There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Open Dynamics Engine を用いたスノーボードロボットシミュレータの開発

In this paper, the use of the combined deterministic-stochastic subspace identification algorithm for the experimental modal analysis of mechanical structures is discussed. The algorithm requires artificial forces to be applied to the structure, so it can be used for experimental modal analysis (EMA). The algorithm can also be used for operational modal analysis (OMA), since the excitation level of the artificial force(s) can be low compared to the excitation level of the ambient forces. Both the modes that are artificially excited and those that are excited by the ambient forces are identified. This type of operational modal analysis is called an OMAX analysis (Operational Modal Analysis with eXogenous inputs) [1]. The main advantages of OMAX over OMA are that the modes that are excited by the artificial forces can be scaled to unity modal mass and that a higher number of modes can be identified.

Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis

A survey on image mosaicing techniques

Dynamic projection mapping for moving objects has attracted much attention in recent years. However, conventional approaches have faced some issues, such as the target objects being limited to rigid objects, and the limited moving speed of the targets. In this paper, we focus on dynamic projection mapping onto rapidly deforming non-rigid surfaces with a speed sufficiently high that a human does not perceive any misalignment between the target object and the projected images. In order to achieve such projection mapping, we need a high-speed technique for tracking non-rigid surfaces, which is still a challenging problem in the field of computer vision. We propose the Deformable Dot Cluster Marker (DDCM), a novel fiducial marker for high-speed tracking of non-rigid surfaces using a high-frame-rate camera. The DDCM has three performance advantages. First, it can be detected even when it is strongly deformed. Second, it realizes robust tracking even in the presence of external and self occlusions. Third, it allows millisecond-order computational speed. Using DDCM and a high-speed projector, we realized dynamic projection mapping onto a deformed sheet of paper and a T-shirt with a speed sufficiently high that the projected images appeared to be printed on the objects.

Dynamic Projection Mapping onto Deforming Non-Rigid Surface Using Deformable Dot Cluster Marker

This paper proposes a 3-D biped dynamic walking algorithm based on passive dynamic autonomous control (PDAC). The robot dynamics is modeled as an autonomous system of a 3-D inverted pendulum by applying the PDAC concept that is based on the assumption of point contact of the robot foot and the virtual constraint as to robot joints. Due to autonomy, there are two conservative quantities named ldquoPDAC constant,rdquo which determine the velocity and direction of the biped walking. We also propose the convergence algorithm to make PDAC constants converge to arbitrary values, so that walking velocity and direction are controllable. Finally, experimental results validate the performance and the energy efficiency of the proposed algorithm.

/pdf/stabilizing-and-direction-control-of-efficient-3-d-biped-5asa6aeed9.pdf

Stabilizing and Direction Control of Efficient 3-D Biped Walking Based on PDAC

Multi-Locomotion Robotic Systems

This paper proposes a novel concept for simultaneous cell shape and motion analysis in fast microchannel flows by implementing a multiobject feature extraction algorithm on a frame-straddling high-speed vision platform. The system can synchronize two camera inputs with the same view with only a tiny time delay on the sub-microsecond timescale. Real-time video processing is performed in hardware logic by extracting the moment features of multiple cells in 512 $\,\times\,$ 256 images at 4000 fps for the two camera inputs and their frame-straddling time can be adjusted from 0 to 0.25 ms in 9.9 ns steps. By setting the frame-straddling time in a certain range to avoid large image displacements between the two camera inputs, our frame-straddling high-speed vision platform can perform simultaneous shape and motion analysis of cells in fast microchannel flows of 1 m/s or greater. The results of real-time experiments conducted to analyze the deformabilities and velocities of sea urchin egg cells fast-flowing in microchannels verify the efficacy of our vision-based cell analysis system.

Simultaneous Vision-Based Shape and Motion Analysis of Cells Fast-Flowing in a Microchannel

This paper proposes the concept of multidirectional-modal-parameter-based visual inspection with high-frame-rate (HFR) stereo video analysis as a novel active sensing methodology for determining the dynamic properties of a vibrating object. HFR stereo video is used for observing the 3-D vibration distribution of an object under unknown excitations in the audio-frequency range, and the projections of the vibration displacement vectors along multiple directions can be verified using output-only modal analysis that can estimate their modal parameters such as resonant frequencies and mode shapes. Through implementing a fast output-only modal parameter estimation algorithm on a 10000-fps stereo vision platform, we developed a real-time multidirectional-modal-parameter-based visual inspection system; it can measure the 3-D vibration displacement vectors of 30 points on a beam-shaped object from 512 × 96 pixel stereo images at 10000 fps and can determine its resonant frequencies and mode shapes along 72 different directions around its beam axis as its input-invariant modal parameters. To demonstrate the performance of our system in modal-parameter-based visual inspection, the asymmetric dynamic properties, caused by cracks, of several steel beams vibrating at dozens of hertz and having artificial cracks were inspected in real time by determining the modal parameters along 72 directions around their beam axes.

Dynamics-Based Stereo Visual Inspection Using Multidimensional Modal Analysis

This study proposes a concept for multithread active vision sensing that can measure dynamically changing displacement and vibration at multiple points on civil engineering structures. In multithread active vision sensing, a high-speed camera can function virtually as multiple tracking cameras by accelerating its measurement, computation, and actuation with ultrafast viewpoint switching at millisecond level. This enables simultaneous measurement of small vibrations distributed across a wide range, which cannot be observed using a single camera system, because its pixel accuracy is generally incompatible with its wide angle of view. We developed a galvanomirror-based high-speed multithread active vision system that can switch 500 different views in a second; it functioned as 15 virtual cameras each operating at 33.3 fps to observe multiple scenes in completely different views. The experimental results for a 4-m-long truss-structure bridge model to which 15 markers were attached show that a single active vision system can observe the deformation of the bridge structure and estimate modal parameters, such as resonant frequencies and mode shapes, at a frequency on the order of dozens of hertz.

Tadayoshi Aoyama

Papers

Stabilizing and Direction Control of Efficient 3-D Biped Walking Based on PDAC

Multi-Locomotion Robotic Systems

Simultaneous Vision-Based Shape and Motion Analysis of Cells Fast-Flowing in a Microchannel

Dynamics-Based Stereo Visual Inspection Using Multidimensional Modal Analysis

Vibration Sensing of a Bridge Model Using a Multithread Active Vision System