A Smart Real-Time Standalone Route Recognition System for Visually Impaired Persons

Visual Impairment is a common disability that results in poor or no eyesight, whose victims suffer inconveniences in performing their daily tasks. Visually impaired persons require some aids to interact with their environment safely. Existing navigation systems like electronic travel aids (ETAs) are mostly cloud-based and rely heavily on the internet and google map. This implies that systems deployment in locations with poor internet facilities and poorly structured environments is not feasible. This paper proposed a smart real-time standalone route recognition system for visually impaired persons. The proposed system makes use of a pedestrian route network, an interconnection of paths and their associated route tables, for providing directions of known locations in real-time for the user. Federal University of Technology (FUT), Minna, Gidan Kwanu campus was used as the case study. The result obtained from testing of the device search strategy on the field showed that the complexity of the algorithm used in searching for paths in the pedestrian network is , at worst-case scenario, where N is the number of paths available in the network. The accuracy of path recognition is 100%. This implies that the developed system is reliable and can be used in recognizing and navigating routes by the visual impaired in real-time

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

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

Multi-sensor fusion for automated guided vehicle positioning

This thesis presents positioning system of Automated Guided Vehicles or AGV for short, which is a mobile robot that follows wire or magnetic tape in the floor to navigate from point to another in workspace. AGV serves in industrial fields to convey materials and products around the manufacturing facility or warehouse thus, time of manufacturing process and number of labors can be reduced accordingly. In contrast, the limitation of its movement specified by the guidance path considered as a main weakness. In order to make the AGV moves freely without guidance path, it is essential to know current position first before starts navigate to target place then, the position has to be updating during movement. For mobile robots positioning and path tracking, two basic techniques are usually used, relative and absolute positioning. Relative positioning techniques based on measuring travelled distance by the robot and accumulate it to its initial position to estimate current position, which lead to drift error over time. Digital compass, Global Positioning System (GPS), and landmarks based positioning are examples of absolute positioning techniques, in which robot position estimated from single reading. Absolute positioning does not have drift error but the system cost is high and has signal blockage inside buildings as in case of landmarks and GPS respectively. The developed positioning system based on odometry, accelerometer, and digital compass for path tracking. RFID landmarks installed in predefined positions and ultrasonic GPS used to eliminate drift error in position estimated from odometry and accelerometer. Radio frequency module is used to transfer sensors reading from the mobile robot to a host PC has software program written on LabVIEW, which has a positioning algorithm and graphical display for robot position. The experiments conducted have illustrated that the developed sensor fusion positioning system can be integrated with AGV to replace the ordinary guidance system. It will give AGV flexibility in task manipulation in industrial application

Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People

Facilitating navigation in pedestrian environments is critical for enabling people who are blind and visually impaired (BVI) to achieve independent mobility. A deep reinforcement learning (DRL)–based assistive guiding robot with ultrawide-bandwidth (UWB) beacons that can navigate through routes with designated waypoints was designed in this study. Typically, a simultaneous localization and mapping (SLAM) framework is used to estimate the robot pose and navigational goal; however, SLAM frameworks are vulnerable in certain dynamic environments. The proposed navigation method is a learning approach based on state-of-the-art DRL and can effectively avoid obstacles. When used with UWB beacons, the proposed strategy is suitable for environments with dynamic pedestrians. We also designed a handle device with an audio interface that enables BVI users to interact with the guiding robot through intuitive feedback. The UWB beacons were installed with an audio interface to obtain environmental information. The on-handle and on-beacon verbal feedback provides points of interests and turn-by-turn information to BVI users. BVI users were recruited in this study to conduct navigation tasks in different scenarios. A route was designed in a simulated ward to represent daily activities. In real-world situations, SLAM-based state estimation might be affected by dynamic obstacles, and the visual-based trail may suffer from occlusions from pedestrians or other obstacles. The proposed system successfully navigated through environments with dynamic pedestrians, in which systems based on existing SLAM algorithms have failed

Eu Sonar : uso de computação vestível para o auxílio a deficientes visuais

Monografia (graduação)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2016.Neste trabalho, realizamos um estudo sobre o histórico da computação vestível e propomos um novo sistema baseado no uso de sensores e micromotores, para a detecção de obstáculos e correto direcionamento de pessoas com deficiência visual. Para isso, desenvolvemos um sistema que recebe dados através de comunicação sem fio via interface bluetooth de um dispositivo móvel equipado com GPS e bússola, usado para alertar e guiar o deficiente visual a seu destino por meio de vibrações. Testes de laboratório foram realizados a fim de comprovar a eficácia do sistema proposto, bem como identificar os principais problemas que podem advir da sua implementação prática. Um protótipo plenamente funcional foi construído e testado com usuários deficientes visuais, bem como usuários não-deficientes. Os resultados obtidos demonstram que o sistema proposto é promissor e pontos de melhoria são sugeridos.In this paper, we carried out a study on the history of wearable computing and propose a new system based on the use of sensors and micromotors, for the detection of obstacles and correct guiding of people with visual impairment. For this, we developed a system that receives data through wireless communication via Bluetooth interface for a mobile device equipped with GPS and compass, used to alert and guide the visually impaired to their destination through vibrations. Laboratory tests were conducted to prove the effectiveness of the proposed system and to identify the main problems that may arise from its practical implementation. A fully functional prototype was built and tested with visually impaired users as well as non-disabled users. The results show that the proposed system is promising and points of improvement are suggested

Haptic Interaction with a Guide Robot in Zero Visibility

Search and rescue operations are often undertaken in dark and noisy environment in which rescue team must rely on haptic feedback for exploration and safe exit. However, little attention has been paid specifically to haptic sensitivity in such contexts or the possibility of enhancing communicational proficiency in the haptic mode as a life-preserving measure. The potential of root swarms for search and rescue has been shown by the Guardians project (EU, 2006-2010); however the project also showed the problem of human robot interaction in smoky (non-visibility) and noisy conditions. The REINS project (UK, 2011-2015) focused on human robot interaction in such conditions. This research is a body of work (done as a part of he REINS project) which investigates the haptic interaction of a person wit a guide robot in zero visibility. The thesis firstly reflects upon real world scenarios where people make use of the haptic sense to interact in zero visibility (such as interaction among firefighters and symbiotic relationship between visually impaired people and guide dogs). In addition, it reflects on the sensitivity and trainability of the haptic sense, to be used for the interaction. The thesis presents an analysis and evaluation of the design of a physical interface (Designed by the consortium of the REINS project) connecting the human and the robotic guide in poor visibility conditions. Finally, it lays a foundation for the design of test cases to evaluate human robot haptic interaction, taking into consideration the two aspects of the interaction, namely locomotion guidance and environmental exploration