Home Service Robot Research Articles

The Indoor Scene Video Recognition Technology for Home Robots Based on Visual Attention Model Combined with Spatial Information

A model of indoor scene video recognition technology applied to home robots is proposed based on visual attention model.This model creates image features based on the feature map of visual attention model by combining with spatial information.In classification,complex details of the indoor image are avoided and spatial information of the different scenes are retained by applying these features.Moreover,a home service robot is used as experimental platform to conduct experiments.The result shows that good recognition results can be achieved by using the proposed model,and real-time video recognition are implemented on the robot.

A faster path planner using accelerated particle swarm optimization

The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.

Human typical action recognition using gray scale image of silhouette sequence

Correct recognition of human action is the basis for home service robots. Human action recognition is a research hotspot unsolved completely at present. This paper presents a new way of human action recognition. RBF (Radial Basis Function) neural networks-based methodology using silhouette as a representative descriptor of human posture to achieve daily human actions recognition is proposed. The silhouette features of an action sequence are transformed to a grayscale image after building an adaptive background model. Then the gray scale image dimension is reduced by the DCTs (Discrete Cosine Transforms) and the radial basis function neural network is employed to recognize human actions. Finally, the experimental results are provided to show the effectiveness of the proposed method.

Holography map for home robot: an object-oriented approach

The environment map plays an important role in robot service, so it should contain not only appearance information about the whole service environment, but also their profoundness. The key contribution of the paper is the presentation of a novel semantic map, namely, a holography map composed of robot, family persons, operable items, local environments, as well as locations and path sections for home service robot cognizing its surroundings and providing services. Inspired by the object-oriented approach, the holography map is divided into three hierarchies of item-room-home and in detail 13 classes of objects. The design and storage of the object-oriented holography map are described comprehensively, and construction of the map is introduced. The execution of robot service based on the object-oriented holography map is discussed briefly. Experiments on real service robot demonstrate that the object-oriented holography map is nearer to human thinking and applicable to indoor robot service tasks.

A Speech Recognizing Circuit for Home Service Robot

Due to the increased customer demand for various applications in various fields, service robots are becoming very popular. Human Robot Interaction (HRI) is very essential for the good performance of the home service robot. A robot can be controlled by many methods and here the robot is controlled by voice commands which are given orally. The robot must be able to perform various tasks such as speech source localization, source separation and classification etc. The robot must be capable to identify the source accurately. The speech recognizer and a speaker classifier are used to improve the performance of the robot. Reverberation deteriorates the quality and intelligibility of speech. This leads to the poor performance of classification systems. The noise effects can also degrade the performance of the classification systems. The channel may also have ISI. So channel must be equalized to nullify these effects. Here a new blind deconvolutive neural network is used for speech classification in the robot. Using this new method the robot can identify the commands given to it more accurately than by the existing methods.

정리정돈용 서비스 로봇 플랫폼의 구현 연구

In this paper, a Smart Home Service Robot, McBot II, which performs mess-cleanup function etc. in house, is designed much more optimally than other service robots. It is newly developed in much more practical system than McBot I which we had developed two years ago. One characteristic attribute of mobile platforms equipped with a set of dependent wheels is their omni- directionality and the ability to realize complex translational and rotational trajectories for agile navigation in door. An accurate coordination of steering angle and spinning rate of each wheel is necessary for a consistent motion. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A specialized anthropomorphic robot manipulator which can be attached to the housemaid robot McBot II, is developed in this paper. This built-in type manipulator consists of both arms with 4 DOF (Degree of Freedom) each and both hands with 3 DOF each. The robotic arm is optimally designed to satisfy both the minimum mechanical size and the maximum workspace. Minimum mass and length are required for the built-in cooperated-arms system. But that makes the workspace so small. This paper proposes optimal design method to overcome the problem by using neck joint to move the arms horizontally forward/backward and waist joint to move them vertically up/down. The robotic hand, which has two fingers and a thumb, is also optimally designed in task-based concept. Finally, the good performance of the developed McBot II is confirmed through live tests of the mess-cleanup task.

