Emergency response to the nuclear accident at the Fukushima Daiichi Nuclear Power Plants using mobile rescue robots

On March 11, 2011, a massive earthquake (magnitude 9.0) and accompanying tsunami hit the Tohoku region of eastern Japan. Since then, the Fukushima Daiichi Nuclear Power Plants have been facing a crisis due to the loss of all power that resulted from the meltdown accidents. Three buildings housing nuclear reactors were seriously damaged from hydrogen explosions, and, in one building, the nuclear reactions became out of control. It was too dangerous for humans to enter the buildings to inspect the damage because radioactive materials were also being released. In response to this crisis, it was decided that mobile rescue robots would be used to carry out surveillance missions. The mobile rescue robots needed could not be delivered to the Tokyo Electric Power Company (TEPCO) until various technical issues were resolved. Those issues involved hardware reliability, communication functions, and the ability of the robots' electronic components to withstand radiation. Additional sensors and functionality that would enable the robots to respond effectively to the crisis were also needed. Available robots were therefore retrofitted for the disaster reponse missions. First, the radiation tolerance of the electronic componenets was checked by means of gamma ray irradiation tests, which were conducted using the facilities of the Japan Atomic Energy Agency (JAEA). The commercial electronic devices used in the original robot systems operated long enough (more than 100 h at a 10% safety margin) in the assumed environment (100 mGy/h). Next, the usability of wireless communication in the target environment was assessed. Such tests were not possible in the target environment itself, so they were performed at the Hamaoka Daiichi Nuclear Power Plants, which are similar to the target environment. As previously predicted, the test results indicated that robust wireless communication would not be possible in the reactor buildings. It was therefore determined that a wired communication device would need to be installed. After TEPCO's official urgent mission proposal was received, the team mounted additional devices to facilitate the installation of a water gauge in the basement of the reactor buildings to determine flooding levels. While these preparations were taking place, prospective robot operators from TEPCO trained in a laboratory environment. Finally, one of the robots was delivered to the Fukushima Daiichi Nuclear Power Plants on June 20, 2011, where it performed a number of important missions inside the buildings. In this paper, the requirements for the exploration mission in the Fukushima Daiichi Nuclear Power Plants are presented, the implementation is discussed, and the results of the mission are reported.     

On-chip Diamond MEMS Magnetic Sensing through Multifunctionalized Magnetostrictive Thin Film

Electrically integrable, high-sensitivity, and high-reliability magnetic sensors are not yet realized at high temperatures (500 °C). In this study, an integrated on-chip single-crystal diamond (SCD) micro-electromechanical system (MEMS) magnetic transducer is demonstrated by coupling SCD with a large magnetostrictive FeGa film. The FeGa film is multifunctionalized to actuate the resonator, self-sense the external magnetic field, and electrically readout the resonance signal. The on-chip SCD MEMS transducer shows a high sensitivity of 3.2 Hz mT⁻¹ from room temperature to 500 °C and a low noise level of 9.45 nT Hz^−1/2 up to 300 °C. The minimum fluctuation of the resonance frequency is 1.9 × 10⁻⁶ at room temperature and 2.3 × 10⁻⁶ at 300 °C. An SCD MEMS resonator array with parallel electric readout is subsequently achieved, thus providing a basis for the development of magnetic image sensors. The present study facilitates the development of highly integrated on-chip MEMS resonator transducers with high performance and high thermal stability.     

Market prediction using machine learning based on social media specific features

Artificial Life and Robotics - In recent years, unspecified messages posted on social media have significantly affected the price fluctuations of online-traded products, such as stocks and virtual...     

Bounded Rationality,Group Formation and the Emergence of Trust: An Agent-Based Economic Model

Computational Economics - It is possible to model trust as an investment game, where a player in order to receive a reward or a better outcome, accepts a certain risk of defection by another...     

