3,762 research outputs found
Exploring haptic interfacing with a mobile robot without visual feedback
Search and rescue scenarios are often complicated by low or no visibility conditions. The lack of visual feedback hampers orientation and causes significant stress for human rescue workers. The Guardians project [1] pioneered a group of autonomous mobile robots assisting a human rescue worker operating within close range. Trials were held with fire fighters of South Yorkshire Fire and Rescue. It became clear that the subjects by no means were prepared to give up their procedural routine and the feel of security they provide: they simply ignored instructions that contradicted their routines
Overcoming barriers and increasing independence: service robots for elderly and disabled people
This paper discusses the potential for service robots to overcome barriers and increase independence of
elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly
people and advances in technology which will make new uses possible and provides suggestions for some of these new
applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses
the complementarity of assistive service robots and personal assistance and considers the types of applications and
users for which service robots are and are not suitable
Tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi MARA terhadap mata pelajaran Bahasa Inggeris
Kajian ini dilakukan untuk mengenal pasti tahap penguasaan, sikap dan minat pelajar
Kolej Kemahiran Tinggi Mara Sri Gading terhadap Bahasa Inggeris. Kajian yang
dijalankan ini berbentuk deskriptif atau lebih dikenali sebagai kaedah tinjauan. Seramai
325 orang pelajar Diploma in Construction Technology dari Kolej Kemahiran Tinggi
Mara di daerah Batu Pahat telah dipilih sebagai sampel dalam kajian ini. Data yang
diperoleh melalui instrument soal selidik telah dianalisis untuk mendapatkan
pengukuran min, sisihan piawai, dan Pekali Korelasi Pearson untuk melihat hubungan
hasil dapatan data. Manakala, frekuensi dan peratusan digunakan bagi mengukur
penguasaan pelajar. Hasil dapatan kajian menunjukkan bahawa tahap penguasaan
Bahasa Inggeris pelajar adalah berada pada tahap sederhana manakala faktor utama yang
mempengaruhi penguasaan Bahasa Inggeris tersebut adalah minat diikuti oleh sikap.
Hasil dapatan menggunakan pekali Korelasi Pearson juga menunjukkan bahawa terdapat
hubungan yang signifikan antara sikap dengan penguasaan Bahasa Inggeris dan antara
minat dengan penguasaan Bahasa Inggeris. Kajian menunjukkan bahawa semakin positif
sikap dan minat pelajar terhadap pengajaran dan pembelajaran Bahasa Inggeris semakin
tinggi pencapaian mereka. Hasil daripada kajian ini diharapkan dapat membantu pelajar
dalam meningkatkan penguasaan Bahasa Inggeris dengan memupuk sikap positif dalam
diri serta meningkatkan minat mereka terhadap Bahasa Inggeris dengan lebih baik. Oleh
itu, diharap kajian ini dapat memberi panduan kepada pihak-pihak yang terlibat dalam
membuat kajian yang akan datang
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Mobile assistive technologies for the visually impaired
There are around 285 million visually impaired people worldwide, and around 370,000 people are registered as blind or partially sighted in the UK. Ongoing advances in information technology (IT) are increasing the scope for IT-based mobile assistive technologies to facilitate the independence, safety, and improved quality of life of the visually impaired. Research is being directed at making mobile phones and other handheld devices accessible via our haptic (touch) and audio sensory channels. We review research and innovation within the field of mobile assistive technology for the visually impaired and, in so doing, highlight the need for successful collaboration between clinical expertise, computer science, and domain users to realize fully the potential benefits of such technologies. We initially reflect on research that has been conducted to make mobile phones more accessible to people with vision loss. We then discuss innovative assistive applications designed for the visually impaired that are either delivered via mainstream devices and can be used while in motion (e.g., mobile phones) or are embedded within an environment that may be in motion (e.g., public transport) or within which the user may be in motion (e.g., smart homes)
Empowering and assisting natural human mobility: The simbiosis walker
This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staf
A multimodal smartphone interface for active perception by visually impaired
The diffuse availability of mobile devices, such as smartphones and tablets, has the potential to bring substantial benefits to the people with sensory impairments. The solution proposed in this paper is part of an ongoing effort to create an accurate obstacle and hazard detector for the visually impaired, which is embedded in a hand-held device. In particular, it presents a proof of concept for a multimodal interface to control the orientation of a smartphone's camera, while being held by a person, using a combination of vocal messages, 3D sounds and vibrations. The solution, which is to be evaluated experimentally by users, will enable further research in the area of active vision with human-in-the-loop, with potential application to mobile assistive devices for indoor navigation of visually impaired people
Sample-Efficient Training of Robotic Guide Using Human Path Prediction Network
Training a robot that engages with people is challenging, because it is
expensive to involve people in a robot training process requiring numerous data
samples. This paper proposes a human path prediction network (HPPN) and an
evolution strategy-based robot training method using virtual human movements
generated by the HPPN, which compensates for this sample inefficiency problem.