Monocular vision based 6D object localization for service robot’s intelligent grasping

Intelligent grasping is still a hard problem for home service robots. There are two major issues in the intelligent grasping, i.e. the object recognition and the pose estimation. To grasp casually placed objects, the robot needs the object’s full 6 degrees of freedom pose data. To deal with the challenges such as illumination changes, cluttered background, occlusion, etc., we propose a monocular vision based object recognition and 6D pose estimation method. The SIFT feature point matching and brute-force search algorithm is used to do a tentative object recognition. The object recognition result is then verified with the homography constraint. After passing the verification, the 6D pose estimation is obtained through the decomposition of the homography matrix and the result is refined using the Levenberg–Marquardt algorithm. We embed our pose estimation method in a tracking by detection framework to keep computing and refining the pose during the whole approaching procedure. To test our method, a robot arm of seven degrees of freedom was utilized for a group of grasping experiments. The experimental results showed that our approach successfully recognized and grasped a variety of household objects with decent accuracy.

Development of 3D Elastic Deformable Object Model for Robot Manipulation Purposes

This paper presents a mass-spring model applied in the manipulation of elastic deformable object for home service robot application. In this paper, we present a system used to fold a piece of rectangular cloth from a specific initial condition using robot. The cloth is modeled as a 3D object in a 2D quadrangular mesh based on a mass-spring system and its state is estimated using an explicit integration scheme that computes the particle position as a function of internal and external forces acting on the elastic deformable object. The state of the elastic deformable object under robot manipulation is currently tracked from the trajectory of the mass points in the mass-spring system model in a self developed simulator, which integrates a mass-spring model and a 5 DOF articulated robotic arm. To test the reliability of the model, the simulator is used to predict the best possible paths for the robotic arm to fold a rectangular cloth in two. In the test, the state of the object is derived from the model and then compared with practical experiment. Based on the test, the error is generally acceptable. Thus, this model can be used as an estimator for vision-based tracking on the state of an elastic deformable object for manipulation by home service robots.

Performance Comparison of Gender and Age Group Recognition for Human-Robot Interaction

In this paper, we focus on performance comparison of gender and age group recognition to perform robot’s application services for Human-Robot Interaction (HRI). HRI is a core technology that can naturally interact between human and robot. Among various HRI components, we concentrate audio-based techniques such as gender and age group recognition from multichannel microphones and sound board equipped with robots. For comparative purposes, we perform the performance comparison of Mel-Frequency Cepstral Coefficients (MFCC) and Linear Prediction Coding Coefficients (LPCC) in the feature extraction step, Support Vector Machine (SVM) and C4.5 Decision Tree (DT) in the classification step. Finally, we deal with the usefulness of gender and age group recognition for human-robot interaction in home service robot environments.

The ZigBee Based Wireless Sensor and Actor Network in Intelligent Space Oriented to Home Service Robot

In the study of intelligent space oriented to home service robot, an important technology is how to construct an communication network which has the characters of high reliability and easy building. In this paper, based on the characteristics of ZigBee protocol, ZigBee technology is used to construct a wireless sensor and actor network. Several intelligent services based on ZigBee wireless sensor and actor network are shown to certify the reliability of this communication network. ZigBee wireless sensor and actor network builds an information bridge for the components in the intelligent space, the spatially distributed devices are connected together seamlessly. With this network, robot can share the mass information in the intelligent space and improve its performance with “light-packs”, devices in intelligent space, such as lamp, curtain can be controlled autonomously.

家庭用ロボットの事故発生リスク低減を目的とする取り扱い方法確認対話システム

Recently, the social demands for home service robots are increasing. For the development of home robots, we must consider and reduce the risk of accidents in using the robots. In this paper, we propose a new method of the robot which can reduce the risk of accidents by itself. The robot with the proposed method acts in the following way: (1) The robot explains the user about possible risks while using the desired function, (2) The user confirms to the robot that he/she understands the warning, (3) The robot recognizes the user's understanding, and then (4) The robot provides the desired function to the user. We named this method as ``confirmation dialogue system''. We implemented a simple prototype system as an example of the confirmation dialogue system in our home robot PaPeRo, and have collected user's feedback after some experiments. Our prototype system has demonstrated the effectiveness of this method for reducing risks in home robots.

