Automated Speaker Recognition for Home Service Robots Using Genetic Algorithm and Dempster–Shafer Fusion Technique

2009 ◽  
Vol 58 (9) ◽  
pp. 3058-3068 ◽  
Author(s):  
Yanmei Zhan ◽  
H. Leung ◽  
Keun-Chang Kwak ◽  
Hosub Yoon
Keyword(s):  
Genetic Algorithm ◽  
Speaker Recognition ◽  
Service Robots ◽  
Fusion Technique ◽  
Home Service

Generic Technology of Home Service Robot

2011 ◽  
Vol 121-126 ◽  
pp. 3330-3334
Author(s):  
Zhong Hai Yu
Keyword(s):  
Modular Design ◽  
Service Robots ◽  
Service Robot ◽  
Home Nursing ◽  
Paper Briefly ◽  
Home Service Robot ◽  
Home Service ◽  
Reconfigurable Robot ◽  
Research Situation ◽  
Technology Standardization

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.

scholarly journals Learning and Development of Home Service Robots’ Service Cognition Based on a Learning Mechanism

2020 ◽  
Vol 10 (2) ◽  
pp. 464
Author(s):  
Fei Lu ◽  
Min Huang ◽  
Xiaolei Li ◽  
Guohui Tian ◽  
Hao Wu ◽  
...  
Keyword(s):  
Home Environment ◽  
Smart Home ◽  
Learning Algorithm ◽  
Comfort Level ◽  
Service Robots ◽  
Context Model ◽  
Historical Experience ◽  
Intelligent Sensors ◽  
Home Service ◽  
Discrete Part

In order to improve the intelligence of home service robots and resolve their inability to develop service cognition skills in an autonomous, human-like manner, we propose a method for home service robots to learn and develop skills that allow them to perform their services appropriately in a dynamic and uncertain home environment. In a context model built with the support of intelligent sensors and Internet of Things (IoT) technology in a smart home, common-sense information about environmental comfort is recorded into the logical judgment of the robot as a reward provided by the environment. Our approach uses a reinforcement learning algorithm that helps train the robot to provide appropriate services that bring the environment to the user’s comfort level. We modified the incremental hierarchical discriminant regression (IHDR) algorithm to construct an IHDR tree from the discrete part of the data in a smart home to store the robot’s historical experience for further service cognition. Poor adaptive capacity in a changeable home environment is avoided by additional user guidance, which can be inputted after the decision is made by the IHDR tree. In the early development period, when robots make an inappropriate service decision because they lack historical experience, the user can help fix this decision. Then, the IHDR tree is updated incrementally with fixed decisions to enrich the robot’s empirical knowledge and realize the development of its autonomic cognitive ability. The experimental results show that the robot accumulates increasingly more experience over time, and this experience plays an important role in its future service cognition, similar to the process of human mental development.

Facial Expression Recognition of Home Service Robots

2013 ◽  
Vol 411-414 ◽  
pp. 1795-1800 ◽  
Author(s):  
Xiang Zhang Chen ◽  
Zhi Hao Yin ◽  
Ze Su Cai ◽  
Ding Ding Zhu
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Nearest Neighbor ◽  
Service Robots ◽  
Service Robot ◽  
K Nearest Neighbor ◽  
Nearest Neighbor Classification ◽  
Adaboost Algorithm ◽  
Home Service ◽  
Neighbor Classification

It is of great significance that a home service robot can recognize facial expressions of a human being. This thesis suggests that features of facial expressions be extracted with PCA, and facial expressions be recognized by distance-based Hashing K-nearest neighbor classification. First, Haar-like feature and AdaBoost algorithm is adopted to detect a face and preprocess the face image; then PCA is applied to extract features of the facial expression, those features will be inserted into the hash table; finally, the facial expression can be recognized by K-nearest neighbor classification algorithm. As concluded, recognition efficiency can be greatly improved after reconstructing the feature database into hash tables.

3D Elastic Deformable Object Model for Robot Manipulation Purposes

2014 ◽  
Vol 18 (3) ◽  
pp. 375-382 ◽  
Author(s):  
Khairul Salleh Mohamed Sahari ◽  
◽  
Yew Cheong Hou
Keyword(s):  
The State ◽  
Service Robots ◽  
Robotic Arm ◽  
Service Robot ◽  
Integration Scheme ◽  
Explicit Integration ◽  
Robot Manipulation ◽  
Deformable Object ◽  
Home Service ◽  
Mass Spring

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

scholarly journals A new action recognition method by distinguishing ambiguous postures

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141774948 ◽  
Author(s):  
Zhiqiang Liu ◽  
Jianqin Yin ◽  
Jinping Li ◽  
Jun Wei ◽  
Zhiquan Feng
Keyword(s):  
Action Recognition ◽  
Recognition Accuracy ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Service Robots ◽  
Bag Of Words ◽  
Recognition Method ◽  
Weighted Voting ◽  
Human Behaviors ◽  
Home Service

One of the most important aspects of promoting the intelligence of home service robots is to reliably recognize human actions and accurately understand human behaviors and intentions. In the task of action recognition, there are many common ambiguous postures, which affect the recognition accuracy. To improve the reliability of the service provided by home service robots, this article presents a method of probabilistic soft-assignment recognition scheme based on Gaussian mixture models to recognize similar actions. First, we generate a representative posture dictionary based on the standard bag-of-words model; then, a Gaussian mixture model is introduced for the similar poses. Finally, combined with the Naive Bayesian principle, the method of weighted voting is used to recognize the action. The proposed scheme is verified by recognizing four types of daily actions, and the experimental results show its effectiveness.

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