Nobuhiro Ito

RoboCup Rescue Robot and Simulation Leagues

The RoboCup Rescue Robot and Simulation competitions have been held since 2000. The experience gained during these competitions has increased the maturity level of the field, which allowed deployin ...

Agent Model for Dynamically Changing Plan in π-Calculus

Abstract The authors propose a new model for the agent system and a new language. First, they develop a new model to use a new language developed for describing agent plans based on 7r-calculus, called PDL (Plan Description Language). The plans described in PDL can be changed dynamically while it is executing, because 7r-calculus provides dynamically changing structures. By using this property, agents can, in executing their plans, change those plans to adapt to the environment around them. This property is very important to agents, and is called reflection. Second, the authors implement a system. In order to do so, they propose a primitive language, called PiL (Pi-calculus Language). PiL is used on a computer more easily than the mathematical notations of 7r-calculus. Finally, they show, by using this system, that their proposition is very useful in a dynamically changing environment.

RoboCup Rescue Simulation Innovation Strategy

The RoboCup rescue simulation competitions have been held since 2001. The experience gained during these competitions has supported the development of multi-agent and robotics based solution for disaster mitigation. The league consists of three distinct competitions. These competitions are the agent competition, the virtual robots competition, and the infrastructure competition. The main goal of the infrastructure competition is to increase every year the challenge and to drive the innovation of the league, while the agent and virtual robot competition are focused on developing intelligent agents and robot control systems that can cope with those challenges. This paper provides an overview on the current state-of-the-art in the league and developments and innovations planned for the future.

Formalization of Decentralized Cooperation Model for Disaster Simulation

In Disaster Simulation, multiple heterogeneous agents work together, forming a cooperative team, in a common environment to achieve a common goal. As it is difficult to achieve the expected results in dynamic environment, the current Disaster Simulations are forced to use centralized system in which the central agent is handling the communication, cooperation and coordination activities of all other agents. In centralized system, if the central agent (that is controlling the whole system) fails then the whole system could crash. Also, if we cannot skip the effect of dynamic environment in centralized system, it may result in more unwanted communication and, hence, may impair the performance of the whole system. This paper focuses on such performance bottlenecks caused by centralized model introducing a decentralized model for cooperation and its formalization. We describe how the decentralized model could be the best solution for robustness of the performance of the Disaster Simulation and we also discuss about how to formalize the group for decentralized cooperation model in dynamic environment.

Toward Formal Verification of ECU for Gasoline Direct Injection Engines

Currently, electronic control units are employed for almost all automobiles. An engine control unit (ECU), which is also called a powertrain control module, is an electronic control unit for an engine. A fault in computer software for an ECU may cause a hazardous event or a fatal accident. So, in this study, we employ a formal method to design a computer program of ECU. Specifically, we employ a formal method called I/O-automaton, and we model an ECU of a gasoline direct injection engine with a specification language based on I/O-automaton theory. We also introduce an I/O-automaton that is with regard to the correctness of the timing of engines ignition, and we discuss how to prove the correctness of the design of ECU.

An Environment for Combinatorial Experiments in a Multi-agent Simulation for Disaster Response

We present a research environment for combinatorial experiments for the RoboCupRescue Simulation, which is a platform for the study of disaster-relief strategies using multi-agent simulations. To simulate the agents in disaster-relief situations in the RoboCupRescue Simulation, it is necessary to implement a wide variety of algorithms for tasks such as such as group formation, path planning, and task allocation. Recently, we proposed a modular framework, the Agent Development Framework, that enables researchers to implement, study, and test each algorithm independently. Because the algorithms developed in this framework are mutually replaceable, it is possible to combine algorithms developed by different researchers. In this study, we further propose an experimental environment to efficiently handle the experiments of a huge number of possible combinations of the algorithms. As a demonstration, we test various combinations of the algorithms developed by the participants of RoboCup 2017 and show that there indeed exists a set of the algorithms that is superior to the original ones developed by each team.

Proposed Environment to Support Development and Experiment in RoboCupRescue Simulation

The RoboCupRescue Simulation project is a test bed for multi-agent systems research for disaster relief. However, researchers have to implement many types of algorithm and require a complicated procedure for experiments, which places a heavy burden on them. Therefore, we propose an environment that integrates an agent-development framework and an experiment-management system to support researchers.

Design of Agent Development Framework for RoboCupRescue Simulation

The RoboCup Rescue Simulation project is one of the responses to recent large-scale natural disasters. In particular, the project provides a platform for studying disaster-relief agents and simulations. The aim of the project is to contribute to soci by making our research findings available. Some of the agents contain excellent algorithms, and so it should be possible to share them among developers. However, this is hindered by the fact that the program structure of the agents is different for each team. Therefore, in this paper, we design and implement an agent-development framework that unifies the structure within the project to facilitate such technical exchange.

Assessment of BAR: Breakdown Agent Replacement Algorithm for SCRAM

In the Multi-Agent Systems, many agents work together towards achieving a defined goal. As it may be difficult for the agents to work in a dynamic environment, the current concept is trying to focus on the issues of situation where there may be cases of agent breaking down. This algorithm will distinguish and groupify the breakdown agents from the active agents. The authors are focusing on this scenario and replacement of breakdown agents by active agents by implementing the SCRAM-Scalable Collision-avoiding Role Assignment with Minimal-makespan, which has generalized to many Multi-Agent Systems specifically focusing on the collision avoidance among the agents. The authors are trying to address the impact and fate of breakdown agents, which otherwise is not yet addressed in SCRAM, through a new algorithm. This paper is designed to allow the generalization of the concept of SCRAM without any collision and disturbances even in the case of agent breakdown.

Problem Solving with Interactive-Theorem Proving - A Case Study

With the development of artificial intelligence technology over several decades, it is getting possible to find useful knowledge from an enormous amount of data. Also, it is getting possible to solve the difficult problems which cannot be solved by a human prover. Actually, a Japanese research project called Todai Robot Project tries to develop an intelligent robot that passes an entrance examination of the University of Tokyo. A case study was conducted to solve a prep schools practice test with an artificial intelligence technology called Torobo-kun. It attracted great attention because of the good results. It is interesting to clarify the kind of an entrance exam problem which can be solved with a computer-assisted theorem proving tool. In this study, we conduct a case study to solve an entrance exam of a top university with an interactive theorem proving tool. Specifically, we employ Larch Prover (LP) which is a theorem proving tool based on equational theory and we solve a Kyushu Universitys entrance exam problem of mathematics.