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检索条件"机构=International Center of Excellence in Intelligent Robotics and Automation Research"

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Low cost solution for calibration in absolute accuracy of an industrial robot for iCPS applications

Low cost solution for calibration in absolute accuracy of an...

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1st IEEE international Conference on Industrial Cyber-Physical Systems, ICPS 2018

作者： Luo, Ren C. Wang, Hao Kuo, Mong-Hsun International Center of Excellence in Intelligent Robotics and Automation Research National Taiwan University Taipei Taiwan

ISBN: (纸本)9781538665312

The development of industrial cyber-physical systems (iCPS) and its extended application, many of the functions and applications of industrial robots will require self-control improvements. Due to the need in the industry, this paper presents a calibration method to resolve the absolute accuracy of robot TCP movement in a limited workspace problem. We implement this low-cost method with camera tracking which in a much lower cost fashion than general purpose laser tracking device. We use Rectified Linear Unit (ReLU) method based on deep neural network (DNN) which can be more efficient than traditional empirical compensation method in improving the error offset calculation and calibration accuracy. In addition, the justification for selecting training data, the methods for designing DNN models and the schemes for improving DNN models are also described in details. © 2018 IEEE.

关键词： Calibration

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Online trajectory tracking based on model predictive control for Service Robot

Online trajectory tracking based on model predictive control...

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2014 IEEE international Conference on automation Science and Engineering, CASE 2014

作者： Luo, Ren C. Huang, Kai C. Alami, Rachid International Center of Excellence on Intelligent Robotics and Automation Research LAAS/CNRS Robotics and AI Group National Taiwan University Taipei Taipei Taiwan

The objective of this paper is to present an online trajectory tracking based on model predictive control for service robot. The key point of model predictive control (MPC) algorithm is to consider an on-line optimization problem so as to obtain the optimal control input sequence in a specific time period. The main characteristics of MPC are only the first element of the control sequence is implemented as the current control input in the repeated calculations. Hence, it is more suitable for time-varying systems than conventional infinite horizon control. In this paper, explicit model predictive controller is applied to a Dual-arm Service Robot (Panda Robot) developed in our NTU-iCeiRA Lab. There are six Degrees-of-freedom for each arm, which is capable of achieving desired tasks. The proposed method is able to control the movement of each axes based on the information itself to minimize the performance index that we choose. Moreover, in order to decrease the effect of jerky motion, we apply an on-line trajectory generator to obtain a smooth trajectory by the constraints of velocity and acceleration. Experimental results demonstrate that the proposed control scheme is able to increase the positioning accuracy. © 2014 IEEE.

关键词： Model predictive control

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Hybrid Eye-to-hand and Eye-in-hand visual servo system for parallel robot conveyor object tracking and fetching

Hybrid Eye-to-hand and Eye-in-hand visual servo system for p...

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作者： Luo, Ren C. Chou, Shih-Che Yang, Xin-Yi Peng, Norman International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University Taipei Taiwan Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (纸本)9781479940325

The objective of this paper is to develop conveyer object tracking and fetching system. The traditional visual servo system for parallel robot is based on Eye-to-hand method which suffers from the narrow field of view (FOV). The basic step of moving assembling is multiple objects tracking which needs broad work space and big FOV of the parallel robot. In this paper, a Hybrid Eye-to-hand and Eye-in-hand Visual Servo System for parallel robot is proposed. Via this hybrid system, the parallel robot can achieve (multiple) object tracking and fetching with priority planning we designed. The eye-to-hand visual system with low resolution camera provides the estimations of the velocities and poses of the workpieces. Also the fetching priority is planned with this system. All aforementioned information is transferred to the eye-in-hand visual servo system for further use. Once the object appeared in the FOV of eye-in-hand system in the estimated position, the high resolution camera of the system is employed to acquire the pose information of the object with high accuracy and track it frame by frame. The hybrid system is successfully demonstrated and implemented on parallel robot which not only broadens the working space of parallel robot but also achieves great efficiency and accuracy. © 2014 IEEE.

关键词： Conveyors

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Confidence Fusion Based Emotion Recognition of Multiple Persons for Human-Robot Interaction

Confidence Fusion Based Emotion Recognition of Multiple Pers...

