88 research outputs found
Climbing and Walking Robots
Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study
WEHST: Wearable Engine for Human-Mediated Telepresence
This dissertation reports on the industrial design of a wearable computational device created to enable better emergency medical intervention for situations where electronic remote assistance is necessary. The design created for this doctoral project, which assists practices by paramedics with mandates for search-and-rescue (SAR) in hazardous environments, contributes to the field of human-mediated teleparamedicine (HMTPM). Ethnographic and industrial design aspects of this research considered the intricate relationships at play in search-and-rescue operations, which lead to the design of the system created for this project known as WEHST: Wearable Engine for Human-Mediated Telepresence. Three case studies of different teams were carried out, each focusing on making improvements to the practices of teams of paramedics and search-and-rescue technicians who use combinations of ambulance, airplane, and helicopter transport in specific chemical, biological, radioactive, nuclear and explosive (CBRNE) scenarios. The three paramedicine groups included are the Canadian Air Force 442 Rescue Squadron, Nelson Search and Rescue, and the British Columbia Ambulance Service Infant Transport Team. Data was gathered over a seven-year period through a variety of methods including observation, interviews, examination of documents, and industrial design. The data collected included physiological, social, technical, and ecological information about the rescuers. Actor-network theory guided the research design, data analysis, and design synthesis. All of this leads to the creation of the WEHST system. As identified, the WEHST design created in this dissertation project addresses the difficulty case-study participants found in using their radios in hazardous settings. As the research identified, a means of controlling these radios without depending on hands, voice, or speech would greatly improve communication, as would wearing sensors and other computing resources better linking operators, radios, and environments. WEHST responds to this need. WEHST is an instance of industrial design for a wearable “engine” for human-situated telepresence that includes eight interoperable families of wearable electronic modules and accompanying textiles. These make up a platform technology for modular, scalable and adaptable toolsets for field practice, pedagogy, or research. This document details the considerations that went into the creation of the WEHST design
Machine Performers: Agents in a Multiple Ontological State
In this thesis, the author explores and develops new attributes for machine
performers and merges the trans-disciplinary fields of the performing arts and artificial
intelligence. The main aim is to redefine the term “embodiment” for robots on the
stage and to demonstrate that this term requires broadening in various fields of
research. This redefining has required a multifaceted theoretical analysis of
embodiment in the field of artificial intelligence (e.g. the uncanny valley), as well as
the construction of new robots for the stage by the author. It is hoped that these
practical experimental examples will generate more research by others in similar
fields.
Even though the historical lineage of robotics is engraved with theatrical
strategies and dramaturgy, further application of constructive principles from the
performing arts and evidence from psychology and neurology can shift the perception
of robotic agents both on stage and in other cultural environments. In this light, the
relation between representation, movement and behaviour of bodies has been further
explored to establish links between constructed bodies (as in artificial intelligence)
and perceived bodies (as performers on the theatrical stage). In the course of this
research, several practical works have been designed and built, and subsequently
presented to live audiences and research communities. Audience reactions have been
analysed with surveys and discussions. Interviews have also been conducted with
choreographers, curators and scientists about the value of machine performers.
The main conclusions from this study are that fakery and mystification can be
used as persuasive elements to enhance agency. Morphologies can also be applied that
tightly couple brain and sensorimotor actions and lead to a stronger stage presence. In
fact, if this lack of presence is left out of human replicants, it causes an “uncanny”
lack of agency. Furthermore, the addition of stage presence leads to stronger
identification from audiences, even for bodies dissimilar to their own. The author
demonstrates that audience reactions are enhanced by building these effects into
machine body structures: rather than identification through mimicry, this causes them
to have more unambiguously biological associations. Alongside these traits,
atmospheres such as those created by a cast of machine performers tend to cause even
more intensely visceral responses.