Building an Intelligent Home Space for Service Robot Based on Multi-Pattern Information Model and Wireless Sensor Networks

This paper is concerned with constructing a prototype intelligent home environment for home service robot. In this environment, multi-pattern information can be represented by some intelligent artificial marks. Light-packs service robots can provide reliable and intelligent service by interacting with the environment through the wireless sensor networks. The intelligent space consists the following main components: smart devices with intelligent artificial mark; home server that connects the smart device and maintains the information through wireless sensor network; and the service robot that perform tasks in collaboration with the environment. In this paper, the multi-pattern information model is built, the construction of wireless sensor networks is presented, the smart and agilely home service is introduced. Fi- nally, the future direction of intelligent space system is discussed.

Generic Technology of Home Service Robot

The paper briefly looks back on current research situation of home service robots. It takes a home nursing robot as example to study and discuss some key generic technologies of home service robots. It generally overviewed robot’s mobile platform technology, modular design, reconfigurable robot technique, motion control, sensor technologies, indoor robot’s navigation and localization technology indoor, intelligentization, and robot’s technology standardization. Some the measures of technology standardization of home service robots have been put forward. It has realistic signification for industrialization of home service robots.

A modular design of Bayesian networks using expert knowledge: Context-aware home service robot

Recently, demand for service robots increases, and, particularly, one for personal service robots, which requires robot intelligence, will be expected to increase more. Accordingly, studies on intelligent robots are spreading all over the world. In this situation, we attempt to realize context-awareness for home robot while previous robot research focused on image processing, control and low-level context recognition. This paper uses probabilistic modeling for service robots to provide users with high-level context-aware services required in home environment, and proposes a systematic modeling approach for modeling a number of Bayesian networks. The proposed approach supplements uncertain sensor input using Bayesian network modeling and enhances the efficiency in modeling and reasoning processes using modular design based on domain knowledge. We verify the proposed method is useful as measuring the performance of context-aware module and conducting subjective test.

스마트 홈 서비스 로봇 맥봇II의 설계에 관한 연구

본 논문에서는 스마트 홈 서비스 로봇인 맥봇II(Mess-Cleanup Robot; McBot II)를 설계한다. 그것은 맥봇I에 비하여 더욱 지능적이고 실용적인 시스템으로 개발하였다. 지금까지 진공청소기는 가사 노동의 부담을 덜어주었지만 진공청소기를 운용하는 점에서 노동의 강도는 차이가 없다. 최근에 이 문제의 해결을 위해 상용화된 청소로봇이 나왔지만 큰 시장을 형성하지는 못했다. 왜냐하면 여전히 진공청소 이전에 큰 부피의 쓰레기나 신문, 옷가지 등을 정리정돈 하지 못하는 문제를 가지고 있다. 따라서 우리는 실제 환경에서 이 문제를 해결하기 위해 더 발전된 새로운 정리정돈 로봇 맥봇II를 개발한다. 특히, 본 논문에서는 로봇의 기계적인 설계와 기본적인 제어에 초점을 맞추어 논문을 구성한다. 맥봇II는 인간이 허리 및 손을 이용하여 정리 정돈 작업을 수행하는 메커니즘을 모델로 하여 설계되어 진다. 작업 시 인간의 허리 기능은 변화 범위가 큰 수직형 리프트와 전후진이 가능한 어깨 조인트 구조로 구현한다. 정리정돈 작업을 직접 수행하는 로봇 팔과 핸드는 실용성을 위하여 최소 자유도를 갖는 시스템으로 설계한다. 또한 맥봇II가 좁은 면적의 실내에서 장애물과의 충돌을 방지하면서 고속의 이동 능력을 갖기 위하여 홀로노믹(Holonomic)특성의 이동로봇으로 설계한다. 끝으로 최적화 설계로 구현된 로봇의 몸체/이동/로봇팔/핸드의 동작 제어 실험 결과들을 통하여 맥봇 II의 향상된 성능을 확인한다. In this paper, a smart home service robot McBot II is newly developed in much more practical and intelligent system than McBot I which we had developed a few years ago. Thus far, vacuum-cleaners have lightened the burden of household chores but the operational labor that vacuum-cleaners entail has been very severe. Recently, a cleaning robot was commercialized to solve but it also was not successful because it still had the problem of mess-cleanup, which pertained to the clean-up of large trash and the arrangement of newspapers, clothes, etc. Hence, we develop a new home mess-cleanup robot McBot II to completely overcome this problem on real environments. The mechanical design and the basic control of McBot II, which performs mess-cleanup function etc. in house, is actually focused in this paper. McBot II is mechanically modeled in the same method that the human works in door by using the waist and the hands. The big-ranged vertical lift and the shoulder joints to be able to forward move are mechanically designed for the operating function as the human's waist when the robot works. The mobility of McBot II is designed in the holonomic mobile robot for the collision avoidance of obstacle and the high speed navigation on the small area in door. Finally, good performance of McBot II, which has been optimally desinged, is confirmed through the experimental results for the control of the robotic body, mobility, arms and hands in this paper.