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IEEE/RSJ international Conference on intelligent robotics and Systems

作者： Ren C. Luo Pei Hsien Lin Li Wen Chang International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University

ISBN: (纸本)9781467317375

Emotional interaction with human beings is desirable for robots. In this study, we propose an integrated system which has ability to track multiple people at the same time, to recognize their facial expressions, and to identify social atmosphere. Consequently, robots can easily recognize facial expression, emotion variations of different people, and can respond properly. In our facial expression recognition scheme, we fuse Feature Vectors based Approach (FVA) and Differential-Active Appearance Model Features based Approach (DAFA) to obtain not only apposite positions of feature points, but also more information about texture and appearance. With the obtained useful information, FVA can classify the emotions according to comparison with the distances and ratios of feature points, and DAFA can distinguish emotions from classical machine learning on a low dimensional manifold space. Furthermore, emotion recognition of multiple people at the same time is extended. Based on the proposed algorithm, multiple person emotion analysis and social atmosphere identification can be achieved, which makes the relationship between people and robots much closer. Experimental results demonstrate that the proposed algorithms can recognize facial expressions accurately and robustly. The ambient atmosphere identification system is implemented with a young Einstein robot head in our laboratory.

关键词： Alignment and Tracking of Facial Features Active Appearance Model (AAM) Differential-AAM features (DAFs) Facial Expression Recognition Human-Computer Interactions Ambient Atmosphere Identification

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On-line Adaptive control for Minimizing Slippage Error While Mobile Platform and Manipulator Operate Simultaneously for robotics Mobile Manipulation

On-line Adaptive control for Minimizing Slippage Error While...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Ren C. Luo Yueh-Shiuan Tsai International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University

ISBN: (纸本)9781479917631

Mecanum wheels can apply a flexible mobility to a mobile robot, in this paper, a mobile manipulation robot is designed with combination of a Mecanum wheeled mobile platform and a 7-degrees of freedom (DoF) robot manipulator. Due to the mechanism of Omni-directional mobility, the Mecanum wheeled robot suffers with slip errors on the free rollers, these errors may be reduced with additional sensors and appropriate feedback control. However, while the mobile platform and the manipulator operate simultaneously, the displacement of the center of gravity of the whole robot increases the complexity to the motion control. To solve this problem, we analyze and model the effect of inconsistency of slippage errors caused by the unbalance of normal force on the wheels, and propose an on-line adaption slippage model for the Mecanum vehicle to generate a better control system to reduce these errors. We proof the effectiveness by using our proposed adaption model and on-line compensation control with experiments.

关键词： Yttrium

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Dynamic face recognition system in recognizing facial expressions for service robotics

Dynamic face recognition system in recognizing facial expres...

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IEEE/ASME (AIM) international Conference on Advanced intelligent Mechatronics

作者： Ren C. Luo Pei. H. Lin Yen. C. Wu C. Y. Huang International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University Taiwan

ISBN: (纸本)9781467325752

Facial expression recognition is an essential issue in the field of human and computer interactions. The objective of this paper is to deal with the problem of failure for the feature points on face based on active appearance model (AAM) in fitting with different users. We train the fitting model for different users before recognition. A high-quality AAM alignment results rely on appropriate selections of initial positions. In our method, we apply partial AAM fitting on mouth and eyes. Therefore we could have a better alignment for facial features; as a result, it can implement for tracking real-world video and perform real-time alignment. To obtain stable partial AAM, we use multi-level optical flow to determine initial positions of facial feature models. Then we use the Eigen-faces dynamic face recognition system to recognize different users and select the trained fitting model in recognizing the facial expressions, we combine the methodology of facial expression recognition with Eigen-faces dynamic face recognition. In this paper, we have demonstrated our approach which can accurately recognize different user's facial expressions and emotional variation.

关键词： Active appearance model Face recognition Face Fitting Vectors Optical imaging

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Multi-objects recognition using unsupervised learning and classification

Multi-objects recognition using unsupervised learning and cl...

