scholarly journals Efficient Active Sensing with Categorized Further Explorations for a Home Behavior-Monitoring Robot

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Wenwei Yu ◽  
Keigo Nakahata ◽  
Guang Hao Sun ◽  
Akio Namiki ◽  
Sayuri Suwa ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Template Matching ◽  
Mobile Robotics ◽  
The Elderly ◽  
Target Object ◽  
Target Person ◽  
Active Sensing ◽  
Robot System ◽  
Body Contour ◽  
Behavior Monitoring

Mobile robotics is a potential solution to home behavior monitoring for the elderly. For a mobile robot in the real world, there are several types of uncertainties for its perceptions, such as the ambiguity between a target object and the surrounding objects and occlusions by furniture. The problem could be more serious for a home behavior-monitoring system, which aims to accurately recognize the activity of a target person, in spite of these uncertainties. It detects irregularities and categorizes situations requiring further explorations, which strategically maximize the information needed for activity recognition while minimizing the costs. Two schemes of active sensing, based on two irregularity detections, namely, heuristic-based and template-matching-based irregularity detections, were implemented and examined for body contour-based activity recognition. Their time cost and accuracy in activity recognition were evaluated through experiments in both a controlled scenario and a home living scenario. Experiment results showed that the categorized further explorations guided the robot system to sense the target person actively. As a result, with the proposed approach, the robot system has achieved higher accuracy of activity recognition.

scholarly journals Evaluation of a Home Biomonitoring Autonomous Mobile Robot

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Enrique Dorronzoro Zubiete ◽  
Keigo Nakahata ◽  
Nevrez Imamoglu ◽  
Masashi Sekine ◽  
Guanghao Sun ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Success Rate ◽  
Activity Recognition ◽  
The Elderly ◽  
Daily Activities ◽  
Robot System ◽  
Observation Position ◽  
Series Of Experiments ◽  
Home Living ◽  
Watching Tv

Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track a subject and identify his daily living activities has been developed. However, the system has not been tested in any home living scenarios. In this study we did a series of experiments to investigate the accuracy of activity recognition of the mobile robot in a home living scenario. The daily activities tested in the evaluation experiment include watching TV and sleeping. A dataset recorded by a distributed distance-measuring sensor network was used as a reference to the activity recognition results. It was shown that the accuracy is not consistent for all the activities; that is, mobile robot could achieve a high success rate in some activities but a poor success rate in others. It was found that the observation position of the mobile robot and subject surroundings have high impact on the accuracy of the activity recognition, due to the variability of the home living daily activities and their transitional process. The possibility of improvement of recognition accuracy has been shown too.

scholarly journals Carebots

2016 ◽  
Vol 138 (09) ◽  
pp. S8-S13 ◽  
Author(s):  
Thiago Marinho ◽  
Christopher Widdowson ◽  
Amy Oetting ◽  
Arun Lakshmanan ◽  
Hang Cui ◽  
...  
Keyword(s):  
Older Adults ◽  
Multidisciplinary Approach ◽  
Human Perception ◽  
The Elderly ◽  
Comfort Level ◽  
Robot System ◽  
Perceived Safety ◽  
High Level ◽  
Future Work ◽  
Flying Robots

This article demonstrates a multidisciplinary approach that proposes to augment future caregiving by prolonged independence of older adults. The human–robot system allows the elderly to cooperate with small flying robots through an appropriate interface. ASPIRE provides a platform where high-level controllers can be designed to provide a layer of abstraction between the high-level task requests, the perceptual needs of the users, and the physical demands of the robotic platforms. With a robust framework that has the capability to account for human perception and comfort level, one can provide perceived safety for older adults, and further, add expressively that facilitates communication and interaction continuously throughout the stimulation. The proposed framework relies on an iterative process of low-level controllers design through experimental data collected from psychological trials. Future work includes the exploration of multiple carebots to cooperatively assist in caregiving tasks based on human-centered design approach.

scholarly journals Feasibility Study of Textureless Object Detection and Pose Estimation Based on a Model with 3D Edgels and Surfaces

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Kimitoshi Yamazaki ◽  
Kiyohiro Sogen ◽  
Takashi Yamamoto ◽  
Masayuki Inaba
Keyword(s):  
Object Detection ◽  
Feasibility Study ◽  
Pose Estimation ◽  
Template Matching ◽  
Input Data ◽  
Three Dimensional ◽  
Target Object ◽  
Textural Features ◽  
Two Dimensional ◽  
Home Appliances

Abstract This paper describes a method for the detection of textureless objects. Our target objects include furniture and home appliances, which have no rich textural features or characteristic shapes. Focusing on the ease of application, we define a model that represents objects in terms of three-dimensional edgels and surfaces. Object detection is performed by superimposing input data on the model. A two-stage algorithm is applied to bring out object poses. Surfaces are used to extract candidates fromthe input data, and edgels are then used to identify the pose of a target object using two-dimensional template matching. Experiments using four real furniture and home appliances were performed to show the feasibility of the proposed method.We suggest the possible applicability in occlusion and clutter conditions.

