forcing agents to synchronize or by executing plans while preserving temporal dependencies. This paper proposes an alternative approach, called time-independent planning, which is both online and distr