181 research outputs found
On power line positioning systems
Power line infrastructure is available almost everywhere. Positioning systems aim to estimate where a device or target is. Consequently, there may be an opportunity to use power lines for positioning purposes. This survey article reports the different efforts, working principles, and possibilities for implementing positioning systems relying on power line infrastructure for power line positioning systems (PLPS). Since Power Line Communication (PLC) systems of different characteristics have been deployed to provide communication services using the existing mains, we also address how PLC systems may be employed to build positioning systems. Although some efforts exist, PLPS are still prospective and thus open to research and development, and we try to indicate the possible directions and potential applications for PLPS.European Commissio
Recommended from our members
Bio-inspired soft robotic systems: Exploiting environmental interactions using embodied mechanics and sensory coordination
Despite the widespread development of highly intelligent robotic systems exhibiting great precision, reliability, and dexterity, robots remain incapable of performing basic manipulation tasks that humans take for granted. Manipulation in unstructured environments continues to be acknowledged as a significant challenge. Soft robotics, the use of less rigid materials in robots, has been proposed as one means of addressing these limitations. The technique enables more compliant interactions with the environment, allowing for increasingly adaptive behaviours better suited to more human-centric applications.
Embodied intelligence is a biologically inspired concept in which intelligence is a function of the entire system, not only the controller or `brain'. This thesis focuses on the use of embodied intelligence for the development of soft robots, with a particular focus on how it can aid both perception and adaptability. Two main hypotheses are raised: first, that the mechanical design and fabrication of soft-rigid hybrid robots can enable increasingly environmentally adaptive behaviours, and second, that sensing materials and morphology can provide intelligence that assists perception through embodiment. A number of approaches and frameworks for the design and development of embodied systems are presented that address these hypotheses.
It is shown how embodiment in soft sensor morphology can be used to perform localised processing and thereby distribute the intelligence over the body of a system. Specifically in soft robots, sensor morphology utilises the directional deformations created by interactions with the environment to aid in perception. Building on and formalising these ideas, a number of morphology-based frameworks are proposed for detecting different stimuli.
The multifaceted role of materials in soft robots is demonstrated through the development of materials capable of both sensing and changes in material property. Such materials provide additional functionality beyond their integral scaffolding and static mechanical characteristics. In particular, an integrated material has been created exhibiting both sensing capabilities and also variable stiffness and `tackâ force, thereby enabling complex single-point grasping.
To maximise the intelligence that can be gained through embodiment, a design approach to soft robots, `soft-rigid hybrid' design is introduced. This approach exploits passive behaviours and body dynamics to provide environmentally adaptive behaviours and sensing. It is leveraged by multi-material 3D printing techniques and novel approaches and frameworks for designing mechanical structures.
The findings in this thesis demonstrate that an embodied approach to soft robotics provides capabilities and behaviours that are not currently otherwise achievable. Utilising the concept of `embodiment' results in softer robots with an embodied intelligence that aids perception and adaptive behaviours, and has the potential to bring the physical abilities of robots one step closer to those of animals and humans.EPSR
Non-Contact Sleep Monitoring
"The road ahead for preventive medicine seems clear. It is the delivery
of high quality, personalised (as opposed to depersonalised) comprehensive
medical care to all." Burney, Steiger, and Georges (1964)
This world's population is ageing, and this is set to intensify over the next forty years.
This demographic shift will result in signicant economic and societal burdens (partic-
ularly on healthcare systems). The instantiation of a proactive, preventative approach
to delivering healthcare is long recognised, yet is still proving challenging. Recent work
has focussed on enabling older adults to age in place in their own homes. This may
be realised through the recent technological advancements of aordable healthcare sen-
sors and systems which continuously support independent living, particularly through
longitudinally monitoring deviations in behavioural and health metrics. Overall health
status is contingent on multiple factors including, but not limited to, physical health,
mental health, and social and emotional wellbeing; sleep is implicitly linked to each of
these factors.
This thesis focusses on the investigation and development of an unobtrusive sleep mon-
itoring system, particularly suited towards long-term placement in the homes of older
adults. The Under Mattress Bed Sensor (UMBS) is an unobstrusive, pressure sensing
grid designed to infer bed times and bed exits, and also for the detection of development
of bedsores. This work extends the capacity of this sensor. Specically, the novel contri-
butions contained within this thesis focus on an in-depth review of the state-of-the-art
advances in sleep monitoring, and the development and validation of algorithms which
extract and quantify UMBS-derived sleep metrics.
Preliminary experimental and community deployments investigated the suitability of the
sensor for long-term monitoring. Rigorous experimental development rened algorithms
which extract respiration rate as well as motion metrics which outperform traditional
forms of ambulatory sleep monitoring. Spatial, temporal, statistical and spatiotemporal
features were derived from UMBS data as a means of describing movement during sleep.
These features were compared across experimental, domestic and clinical data sets, and
across multiple sleeping episodes. Lastly, the optimal classier (built using a combina-
tion of the UMBS-derived features) was shown to infer sleep/wake state accurately and
reliably across both younger and older cohorts.
