Emergence of adaptive behaviors by redundant robots : Robustness to changes environment and failures

Acquiring adaptive behaviors of robots automatically is one of the most interesting topics of the evolutionary systems. In previous works, we have developed an adaptive autonomous control method for redundant robots. The QDSEGA is one of the methods that we have proposed for them. The QDSEGA is realized by combining Q-learning and GA, and it can acquire suitable behaviors by adapting a movement of a robot for a task. In this paper, we focus on the adaptability of the QDSEGA and discuss the robustness of the autonomous redundant robot that is controlled by the QDSEGA. To demonstrate the effectiveness of the QDSEGA, simulations of obstacle avoidance by a 10-link manipulator in the changeable environment and locomotion by a 12-legged robot with failures have been carried out, and as a result, adaptive behaviors for each environment and each broken body have emerged. </p

Fundamental study of fluid transfer using electro-rheological effect

Considering that there is no pump feeding an Electro-Rheological-Fluid, a new type of pump has been manufactured and fluid dynamic characteristics have been elucidated. This pump can feed the ERF by utilizing effectively the change in physical properties of the fluid by the application of voltage. The principle and configuration of this pump and the methods of theoretical analysis are described, and the influence of the voltage on the feeding characteristics was examined The dispersoidal ERF has been treated hitherto as a type of Newtonian fluid. However. experiments showed that not only the induced shear stress but also the viscosity is affected by the electric field strength and that the ERF must be treated as a pseudo-plastic flow. The method of analysis described here can be applied to design the pump differing in dimensions because the analysis gave qualitative evaluations about the flow rate and pressure difference</p

Development of a video-rate range finder using dynamic threshold method for characteristic point detection

This study develops a video-rate stereo range finding circuit to obtain the depth of objects in a scene by processing video signals (R, G, B, and brightness signals) from binocular CCD cameras. The electronic circuit implements a dynamic threshold method to decrease the affect of signal noise in characteristic point detection, where a video signal from each CCD camera is compared with multiple thresholds, shifting dynamically by feeding back the previous comparison result. Several object depth measurement experiments for simple indoor scenes show that the dynamic threshold method gives high acquisition and correct rates of depth data compared with those by a fixed threshold method for the video signals and a relative method for R, G, and B signals utilized in the authors' previous range finders

Hybrid autonomous control for heterogeneous multi-agent system

Reinforcement learning is an adaptive and flexible control method for autonomous system. In our previous works, we had proposed a reinforcement learning algorithm for redundant systems: &quot;Q-learning with dynamic structuring of exploration space based on GA (QDSEGA)&quot;, and applied it to multi-agent systems. However previous works of the QDSEGA have been restricted to homogeneous agents. In this paper, we extend our previous works of multi-agent systems, and propose a hybrid autonomous control method for heterogeneous multi-agent systems. To demonstrate the effectiveness of the proposed method, simulations of transportation task by 10 heterogeneous mobile robots have been carried out. As a result effective behaviors have been obtained. </p

A Heartbeat Classifier for Continuous Prediction Using a Wearable Device

Heartbeat monitoring may play an essential role in the early detection of cardiovascular disease. When using a traditional monitoring system, an abnormal heartbeat may not appear during a recording in a healthcare facility due to the limited time. Thus, continuous and long-term monitoring is needed. Moreover, the conventional equipment may not be portable and cannot be used at arbitrary times and locations. A wearable sensor device such as Polar H10 offers the same capability as an alternative. It has gold-standard heartbeat recording and communication ability but still lacks analytical processing of the recorded data. An automatic heartbeat classification system can play as an analyzer and is still an open problem in the development stage. This paper proposes a heartbeat classifier based on RR interval data for real-time and continuous heartbeat monitoring using the Polar H10 wearable device. Several machine learning and deep learning methods were used to train the classifier. In the training process, we also compare intra-patient and inter-patient paradigms on the original and oversampling datasets to achieve higher classification accuracy and the fastest computation speed. As a result, with a constrain in RR interval data as the feature, the random forest-based classifier implemented in the system achieved up to 99.67% for accuracy, precision, recall, and F1-score. We are also conducting experiments involving healthy people to evaluate the classifier in a real-time monitoring system

Development of a tactile sensing flexible actuator

The disadvantages of flexible artificial fingers have been improved. The finger is provided with the tactile sense by two types of sensors to detect when the finger tip touches an object and to estimate both the finger force and object size. The rigidity is enhanced by equipping the finger with a reinforcing material similar to that of human bone. A prototype robot hand with four fingers has been manufactured for experiments and mounted on an industrial articulated robot. The effectiveness of the improved robot hand finger was confirmed throughout experimental tests of grasping action</p

Analysis of electric-fluid analogy of pressure transmission through an electro-rheological-fluid in annuli

The article concerns the development of flexible robotic fingers using electro-rheological fluid (ERF) for pressure control. It describes a technique to predict the transient response of a pressure control device using ERF by an electric-flow analogy. The inertia is calculated from the theoretical equation. The resistance and additional voltage source by the ER effect are derived theoretically by assuming the flow in the electrode annuli of the pressure control device as a flow of the Bingham fluid. The capacitance is determined to compare the time-responses of pressures by the prediction based on a model with the results of a simple experiment. The predictions of transient flow, using the determined parameters of the model are in qualitatively good agreement with the experimental results</p

Path evaluation for a mobile robot based on a risk of collision

An odometry system that mobile robot uses for positioning has cumulative error because of wheels' slippage and uneven ground. It causes a risk of collision of obstacles. Therefore, we propose a path evaluation method for a mobile robot based on a risk of collision. To evaluate a robot's path, we define an evaluation value as an integral of a risk of collision along the path. To evaluate the risk of collision at each point, we use an estimated positioning error generated in the odometry system. Using the evaluation method, the robot can plan a path based on a risk of collision, not the shortest path. We also consider sensing points planning for position adjustment of the mobile robot, based on the same approach. Some examples of path evaluation results support a validity of the proposed method.</p