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IEEE international Symposium on Industrial Electronics (ISIE)

作者： Ren C. Luo Po-Yu Chuang Xin-Yi Yang International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University Taipei Taiwan

ISBN: (纸本)9781467351942

The objective of this paper is to develop a real-time unsupervised learning method to detect multi-objects. Variance and gradient variance, as main texture feature, are compressed based on PCA (Principal Component Analysis) to get initial classifications of clusters via K-means algorithm in the image frame. The cluster-kernel of each class, the nucleus as we defined, is figured out through shifting the sampling area in each cluster. Based on the nucleus, the policy of cell expansion as we designed is operated to merge different classes into one object which turns the work from feature level into object level. All potential objects and cells of the objects are detected and labeled in the frame. The descriptors of each object are employed as hypothesis for the next frames object-classification. Our results demonstrate that it is possible and fast to recognize multi-objects without and training model or labeled data. The process of learning could be operated with initial clustering and automatic updating with information of the new classification.

关键词： Feature extraction Clustering algorithms Principal component analysis Algorithm design and analysis Merging Unsupervised learning Image color analysis

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Real time human motion imitation of anthropomorphic dual arm robot based on Cartesian impedance control

Real time human motion imitation of anthropomorphic dual arm...

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international Workshop on Robot Sensing (ROSE)

作者： Ren C. Luo Bo-Han Shih Tsung-Wei Lin International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University Taipei Taiwan

This paper presented a real-time human motion imitation approach to control an anthropomorphic dual arm robot by human demonstration. We use the processed positions of human skeleton joints from Kinect sensor as commands directly to control the robot arms by using Cartesian impedance control to follow the human motion without solving inverse kinematics problem. In order to avoid a jerky robot arm motion, we apply an on-line trajectory generator algorithm to obtain a smooth movement trajectory by imposing the limit of velocity and acceleration. Moreover, the self-collision problem has also been considered. When the distance between two parts of body is close enough, a repulsive force will automatically generate to prevent collision. Taking the robot capability and safe issue into account, the output force is restricted to ensure that the action of robot is stable. We demonstrate the feasibility of the approach by implementing the human motion imitation system on a humanoid dual arm robot developed in our lab. The experimental results show that the system is in good practice and flexible enough to imitate various human motions.

关键词： Robot sensing systems Force Trajectory Robot kinematics Joints Collision avoidance

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Resume navigation and re-localization of an autonomous mobile robot after being kidnapped

Resume navigation and re-localization of an autonomous mobil...

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international Workshop on Robot Sensing (ROSE)

作者： Ren C. Luo Keng C. Yeh Kuan H. Huang International Center of Excellence on Intelligent Robotics and Automation Research National Taiwan University Taipei Taiwan

The kidnapped robot problem is one of the essential issues in Human Robot Interaction research fields. This work addresses the problem of the position and orientation (pose) recovery after the robot being kidnapped, based on Laser Range Finder (LRF) sensor. By now the Monte Carlo Localization (MCL) has been introduced as a useful localization method. However the computational load of MCL is extremely large and not efficient at the initial few steps, which causes the localization process to take long computation time after the robot has been kidnapped and resets the particles. This paper provides a methodology to solve it by fusing MCL with Fast Library for Approximate Nearest Neighbors (FLANN) machine learning technique. We design a feature for LRF data called Geometric Structure Feature Histogram (GSFH).The feature GSFH encodes the LRF data to use it as the descriptor in FLANN. By building the database previously and FLANN searching technique, we filter out the most impossible area and reduce the computation load of MCL. Both in simulation and real autonomous mobile robot experiments show the effectiveness of our method.

关键词： Load modeling Robots Computational efficiency Convergence

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Design and implementation of modularized 7-DOFs dual arm manipulator

Design and implementation of modularized 7-DOFs dual arm man...

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IEEE international Conference on Industrial Technology (ICIT)

作者： Ren C. Luo Zhi-Xian Liao International Center of Excellence in Intelligent Robotics and Automation Research National Taiwan University Taipei Taiwan

ISBN: (纸本)9781467380768

This paper introduces the analytical inverse kinematic solution of modularized seven DOFs redundant manipulator with offsets at shoulder and elbow or wrist, and uses the analytical solution of manipulator to achieve dual arm intuitive teaching. Furthermore, this paper verify the method of select proper joint as redundant axis which could enhance the ability of obstacle avoidance in the corresponding workspace. Intuitive teaching and playing are successfully implemented to verify the prof-of-concept.

关键词： inverse kinematic seven degree of freedom redundant manipulator offsets with shoulder and elbow offsets with shoulder and wrist dual arm intuitive teaching Modularity Obstacle avoidance Arm spiral arm offsets Elbow Wrist Intuitive Shoulder Dual Pedagogy Teaching Redundant manipulators

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