Tiny and Blurred Face Alignment for Long Distance Face Recognition

Applying face alignment after face detection exerts a heavy influence on face recognition. Many researchers have recently investigated face alignment using databases collected from images taken at close distances and with low magnification. However, in the cases of home-service robots, captured images generally are of low resolution and low quality. Therefore, previous face alignment research, such as eye detection, is not appropriate for robot environments. The main purpose of this paper is to provide a new and effective approach in the alignment of small and blurred faces. We propose a face alignment method using the confidence value of Real-AdaBoost with a modified census transform feature. We also evaluate the face recognition system to compare the proposed face alignment module with those of other systems. Experimental results show that the proposed method has a high recognition rate, higher than face alignment methods using a manually-marked eye position.

A Deconvolutive Neural Network for Speech Classification With Applications to Home Service Robot

Reverberation deteriorates the quality and intelligibility of speech, leading to the poor performance of classification systems. Room reverberation parameters depend on the location of the speaker and the microphone and the room geometry. For mobile robots, the reverberation is constantly changing due to the relative movement of the speaker and the robot. This can affect the spectral properties of the signal and therefore, the classification accuracy. The contribution of this paper is a new network architecture, which uses neural network constant modulus algorithm (NNCMA) based equalizer followed by a multi-layer preceptron (MLP) classifier. NNCMA is an MLP which is trained with a cost function similar to constant modulus algorithm (CMA). With this two-stage structure, the classifier does not have to consider the time-varying nature of the reverberation. The proposed algorithm is applied to speech samples collected by the home service robot WEVER-R2 for speaker classification in a typical home or office environment. We use them for gender classification application. The proposed neural network was found to have 83.73% of classification accuracy for age classification and 88.91% of classification accuracy for gender classification, while the standard MLP had a classification accuracy of 71.43% and 72.29%, respectively.