Revolving Vernier Mechanism Controls Size of Linear Homomultimer

A new kind of the Vernier mechanism that is able to control the size of linear assembly of DNA origami nanostructures is proposed. The mechanism is realized by mechanical design of DNA origami, which consists of a hollow cylinder and a rotatable shaft in it connected through the same scaffold. This nanostructure stacks with each other by the shape complementarity at its top and bottom surfaces of the cylinder, while the number of stacking is limited by twisting angle of the shaft. Experiments have shown that the size distribution of multimeric assembly of the origami depends on the twisting angle of the shaft; the average lengths of the multimer are decamer, hexamer, and tetramer for 0°, 10°, and 20° twist, respectively. In summary, it is possible to affect the number of polymerization by adjusting the precise shape and movability of a molecular structure.     

A biped static balance control and torque pattern learning under unknown periodic external forces

This paper addresses a biped balancing task in which an unknown external force is exerted, using the so-called ‘ankle strategy’ model. When an external force is periodic, a human adaptively maintains the balance, next learns how much force should be produced at the ankle joint from its repeatability, and finally memorized it as a motion pattern. To acquire motion patterns with balancing, we propose a control and learning method: as the control method, we adopt ground reaction force feedback to cope with an uncertain external force, while, as the learning method, we introduce a motion pattern generator that memorizes the torque pattern of the ankle joint by use of Fourier series expansion. In this learning process, the period estimation of the external force is crucial; this estimation is achieved based on local autocorrelation of joint trajectories. Computer simulations and robot experiments show effective control and learning results with respect to unknown periodic external forces.     

A study on a quantum-inspired evolutionary algorithm based on pair swap

A quantum-inspired evolutionary algorithm (QEA) is proposed as a stochastic algorithm to perform combinatorial optimization problems. The QEA is evolutionary computation that uses quantum bits and superposition states in quantum computation. Although the QEA is a coarse-grained parallel algorithm, it involves many parameters that must be adjusted manually. This paper proposes a new method, named pair swap, which exchanges each best solution information between two individuals instead of migration in the QEA. Experimental results show that our proposed method is a simpler algorithm and can find a high quality solution in the 0-1 knapsack problem. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Bottom-up pyramid cellular acceptors with three-dimensional layers

In 1997, C.R. Dyer and A. Rosenfeld introduced an acceptor on a two-dimensional pattern (or tape), called the pyramid cellular acceptor, and demonstrated that many useful recognition tasks are executed by pyramid cellular acceptors in time proportional to the logarithm of the diameter of the input. They also introduced a bottom-up pyramid cellular acceptor which is a restricted version of the pyramid cellular acceptor, and proposed some interesting open problems of the bottom-up pyramid cellular acceptors. On the other hand, we think that the study of threedimensional automata has been meaningful as the computational model of three-dimensional information processing such as computer vision, robotics, and so forth. In this paper, we investigate about bottom-up pyramid cellular acceptors with three-dimensional layers, and show their some accepting powers. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Dynamic alternation of primate response properties during trial-and-error knowledge updating

Humans and animals seek appropriate solutions to novel problems through trial-and-error (TE) actions and observation of their outcomes. Once an individual has obtained the knowledge (rule) to solve a problem, knowledge-based (KB) actions may be applied in a stereotypical manner. Solutions can thus be based on TE or KB actions. To characterize this learning process at the behavioral level, we developed a new cognitive task for a laboratory monkey (Macaca fuscata) to perform. In this task, a search array consisting of six elements of different colors was presented, one of which was the behaviorally relevant target. The target color was changed unpredictably with no instruction or signal, requiring the monkey to use a TE search strategy to find the target color. We found that once the monkey identified the relevant color by chance after a color change, correct performance increased in a step-like manner and at the same time, other response properties (reaction time and color-choice tendency) also changed discontinuously. These step-like alternations in behavioral performance may be attributed to the subject’s switching between TE and KB search strategies in the two phases. The present study has therefore provided behavioral evidence for the timing and manner of switching between search strategies during the process of updating knowledge.