20 Human-Friendly Care Robot System for the Elderly

2006 ◽  
pp. 323-332 ◽  
Author(s):  
Dong Hyun Yoo ◽  
Hyun Seok Hong ◽  
Han Jo Kwon ◽  
Myung Jin Chung
Keyword(s):  
The Elderly ◽  
Robot System

Design and Development of a Small Stereovision Sensor Module for Small Self-Contained Autonomous Robots

2005 ◽  
Vol 17 (3) ◽  
pp. 248-254 ◽  
Author(s):  
Kei Okada ◽  
◽  
Takeshi Morishita ◽  
Marika Hayashi ◽  
Masayuki Inaba ◽  
...  
Keyword(s):  
Template Matching ◽  
Autonomous Robots ◽  
General Purpose ◽  
Image Sensors ◽  
Robot System ◽  
Visual Functions ◽  
Autonomous Behavior ◽  
Cmos Image Sensors ◽  
Sensor Module ◽  
Small Robot

We designed a small stereovision (SSV) sensor module for easily adding visual functions to a small robot and enabling their use. The SSV sensor module concept includes 1) a vision sensor module containing a camera and a visual processor and 2) connecting to a robot system through general-purpose interface. This design enables the use of visual functions as ordinary sensors such, as touch or ultra-sonic sensors, by simply connecting a general-purpose interface port such as an IO port or serial connector. We developed a prototype module with small CMOS image sensors for a mobile phone and a 16 bit microprocessor. The 30×40mm prototype is small enough to attach even to palm-top robots. Our module demonstrates image processing including binarization, color extraction and labeling, and template matching. We developed self-contained robots, including a 2DOF head robot, a humanoid robot, and a palm-top robot, and realized vision-based autonomous behavior.

A SIFT Feature-Based Template Matching Method for Detecting and Counting Objects in Life Space

2010 ◽  
Vol 36 ◽  
pp. 413-421 ◽  
Author(s):  
Hideaki Kawano ◽  
Hideaki Orii ◽  
Katsuaki Shiraishi ◽  
Hiroshi Maeda
Keyword(s):  
Template Matching ◽  
Autonomous Robots ◽  
Target Object ◽  
Main Process ◽  
Spatial Transformation ◽  
Scale Invariant ◽  
Everyday Objects ◽  
Counting Task ◽  
Feature Based ◽  
Scale Invariant Feature

Autonomous robots are at advanced stage in various fields, and they are expected to autonomously work at the scenes of nursing care or medical care in the near future. In this paper, we focus on object counting task by images. Since the number of objects is not a mere physical quantity, it is difficult for conventional phisical sensors to measure such quantity and an intelligent sensing with higher-order recognition is required to accomplish such counting task. It is often that we count the number of objects in various situations. In the case of several objects, we can recognize the number at a glance. On the other hand, in the case of a dozen of objects, the task to count the number might become troublesome. Thus, simple and easy way to enumerate the objects automatically has been expected. In this study, we propose a method to recognize the number of objects by image. In general, the target object to count varies according to user's request. In order to accept the user's various requests, the region belonging to the desired object in the image is selected as a template. Main process of the proposed method is to search and count regions which resembles the template. To achieve robustness against spatial transformation, such as translation, rotation, and scaling, scale-invariant feature transform (SIFT) is employed as a feature. To show the effectiveness, the proposed method is applied to few images containing everyday objects, e.g., binders, cans etc.

Human body contour data based activity recognition

2013 ◽  
Author(s):  
Nergui Myagmarbayar ◽  
Yoshida Yuki ◽  
Nevrez Imamoglu ◽  
Jose Gonzalez ◽  
Mihoko Otake ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Human Body ◽  
Body Contour

Research on NN-PID Motion Control Technology for a Wheeled Mobile Robot

2012 ◽  
Vol 538-541 ◽  
pp. 2636-2640
Author(s):  
Shi Zhu Feng ◽  
Ming Xu
Keyword(s):  
Mobile Robot ◽  
Motion Control ◽  
Pid Controller ◽  
Mobile Robotics ◽  
Kinematic Model ◽  
Wheeled Mobile Robot ◽  
Control Technology ◽  
Robot System

Robotics is a spiry integral technology of mechanics, electrics and cybernetics. Through systematical study of a wheeled mobile robot, The kinematic model of it is deduced. A Cerebella Model Articulation Controller (CMAC) PID controller was developed to control the motion to accomplish the realistic motions of the wheeled mobile robot system. The experimental is carried out. The results prove the algorithm is correct, and indicate that the design of CMAC-PID controller is a success. The whole research will provide a reference to the study of the mobile robotics.

scholarly journals Ambient Assisted Living: A Research on Human Activity Recognition and Vital Health Sign Monitoring using Deep Learning Approaches

2019 ◽  
Vol 8 (6S4) ◽  
pp. 531-540
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Assisted Living ◽  
Independent Living ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
Human Activity Recognition ◽  
Living Environment ◽  
Learning Approaches

The rise in life expectancy rate and dwindled birth rate in new age society has led to the phenomenon of population ageing which is being witnessed across the world from past few decades. India is also a part of this demographic transition which will have the direct impact on the societal and economic conditions of the country. In order to effectively deal with the prevailing phenomenon, stakeholders involved are coming up with the Information and Communication Technology (ICT) based ecosystem to address the needs of elderly people such as independent living, activity recognition, vital health sign monitoring, prevention from social isolation etc. Ambient Assisted Living (AAL) is one such ecosystem which is capable of providing safe and secured living environment for the elderly and disabled people. In this paper we will focus on reviewing the sensor based Human Activity Recognition (HAR) and Vital Health Sign Monitoring (VHSM) which is applicable for AAL environments. At first we generally describe the AAL environment. Next we present brief insights into sensor modalities and different deep learning architectures. Later, we survey the existing literature for HAR and VHSM based on sensor modality and deep learning approach used.

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