In this paper, we present a novel robot achieving high-speed passive dynamic walking (PDW) using ankle inerters. Recent flat-footed biped robots have achieved energy-efficient walking using ankle elasticity. Biped robots with ankle elasticity cannot, however, easily achieve high-speed walking since they easily slip or bound during walking. To develop a biped robot achieving more various walking than conventional flat-footed robots with ankle elasticity, we have proposed a new biped robot with ankle springs and inerters at the ankles from a viewpoint of mechanical impedance. By simulation, we have shown that the flat-footed biped robot with ankle impedance achieves fast PDW using the ankle inerters. We have thus built a flat-footed passive dynamic walker with ankle springs and inerters as a robot achieving high-speed PDW. We show that our walker achieves high-speed PDW by simulations and experiments.
In this paper, a quadrupedal quasi-passive dynamic walking robot driven by a rocking motion has been investigated. Experimental results show that the robot can walk on the level ground and that a walking speed is related to a period and a phase difference of the rocking motion. Through investigation of a shape of soles, we revealed Duke has a nonholonomic constraint that is comparable to that of a kinematic model of “two-wheeled mobile robot” on its sole. As a result of analyses based on the nonlinear control theory, we conclude that the sole shape contributes to a transition of walking speed accompanying with change of the phase difference.
Human locomotion is a complex system generated by redundant actuators and its interaction with environment. Human manages the redundant body with dexterity for adapting to various environments. Analytical studies have revealed that multiple joints and muscles move simultaneously as if the motion is constraint in low-dimensional structures. These low-dimensional structures, called synergy, should reflect the human control strategy; however a methodology that can deal with an effect of synergy on neural control has not been well-established. This study, thus, proposes a composite approach of analytical and constructive study: a system model that integrates skeletal system built on dynamical simulation and synergies obtained from walking experiment is proposed and discussed. The constructed system model realized a stable walk on both level and slope conditions, and synergy similar to that obtained in human experiment could be observed. By manipulating the contribution of synergy and posture controls inherent in the system model, the model approach revealed the factors for forming average posture during locomotion and the importance of synergy tuning for adapting to slope conditions.
This paper presents novel schema for grasping very brittle objects. For the purpose, we develop robotic hand equipped with fingers filled with incompressible fluid; gel. The features of the fingers are uniform contact pressure distribution and controllability of the pressure. It is useful for controlling contact pressure such that it does not over fracture stress. The two fingers are attached on every contact area of the robotic hand, which realizes stable grasp from the viewpoint of passive form closure. We also present grasping strategies for grasping brittle and ductile objects, respectively, and their validities are shown by experiments.
This paper describes studies to understand the fundamental mechanism of the collision and fall induced human injury by using dummy in the experiment. In our dummy experiments, the dummy on the platform is collided by the other dummy and fallen on the floor. It is concluded that the injure criteria such as HIC, Nij, Ac, Dc, AIS, ISS were effected by the initial position and pose of dummy. Especially, HIC (Head Injury Criteria) decrease under the safety area with helmet in all cases of these dummy experiments, and Acs for all cases are over the threshold level. It is strongly recommended that the ISS should be decreased with consideration of elder ages.
This paper describes a method to estimate a set of body dimensions of a subject using the Microsoft Kinect sensor. Principal Component Analysis(PCA) of the AIST anthropometric database shows principal components are interpreted as scale, degree of obesity, length of the upper body, size of the thigh and size of the buttocks respectively. A few body dimensions were chosen by linear multiple regression analysis. Applying the resulting estimator to a given subject using the Kinect sensor to obtain joint positions and 5 body dimensions by analyzing depth image, we can estimate a set of body dimensions for the subject. The system is described and experimental results are shown.
This paper describes a method of measuring moving objects and estimating human behaviors in a room using only one laser range finder (LRF) installed in the room and a strip of mirror attached to a side wall close to a floor. The area of sensing is limited to a plane parallel to and just a few centimeters above the floor, thus covering the whole room with minimal invasion of privacy of a resident while reducing occlusion. The important feature of the measurement consists in processing of both distance and reflectance acquired by the LRF from the surface of the existing objects. This enables immediate distinction of clusters of objects made of different materials in the analysis of the scene cluttered with objects. The human behavior models are effectively utilized to estimate human behavior from LRF data. The experimental results validate the effectiveness of the proposed method.