퍼지 방위각 추정기를 이용한 세 개의 전 방향 바퀴 구조의 이동로봇시스템의 개발

서비스 로봇은 사람이 생활하는 환경에서 동작한다. 이런 환경에서는 일반적인 휠베이스 모빌러티(Mobility) 방식의 이동로봇은 동적인 장애물과 정적인 장애물에 둘러싸여 있으므로 로봇의 움직임에 있어 자유로운 주행에 제약을 받게 된다. 이것은 소위 비홀로노믹(Non-Holonomic) 시스템 특성으로 주행 중인 이동로봇은 장애물을 만나면 별도의 조향장치를 사용하거나 차동 휠 구조 로봇의 회전 과정을 수행한 후 이동하고자 하는 방향으로 진행할 수 있다. 이런 장애물을 신속하게 회피하려면 홀로노믹(Holonomic) 시스템 특성이 필요하다. 홀로노믹 시스템은 별다른 회전과정 없이 단순히 좌우로 이동만 하면 된다. 이러한 특성으로 민첩하게 주행할 수 있고 좁은 공간에서 비홀로노믹 로봇보다 효율적이고 자유로운 주행이 가능하다. 그러므로 본 논문에서는 세 개의 옴니휠(Omni-wheels)을 사용한 홀로노믹 이동로봇 시스템을 개발한다. 세 개의 옴니휠을 사용한 이동로봇의 동역학과 모터 비선형 운동방정식을 고려한 정밀한 비선형 동역학 모델을 유도하여 제시한다. 유도된 식을 통해 각각의 모터 속도를 계산하고. 기본 속도제어기로는 PID방식을 사용한다. 그런데, 옴니휠을 이용한 홀로노믹 이동로봇의 추적제어는 정확한 방위각 센싱 데이터와 기준값(Reference Value)을 필요로 한다. 방위각 센싱은 부정확성과 불확실성(Uncertainty)을 갖는다. 부정확성은 센서 시스템의 노이즈와 얼라이어싱(Aliasing)으로 인하여 발생하고, 불확실성은 모바일 로봇의 왜란(Disturbance)과 미끄러짐(Slip)으로 발생한다. 본 논문에서는 퍼지 논리 추론에 의한 퍼지 방위각 추정기(Estimator)를 개발하여 방위각 제어의 새로운 개념을 제시한다. 끝으로, 퍼지 방위각 추정을 이용한 세 개의 전 방향 바퀴 구조의 이동로봇이 실시간으로 제어되는 실험을 통하여 이동로봇 시스템의 성능을 분석한다. Home service robot are not working in the fixed task such as industrial robot, because they are together with human in the same indoor space, but have to do in much more flexible and various environments. Most of them are developed on the base of the wheel-base mobile robot in the same method as a vehicle robot for factory automation. In these days, for holonomic system characteristics, omni-directional wheels are used in the mobile robot. A holonomicrobot, using omni-directional wheels, is capable of driving in any direction. But trajectory control for omni-directional mobile robot is not easy. Especially, azimuth control which sensor uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A trajectory controller for an omni-directional mobile robot, which each motor is controlled by an individual PID law to follow the speed command from inverse kinematics, needs a precise sensing data of its azimuth and exact estimation of reference azimuth value. It has imprecision and uncertainty inherent to perception sensors for azimuth. In this paper, they are solved by using fuzzy logic inference which can be used straightforward to perform the control of the mobile robot by means of the fuzzy behavior-based scheme already existent in literature. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.

Edge Tracing Manipulation of Clothes Based on Different Gripper Types

Problem statement: Edge tracing is considered important for deformable object manipulation in order to spread and reveal the original shape of an object before it can be sorted. It is important in unfolding clothes to reveal its original state during sorting. Tracing in this study context involved tracing the clothes edge, with the robot arm movement based on feedback from sensors. Development of special tools for deformable object manipulation is also considered to be important as well and must consider the properties of the deformable objects. Approach: This study introduced three robotic grippers developed to handle clothes for home service robots. For each gripper, a unique tracing algorithm was developed to fully utilize the capability of the gripper in edge tracing. Results: Each developed gripper had been tested and edge tracing algorithms have been developed to suit the gripper’s capabilities. Experimental results demonstrated the uniqueness of each gripper and the effectiveness of the tracing algorithm developed. Conclusion: The results showed that the grippers are capable of tracing the edge of clothes and reveal the second corner of the clothes. Inchworm gripper is proven to be the most promising gripper for clothes manipulation.

Ubiquitous Home Service Robot by Combining Ceiling and Robot Mounted Microphone Array

Ubiquitous Home Service Robot by Combining Ceiling and Robot Mounted Microphone Array