Through long-term deployment, it is envisaged that the UMBS-derived features (in-
cluding spatial, temporal, statistical and spatiotemporal features, respiration rate, and
sleep/wake state) may be used to provide unobtrusive, continuous insights into over-
all health status, the progression of the symptoms of chronic conditions, and allow the
objective measurement of daily (sleep/wake) patterns and routines
Hand Gesture and Activity Recognition in Assisted Living Through Wearable Sensing and Computing
With the growth of the elderly population, more seniors live alone as sole occupants of a private dwelling than any other population groups. Helping them to live a better life is very important and has great societal benefits. Assisted living systems can provide support to elderly people in their houses or apartments. Since automated recognition of human gestures and activities is indispensable for human-robot interaction (HRI) in assisted living systems, this dissertation focuses on developing a theoretical framework for human gesture, daily activity recognition and anomaly detection. First, we introduce two prototypes of wearable sensors for motion data collection used in this project. Second, gesture recognition algorithms are developed to recognize explicit human intention. Third, body activity recognition algorithms are presented with different sensor setups. Fourth, complex daily activities, which consist of body activities and hand gestures simultaneously, are recognized using a dynamic Bayesian network (DBN). Fifth, a coherent anomaly detection framework is built to detect four types of abnormal behaviors in human's daily life. Our work can be extended in several directions in the future.School of Electrical & Computer Engineerin
Master of Science
thesisGait analysis is an important tool for diagnosing a wide variety of disorders, with its increasingly accepted benefits culminating in the widespread adoption of motion analysis laboratories. A modern analysis laboratory consists of a multicamera marker tracking system for 3D reconstruction of kinematics and multiple high-fidelity load transducers to determine ground reaction force and enable inverse-dynamics for biomechanics. There is a need for an alternative motion analysis system which does not require a fixed laboratory setting and is lower in cost; freeing the motion capture from the laboratory and reducing the technology costs would enable long-term, home-based, natural monitoring of subjects. This thesis describes two contributions to the end goal of an inexpensive, mobile, insole-based motion analysis laboratory. First is the application of an inertialmeasurement-unit calibration routine and zero-velocity-update algorithm to improve position and orientation tracking. Second is the development, from basic sensor to prototype, of an insole capable of measuring 3 degree-of-freedom ground reaction force. These contributions represent a proof-of-concept that quantitative gait analysis, complete with dynamics, is possible with an insole-based system
A non-holonomic, highly human-in-the-loop compatible, assistive mobile robotic platform guidance navigation and control strategy
The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal.
Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic.
This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments
Exploring the Use of Wearables to Enable Indoor Navigation for Blind Users
One of the challenges that people with visual impairments (VI) have to have to confront daily, is navigating independently through foreign or unfamiliar spaces.Navigating through unfamiliar spaces without assistance is very time consuming and leads to lower mobility. Especially in the case of indoor environments where the use of GPS is impossible, this task becomes even harder.However, advancements in mobile and wearable computing pave the path to new cheap assistive technologies that can make the lives of people with VI easier.Wearable devices have great potential for assistive applications for users who are blind as they typically feature a camera and support hands and eye free interaction. Smart watches and heads up displays (HUDs), in combination with smartphones, can provide a basis for development of advanced algorithms, capable of providing inexpensive solutions for navigation in indoor spaces. New interfaces are also introduced making the interaction between users who are blind and mo-bile devices more intuitive.This work presents a set of new systems and technologies created to help users with VI navigate indoor environments. The first system presented is an indoor navigation system for people with VI that operates by using sensors found in mo-bile devices and virtual maps of the environment. The second system presented helps users navigate large open spaces with minimum veering. Next a study is conducted to determine the accuracy of pedometry based on different body placements of the accelerometer sensors. Finally, a gesture detection system is introduced that helps communication between the user and mobile devices by using sensors in wearable devices
Artificial Intelligence and Ambient Intelligence
This book includes a series of scientific papers published in the Special Issue on Artificial Intelligence and Ambient Intelligence at the journal Electronics MDPI. The book starts with an opinion paper on âRelations between Electronics, Artificial Intelligence and Information Society through Information Society Rulesâ, presenting relations between information society, electronics and artificial intelligence mainly through twenty-four IS laws. After that, the book continues with a series of technical papers that present applications of Artificial Intelligence and Ambient Intelligence in a variety of fields including affective computing, privacy and security in smart environments, and robotics. More specifically, the first part presents usage of Artificial Intelligence (AI) methods in combination with wearable devices (e.g., smartphones and wristbands) for recognizing human psychological states (e.g., emotions and cognitive load). The second part presents usage of AI methods in combination with laser sensors or Wi-Fi signals for improving security in smart buildings by identifying and counting the number of visitors. The last part presents usage of AI methods in robotics for improving robotsâ ability for object gripping manipulation and perception. The language of the book is rather technical, thus the intended audience are scientists and researchers who have at least some basic knowledge in computer science
- âŠ