Tadayoshi Aoyama

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

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.

Multi-Locomotion Robotic Systems

Nowadays, multiple attention have been paid on a robot working in the human living environment, such as in the field of medical, welfare, entertainment and so on. Various types of researches are being conducted actively in a variety of fields such as artificial intelligence, cognitive engineering, sensor- technology, interfaces and motion control. In the future, it is expected to realize super high functional human-like robot by integrating technologies in various fields including these types of researches. The book represents new developments and advances in the field of bio-inspired robotics research introducing the state of the art, the idea of multi-locomotion robotic system to implement the diversity of animal motion. It covers theoretical and computational aspects of Passive Dynamic Autonomous Control (PDAC), robot motion control, multi legged walking and climbing as well as brachiation focusing concrete robot systems, components and applications. In addition, gorilla type robot systems are described as hardware of Multi-Locomotion Robotic system. It is useful for students and researchers in the field of robotics in general, bio-inspired robots, multi-modal locomotion, legged walking, motion control, and humanoid robots. Furthermore, it is also of interest for lecturers and engineers in practice building systems cooperating with humans.

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

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 × 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 projection mapping using high-frame-rate depth vision

In this paper, we report on the development of a projection mapping system that can project RGB light patterns that are enhanced for three-dimensional (3-D) scenes using a GPU-based high-frame-rate (HFR) vision system synchronized with HFR projectors. Our system can acquire 512×512 depth images in real time at 500 fps. The depth image processing is accelerated by installing a GPU board for parallel processing of a gray-code structured light method using infrared (IR) light patterns projected from an IR projector. Using the computed depth images, suitable RGB light patterns to be projected are generated in real time for enhanced application tasks. They are projected from an RGB projector as augmented information onto a 3-D scene with pixel-wise correspondence even when the 3-D scene is time-varied. Experimental results obtained from enhanced application tasks for time-varying 3-D scenes such as (1) depth-based color mapping and (2) augmented reality (AR) spirit level, confirm the efficacy of our system.

Dynamics-Based Stereo Visual Inspection Using Multidimensional Modal Analysis

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.

Locomotion selection strategy for multi-locomotion robot based on stability and efficiency

This paper shows improvement of stability and efficiency for mobility using locomotion selection strategy. First strategy is the selection of a gait relying on locomotion rewards. The locomotion reward has been proposed as an indicator for selection algorithm based on Falling Risk and the moving speed. This strategy has achieved a capability of large changes of uncertainties, such as a steep slope. Second strategy is adjustment of moving speed by the extended locomotion reward that explicitly shows the relationship between the moving speed and Falling Risk. The robot aims at the maximum moving speed without a falling, and removes small changes of uncertainties as a result. We performed an experiment in order to confirm effects of two strategies in an environment that includes a rough terrain as a small uncertainty and two steps as a large uncertainty. The robot improved the moving speed about 37.5% from the case of only using the gait selection strategy.

Real-time feature-based video mosaicing at 500 fps

We conducted high-frame-rate (HFR) video mosaicing for real-time synthesis of a panoramic image by implementing an improved feature-based video mosaicing algorithm on a field-programmable gate array (FPGA)-based high-speed vision platform. In the implementation of the mosaicing algorithm, feature point extraction was accelerated by implementing a parallel processing circuit module for Harris corner detection in the FPGA on the high-speed vision platform. Feature point correspondence matching can be executed for hundreds of selected feature points in the current frame by searching those in the previous frame in their neighbor ranges, assuming that frame-to-frame image displacement becomes considerably smaller in HFR vision. The system we developed can mosaic 512×512 images at 500 fps as a single synthesized image in real time by stitching the images based on their estimated frame-to-frame changes in displacement and orientation. The results of an experiment conducted, in which an outdoor scene was captured using a hand-held camera-head that was quickly moved by hand, verify the performance of our system.

Selection Algorithm for Locomotion Based on the Evaluation of Falling Risk

An environmentally specific type of locomotion (e.g., bipedal or quadrupedal walking) is effective only under the specified environments. However, other conditions could cause physical body constraints and decrease mobility. Despite these constraints, legged robots are desired with high overall mobility such that they can walk under various conditions. Thus, a combination of types of locomotion is needed to maximize overall mobility. We have developed a gorilla-type robot, which can switch between bipedal and quadrupedal walking. A selection technique to optimize locomotion choice would be beneficial to the robot, which will experience challenging situations when walking through complex terrains, receiving disturbances, or malfunctioning. We present a selection algorithm for locomotion (SAL) that improves overall mobility by autonomously selecting the optimal locomotion. The falling risk of each locomotion mode is evaluated with a Bayesian network to represent the robots situation. The evaluation function for the SAL determines the optimal locomotion choice based on falling risk and moving speed. In this paper, the SAL is used for two state variables of locomotion: gait (Ga-SAL) and speed (Sp-SAL). Both the simulations and experiments validated that the robot traveled efficiently in complex environments.

Analysis of Relationship between limb length and joint load in quadruped walking on the slope

An animal has a characteristic ratio of forefoot and rear legs so that its morphology can adapt to the living environment. Likewise, the structure of robot should be better fitted the locomotion in the working environment. This paper derives an optimal structure of the quadruped robot, which minimizes the sum of joint torques of the robot. Minimization of the joint torque allows to reduce the joint acceleration in walking motion, and hence to reduce energy consumption. Numerical simulation analyzed joint torques in each limb length and slope angle under walking on a slope. The optimal rate of rear leg length (RRL) is derived by the simulation as the physical structure. Our analysis suggests that the joint torque will increase as the slope angle becomes steeper in the case that the rear legs are shorter than forelegs. On the other hand, the joint torque will decrease as the slope angle is declined in the case that the forelegs are shorter than the rear legs. Experimental results validated the simulation analysis.

Optimal limb length ratio of quadruped robot minimising joint torque on slopes

This paper aims to determine an optimal structure for a quadruped robot, which will allow the robots joint torque sum to be minimised. An animals characteristic limb length ratio is a vital part of its overall morphology and the one that enables it to travel easily through its environment. For the same reason, a robots structure needs to be suitably designed for locomotion in its working environment. Joint torques are necessary to maintain the posture of the robot and to accelerate joint angles during walking motion, hence, minimisation of joint torques reduces energy consumption. We performed a numerical simulation in which we analysed the joint torques for various limb lengths and slope angles in order to determine the optimal structure of a robot walking on a slope. Our investigation determines that the optimal Ratio of Rear Leg Length RRL can be derived by the use of a simulation designed to determine the physical structure of quadruped robot. Our analysis suggests that joint torque will increase as the slope angle becomes steeper if the rear legs of the robot are shorter than its forelegs, and that joint torque will decrease as the slope angle declines if the robots forelegs are shorter than its rear legs. Finally, experimental results validated our simulation analysis.