This paper proposes a sensing method to evaluate the food texture which is associated to human's impression in mastication. Nursing-care jelly foods, which can be masticated by tongue, are treated. An experimental mastication model are utilized to measure the pressure distribution response of a food in the compression and the fracture. Based on the texture analysis for image, feature values of the pressure distribution are extracted. Testing known foods whose impression levels are obtained by the sensory test, the regression equation modeling the relationship between the feature values and the impression level is derived. By giving the pressure distribution of an unknown food to this model, its impression level can be estimated. Experimental results show that impression levels of three different jelly foods are appropriately estimated.
“Embodiment” plays a critical role in robots' learning, human-robot interaction, and understanding of environment for robots. The concept is also important for the research of robot audition and human auditory perception. We devised an acoustical telepresence robot, “TeleHead” that has a user-like dummy head and can be synchronized with user's head movement. We performed several psychophysical experiments to assess sound localization, delay discrimination, and auditory perceptual grouping ability in humans. The errors of the sound localization via TeleHead were less than 10[deg]. Head posture change during the discriminable delay time ranged from 10[deg] to 17[deg]. The performance of auditory perceptual grouping did not differ between conditions with and without TeleHead. In addition, we used TeleHead to divide head movement effects on perception into three factors: self-movement, sound source movement, and acoustical change. The results indicate that TeleHead can mirror the 3D motion of users with minimal latency and distortion, suggesting that it is a useful tool for measurements of human auditory perception.
International safety standard for personal care robots, which is the key for realizing human safety, will be established soon. The nucleus of this standard is functional safety, which is a new safety concept. We need the interpretation about it, the technical know-how, and a lot of resource in order to develop personal care robots based on this standard, because it is very difficult to understand it. In the present study, we have developed the safety function of Roboticbed, which combines an electric bed and an electric wheelchair, so that it could meet the international standard for functional safety. This paper reports concrete example of this study.
Robotic study has become more diverse and wide as the relation of the robot and the real world has deepened in the recent years. This paper surveys an overview of the entire aspect concerning robotic study from past till present. We show that it offers useful information to all robotic researchers who are looking for their next work theme and also to research funding agencies which are planning to distribute their resources.
All publications, 53,500 in total, on the robotic study has been extracted from three databases provided by the Institute for Scientific Information (ISI). A citation network of these databases, consisting of 34,948 nodes, has been created using the Academic Landscape Visualization Tool which was developed by the University of Tokyo Innovation Policy Research Center.
We conduct an analysis of the network on its centrality, cluster and chronological growth. It is indicated that the current robotic study is composed of four major clusters. These clusters also reveal that their growth correlates with the relation of the robot and their real world use.
We further analyze nine smaller clusters which are young in the average year, to find out their growth potential. In addition, we divide four major clusters into sub-clusters to investigate the details. As a result, we identify the robotic research fields, which are recently growing and also in which Japan is strong or weak.
In this article, an extended Kalman filter based estimation method is proposed for positional relationships between a vehicle and robots for a car transportation system using two robots. This system lifts only the two front wheels of a front wheel drive vehicle, which is commonly used and cannot move automatically, and positions it. Therefore, the system can be made more compact than previous car transportation systems using multiple robots. To control the system transporting cars, some parameters related to positional relationships between robots and a car's nonholonomic constraints are required. However, it is difficult to obtain accurate positional relationships using laser range scanners because the car's body is complexly curved and hides one robot from another.
This estimation method uses force sensors and encoders on robots instead of laser range scanners. A force based cooperative transportation control enables the system to transport cars with nonholonomic constraints without positional relationships. The positional relationships between the robots and conditions of a car's nonholonomic constraints are derived by the extended Kalman filter and a state space model relating robotic motions and positional relationships.