We applied the proposed method to the training of a robotic guide for visually
impaired people, which was designed to collect multimodal human response data
and reflect such data when selecting the robot's actions. We collected 1,507
real-world episodes for training the HPPN and then generated over 100,000
virtual episodes for training the robot policy. User test results indicate that
our trained robot accurately guides blindfolded participants along a goal path.
In addition, by the designed reward to pursue both guidance accuracy and human
comfort during the robot policy training process, our robot leads to improved
smoothness in human motion while maintaining the accuracy of the guidance. This
sample-efficient training method is expected to be widely applicable to all
robots and computing machinery that physically interact with humans
Detección y modelado de escaleras con sensor RGB-D para asistencia personal
La habilidad de avanzar y moverse de manera efectiva por el entorno resulta natural para la mayoría de la gente, pero no resulta fácil de realizar bajo algunas circunstancias, como es el caso de las personas con problemas visuales o cuando nos movemos en entornos especialmente complejos o desconocidos. Lo que pretendemos conseguir a largo plazo es crear un sistema portable de asistencia aumentada para ayudar a quienes se enfrentan a esas circunstancias. Para ello nos podemos ayudar de cámaras, que se integran en el asistente. En este trabajo nos hemos centrado en el módulo de detección, dejando para otros trabajos el resto de módulos, como podría ser la interfaz entre la detección y el usuario. Un sistema de guiado de personas debe mantener al sujeto que lo utiliza apartado de peligros, pero también debería ser capaz de reconocer ciertas características del entorno para interactuar con ellas. En este trabajo resolvemos la detección de uno de los recursos más comunes que una persona puede tener que utilizar a lo largo de su vida diaria: las escaleras. Encontrar escaleras es doblemente beneficioso, puesto que no sólo permite evitar posibles caídas sino que ayuda a indicar al usuario la posibilidad de alcanzar otro piso en el edificio. Para conseguir esto hemos hecho uso de un sensor RGB-D, que irá situado en el pecho del sujeto, y que permite captar de manera simultánea y sincronizada información de color y profundidad de la escena. El algoritmo usa de manera ventajosa la captación de profundidad para encontrar el suelo y así orientar la escena de la manera que aparece ante el usuario. Posteriormente hay un proceso de segmentación y clasificación de la escena de la que obtenemos aquellos segmentos que se corresponden con "suelo", "paredes", "planos horizontales" y una clase residual, de la que todos los miembros son considerados "obstáculos". A continuación, el algoritmo de detección de escaleras determina si los planos horizontales son escalones que forman una escalera y los ordena jerárquicamente. En el caso de que se haya encontrado una escalera, el algoritmo de modelado nos proporciona toda la información de utilidad para el usuario: cómo esta posicionada con respecto a él, cuántos escalones se ven y cuáles son sus medidas aproximadas. En definitiva, lo que se presenta en este trabajo es un nuevo algoritmo de ayuda a la navegación humana en entornos de interior cuya mayor contribución es un algoritmo de detección y modelado de escaleras que determina toda la información de mayor relevancia para el sujeto. Se han realizado experimentos con grabaciones de vídeo en distintos entornos, consiguiendo buenos resultados tanto en precisión como en tiempo de respuesta. Además se ha realizado una comparación de nuestros resultados con los extraídos de otras publicaciones, demostrando que no sólo se consigue una eciencia que iguala al estado de la materia sino que también se aportan una serie de mejoras. Especialmente, nuestro algoritmo es el primero capaz de obtener las dimensiones de las escaleras incluso con obstáculos obstruyendo parcialmente la vista, como puede ser gente subiendo o bajando. Como resultado de este trabajo se ha elaborado una publicación aceptada en el Second Workshop on Assitive Computer Vision and Robotics del ECCV, cuya presentación tiene lugar el 12 de Septiembre de 2014 en Zúrich, Suiza
Integration of Computer Vision and Natural Language Processing in Multimedia Robotics Application
Computer vision and natural language processing (NLP) are two active machine learning research areas. However, the integration of these two areas gives rise to a new interdisciplinary field, which is currently attracting more attention of researchers. Research has been carried out to extract the text associated with an image or a video that can assist in making computer vision effective. Moreover, researchers focus on utilizing NLP to extract the meaning of words through the use of computer vision. This concept is widely used in robotics. Although robots should observe the surroundings from different ways of interactions, natural gestures and spoken languages are the most convenient way for humans to interact with the robots. This would be possible only if the robots can understand such types of interactions. In the present paper, the proposed integrated application is utilized for guiding vision-impaired people. As vision is the most essential in the life of a human being, an alternative source that helps in guiding the blind in their movements is highly important. For this purpose, the current paper uses a smartphone with the capabilities of vision, language, and intelligence which has been attached to the blind person to capture the images of their surroundings, and it is associated with a Faster Region Convolutional Neural Network (F-RCNN) based central server to detect the objects in the image to inform the person about them and avoid obstacles in their way. These results are passed to the smartphone which produces a speech output for the guidance of the blinds
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