Ryo Kurazume

An Experimental Study of a Cooperative Positioning System

Several position identification methods are being used for mobile robots. Dead reckoning is a popular method but due to the error accumulation from wheel slippage, its reliability is low for measurement of long distances especially on uneven surfaces. Another popular method is the landmark method, which estimates current position relative to known landmarks, but the landmark methods limitation is that it cannot be used in an uncharted environment. Thus, this paper proposes a new method called “Cooperative Positioning System (CPS)” that is able to overcome these shortcomings. The main concept of CPS is to divide the robots into two groups, A and B where group A remains stationary and acts as a landmark while group B moves and then group B stops and acts as a landmark for group A. This process is repeated until the target position is reached. Compared with dead reckoning, CPS has a far lower accumulation of positioning errors, and can also work in three dimensions. Furthermore, CPS employs inherent landmarks and therefore can be used in uncharted environments unlike the landmark method. In this paper, we introduce the basic concept of CPS and its positioning principle. Next, we outline a second prototype CPS machine model (CPS-II) and discuss the method of position estimation using the variance of positioning error and weighted least squares method. Position identification experiments using the CPS-II model give a positioning accuracy of 0.12% for position and 0.32 degree for attitude after the robots traveled a distance of 21.5 m.

The Great Buddha Project: Digitally Archiving, Restoring, and Analyzing Cultural Heritage Objects

This paper presents an overview of our research project on digital preservation of cultural heritage objects and digital restoration of the original appearance of these objects. As an example of these objects, this project focuses on the preservation and restoration of the Great Buddhas. These are relatively large objects existing outdoors and providing various technical challenges. Geometric models of the great Buddhas are digitally achieved through a pipeline, consisting of acquiring data, aligning multiple range images, and merging these images. We have developed two alignment algorithms: a rapid simultaneous algorithm, based on graphics hardware, for quick data checking on site, and a parallel alignment algorithm, based on a PC cluster, for precise adjustment at the university. We have also designed a parallel voxel-based merging algorithm for connecting all aligned range images. On the geometric models created, we aligned texture images acquired from color cameras. We also developed two texture mapping methods. In an attempt to restore the original appearance of historical objects, we have synthesized several buildings and statues using scanned data and a literature survey with advice from experts.

Dual arm coordination in space free-flying robot

The control problem of multiple manipulators installed on a free-flying space robot is presented. Kinematics and dynamics are studied and the generalized Jacobian matrix is formulated for the motion control of a multiarm system. Individual and coordinated control of dual manipulators is discussed. For the coordinated operation, a new method of controlling two arms simultaneously-one arm traces a given path, while the other arm works both to keep the satellite attitude and to optimize the total operation torque of the system-is developed. By means of this control method, an interesting torque optimum behavior is observed and a practical target capture operation is exhibited by computer simulation.<<ETX>>

Multi-Part People Detection Using 2D Range Data

People detection is a key capacity for robotics systems that have to interact with humans. This paper addresses the problem of detecting people using multiple layers of 2D laser range scans. Each layer contains a classifier able to detect a particular body part such as a head, an upper body or a leg. These classifiers are learned using a supervised approach based on AdaBoost. The final person detector is composed of a probabilistic combination of the outputs from the different classifiers. Experimental results with real data demonstrate the effectiveness of our approach to detect persons in indoor environments and its ability to deal with occlusions.

Feedforward and feedback dynamic trot gait control for a quadruped walking vehicle

To realize dynamically stable walking for a quadruped walking robot, the combination of the trajectory planning of the body and leg position (feedforward control) and the adaptive control using sensory information (feedback control) is indispensable. In this paper, we propose a new body trajectory, the 3D sway compensation trajectory, for a stable trot gait; we show that this trajectory has a lower energy consumption than the conventional sway trajectory that we have proposed. Then, for the adaptive attitude control method during the 2-leg supporting phase, we consider four methods, that is, a) rotation of body along the diagonal line between supporting feet, b) translation of body along the perpendicular line between supporting feet, c) vertical swing motion of recovering legs, and d) horizontal swing motion of recovering legs; we then describe how we verify the stabilization efficiency of each method through computer simulation, stabilization experimentation, and experimenting in walking on rough terrain using the quadruped walking robot, TITAN-VIII.

