Exploration of unknown object by active touch of robot hand

This paper proposes a method of exploring the local shape of an unknown object using the force and torque information obtained from active touch. In the first, we present a method to estimate an unknown curvature, using rolling and sliding motion with a force/torque sensor attached to the fingertip of the hand. Then, the normal curvature equation from 2D curvatures is obtained. Finally we present a reconstruction algorithm of local geometry by using a normal curvature equation, which is composed of principal curvatures and principal directions. The method is tested by using a hand-arm system consisting of an industrial robot arm and an anthropomorphic robot hand with 6-axis force/torque sensor. The feasibility of the proposed method is experimentally validated for objects with simple geometries such as cylinder, spheres etc.     

Map building method for urban gas pipelines based on landmark detection

This paper presents a map building method for an in-pipe robot to navigate inside urban gas pipelines autonomously, whose configuration is unknown or partially known. In the first, we explain the reason why the navigation in the pipeline is difficult and then, present a method for obtaining a robot’s posture by using a pipeline’s unique geometrical features. The robot can obtain its heading direction by detecting the standardized geometries of pipe elements. Based on the method, we propose a robot controller consisting of discrete and continuous controllers. The discrete controller is activated by pre-defined events and generates appropriate paths for exploration. The continuous controller receives the desired path and physically moves the robot to the desired path. The method is implemented in an in-pipe robot, called MRINSPECT-V and its effectiveness is validated.     

Development of a quadruped walking robot AiDIN-III using biologically inspired kinematic analysis

This paper presents a bio-inspired mechanism design for a quadruped walking robot. The approach is derived from the observation on the behaviors of quadruped locomotion, skeletal structure, and the study on the stability of walking based on morphological analysis. In the first, we define the design parameters such as the dimensions of the body and limbs, the center of mass position, and locomotion mechanisms based on surveys on the literatures from biologists. Then, by using the parameters, we propose an useful framework for determining the design parameters of a quadruped walking robot. For implementations, we manufacture a dog-type self-contained quadruped walking robot, named AiDIN-III (Artificial Digitigrade for Natural Environment version III) and the effectiveness of the proposed idea is validated via experimental works.     

Hybrid Simulation of Miscible Mixing with Viscous Fingering

By modeling mass transfer phenomena, we simulate solids and liquids dissolving or changing to other substances. We also deal with the very small‐scale phenomena that occur when a fluid spreads out at the interface of another fluid. We model the pressure at the interfaces between fluids with Darcy's Law and represent the viscous fingering phenomenon in which a fluid interface spreads out with a fractal‐like shape. We use hybrid grid‐based simulation and smoothed particle hydrodynamics (SPH) to simulate intermolecular diffusion and attraction using particles at a computable scale. We have produced animations showing fluids mixing and objects dissolving.     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.     

Magnetic landmark-based position correction technique for mobile robots with hall sensors

We propose a precise position error compensation and low-cost relative localization method in structured environments using magnetic landmarks and hall sensors. The proposed methodology can solve the problem of fine localization as well as global localization by tacking landmarks or by utilizing various patterns of magnetic landmark arrangement. In this paper, we consider two patterns of implanted permanent magnets on the surface, namely, at each vertex of regular triangles or rectangles on a flat surface. We show that the rectangular configuration of the permanent magnetic bars is better for a robust localization under sensor noise. For the experiments, permanent magnet sets in rectangular configuration are placed on the floor as landmarks at regular intervals, and magnetic hall sensors are installed at the bottom of a mobile robot. In our implementation, the accuracy after the error compensation is less than 1 mm in the position and less than 1° in the orientation. Due to the low cost and accuracy of the proposed methodology, it would be one of the practical solutions to the pose error correction of a mobile robot in structured environments.     

Reconstruction of surface texture based on spatial information measured with a pen-type texture sensor

Surface texture is one of the important properties for the human to identify objects by touch. Effective reconstructions of textures are necessary for realistic interactions between the human and environment via human–computer interfaces. This paper presents a systematic approach for sensing and reconstructing periodic surface textures. Three significant issues are discussed: a pen-type texture sensor that measures the spatial information based on the measurements of contact forces; an algorithm for the reconstruction of periodic textures based on the obtained spatial information; and the method of incremental scanning to identify the polar spectrum of a surface by limited number of scans. The concept of polar spectrum is introduced to describe the spatial properties of the surface, that is, the relation between spatial frequencies and the direction of measurement. The pattern of polar spectrum is used to facilitate surface reconstructions. Experimental results based on the spatial information obtained with a laser displacement sensor and the pen-type texture sensor demonstrate the effectiveness of the proposed methods for the measurement and reconstruction of periodic textures.     

H.264/AVC baseline profile to MPEG‐4 visual simple profile transcoding to reduce the spatial resolution

In this study, we propose a heterogeneous transcoding method of converting an H.264/Advanced video coding (AVC) Baseline profile (BP) video bitstream into an MPEG‐4 Visual simple profile (VSP) video bitstream. The proposed method reduces the spatial resolution for mobile terminals, which support only low resolution video bitstreams. When the H.264/AVC BP video bitstream is transformed into the MPEG‐4 VSP video bitstream, the conversions between the H.264/AVC BP block types and the MPEG‐4 VSP block types are performed by analyzing the macroblocks (MBs) conversion probability and calculating the difference values of motion vector. The proposed transcoding method runs on average 5.5 times faster than the cascaded transcoding methods, for a degradation of the PSNR (peak‐signal‐to ratio) of less than 0.5 dB. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 24–33, 2006     

An approach for pattern recognition of hand activities based on EEG and Fuzzy neural network

Electroencephalography (EEG) is another interesting bio-electrical signal to differ from EMG (Electromyography). In order to pursue its application in the control of the multi-fingered robot hand or the prosthetic hand, the pattern recognition technology of the human hand activities based on EEG should be investigated as a very important and elementary research objective at first. After discussing our research strategy about EEG applied in the control of the robot hand, the recognition model named as Fuzzy Neural Network (FNN) is set up in this paper, and then its related algorithms, such as the fundamental knowledge produced, the learning samples set, the features extracted, and the patterns recognized with the artificial neural network (ANN), are deeply discussed for achieving the classification of some basic mental tasks. In addition, the experimental research has also been done using a two-channel system of measuring EEG signal, and the result shows the new recognition model using FNN can extract not only the effective spectral features of the hand movements and the other usual accompanying mental tasks, such as blinking eyes, watching red color and listening music, so as to achieve the fundamental knowledge production and the feature extraction, but also has the good capability of the pattern recognition about the human hand activities through the fuzzy setting of the learning samples and the training of its ANN.