Early Recognition and Prediction of Gestures

This paper is concerned with an early recognition and prediction algorithm of gestures. Early recognition is the algorithm to provide recognition results before input gestures are completed. Motion prediction is the algorithm to predict the subsequent posture of the performer by using early recognition. In addition to them, this paper considers a gesture network for improving the performance of these algorithms. The performance of the proposed algorithm was evaluated by experiments of real-time control of a humanoid by gestures

Straight legged walking of a biped robot

This paper presents a new methodology for generating a straight legged walking pattern for a biped robot utilizing up-and-down motion of an upper body. Firstly, we define two new indexes, the knee stretch index (KSI) and the knee torque index (KTI), which indicate how efficiently the knee joints are utilized. Next, up-and-down motion of the upper body is automatically planned so that these indexes are optimized and straight legged walking is realized. The basic idea of the proposed method is: i) when a large number of DOFs of motion are required for controlling the ZMP, a robot makes its body height lower; ii) when there is a extra number of DOFs of motion, the body is lifted and the knee joint is stretched. By stretching the knee joints, human-like natural walking motion is obtained. Moreover, energy efficiency is improved since required torque and energy consumption to support the body weight become small at knee joints. The effectiveness of the proposed method is demonstrated by computer simulation and experiments using a humanoid robot, HOAP-1.

Modeling of collision dynamics for space free-floating links with extended generalized inertia tensor

The authors present a basic formulation of motion dynamics of a free-floating rigid-link system to establish a basis of the collision dynamics. They propose a novel concept named extended generalized inertia tensor (Ex-GIT), which is an extended version of the GIT for ground-based arms, and discuss the virtual mass concept. By means of these concepts, they formulate the collision problem focusing on a velocity relationship just before and after the collision without sensing the impact force, but considering the momentum conservation law.<<ETX>>

3D reconstruction of a femoral shape using a parametric model and two 2D fluoroscopic images

In medical diagnostic imaging, an X-ray CT scanner or a MRI system have been widely used to examine 3D shapes or internal structures of living organisms or bones. However, these apparatuses are generally very expensive and of large size. A prior arrangement is also required before an examination, and thus, it is not suitable for an urgent fracture diagnosis in emergency treatment. This paper proposes a method to estimate a patient-specific 3D shape of a femur from only two fluoroscopic images using a parametric femoral model. Firstly, we develop a parametric femoral model by statistical analysis of a number of 3D femoral shapes created from CT images of 51 patients. Then, the pose and shape parameters of the parametric model are estimated from two 2D fluoroscopic images using a distance map constructed by the level set method. Experiments using synthesized images and fluoroscopic images of a phantom femur are successfully carried out and the usefulness of the proposed method is verified.

First-Person Animal Activity Recognition from Egocentric Videos

This paper introduces the concept of first-person animal activity recognition, the problem of recognizing activities from a view-point of an animal (e.g., a dog). Similar to first-person activity recognition scenarios where humans wear cameras, our approach estimates activities performed by an animal wearing a camera. This enables monitoring and understanding of natural animal behaviors even when there are no people around them. Its applications include automated logging of animal behaviors for medical/biology experiments, monitoring of pets, and investigation of wildlife patterns. In this paper, we construct a new dataset composed of first-person animal videos obtained by mounting a camera on each of the four pet dogs. Our new dataset consists of 10 activities containing a heavy/fair amount of ego-motion. We implemented multiple baseline approaches to recognize activities from such videos while utilizing multiple types of global/local motion features. Animal ego-actions as well as human-animal interactions are recognized with the baseline approaches, and we discuss experimental results.