In this thesis, “embodiment” has emerged as a paradigm shift – as well as
within this shift – and morphological computing has been explored as a method to
deepen this visceral immersion. Therefore, this dissertation considers and builds
machine performers as “true” performers for the stage, rather than mere objects with
an aura. Their singular and customized embodiment can enable the development of
non-anthropocentric performances that encompass the abstract and conceptual patterns
in motion and generate – as from human performers – empathy, identification and
experiential reactions in live audiences
Using MapReduce Streaming for Distributed Life Simulation on the Cloud
Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp
Reconstruction and recognition of confusable models using three-dimensional perception
Perception is one of the key topics in robotics research. It is about the processing
of external sensor data and its interpretation. The necessity of fully autonomous
robots makes it crucial to help them to perform tasks more reliably, flexibly, and
efficiently. As these platforms obtain more refined manipulation capabilities, they
also require expressive and comprehensive environment models: for manipulation
and affordance purposes, their models have to involve each one of the objects
present in the world, coincidentally with their location, pose, shape and other aspects.
The aim of this dissertation is to provide a solution to several of these challenges
that arise when meeting the object grasping problem, with the aim of improving
the autonomy of the mobile manipulator robot MANFRED-2. By the analysis
and interpretation of 3D perception, this thesis covers in the first place the
localization of supporting planes in the scenario. As the environment will contain
many other things apart from the planar surface, the problem within cluttered
scenarios has been solved by means of Differential Evolution, which is a particlebased
evolutionary algorithm that evolves in time to the solution that yields the
cost function lowest value.
Since the final purpose of this thesis is to provide with valuable information for
grasping applications, a complete model reconstructor has been developed. The
proposed method holdsmany features such as robustness against abrupt rotations,
multi-dimensional optimization, feature extensibility, compatible with other scan
matching techniques, management of uncertain information and an initialization
process to reduce convergence timings. It has been designed using a evolutionarybased
scan matching optimizer that takes into account surface features of the object,
global form and also texture and color information.
The last tackled challenge regards the recognition problem. In order to procure
with worthy information about the environment to the robot, a meta classifier that discerns efficiently the observed objects has been implemented. It is capable
of distinguishing between confusable objects, such as mugs or dishes with similar
shapes but different size or color.
The contributions presented in this thesis have been fully implemented and
empirically evaluated in the platform. A continuous grasping pipeline covering
from perception to grasp planning including visual object recognition for confusable
objects has been developed. For that purpose, an indoor environment with
several objects on a table is presented in the nearby of the robot. Items are recognized
from a database and, if one is chosen, the robot will calculate how to grasp
it taking into account the kinematic restrictions associated to the anthropomorphic
hand and the 3D model for this particular object. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------La percepción es uno de los temas más relevantes en el mundo de la investigaci
ón en robótica. Su objetivo es procesar e interpretar los datos recibidos por
un sensor externo. La gran necesidad de desarrollar robots autónomos hace imprescindible
proporcionar soluciones que les permita realizar tareas más precisas,
flexibles y eficientes. Dado que estas plataformas cada día adquieren mejores capacidades
para manipular objetos, también necesitarán modelos expresivos y comprensivos:
para realizar tareas de manipulación y prensión, sus modelos han de
tener en cuenta cada uno de los objetos presentes en su entorno, junto con su localizaci
ón, orientación, forma y otros aspectos.
El objeto de la presente tesis doctoral es proponer soluciones a varios de los
retos que surgen al enfrentarse al problema del agarre, con el propósito final de
aumentar la capacidad de autonomía del robot manipulador MANFRED-2. Mediante
el análisis e interpretación de la percepción tridimensional, esta tesis cubre
en primer lugar la localización de planos de soporte en sus alrededores. Dado que
el entorno contendrá muchos otros elementos aparte de la superficie de apoyo buscada, el problema en entornos abarrotados ha sido solucionado mediante Evolución
Diferencial, que es un algoritmo evolutivo basado en partículas que evoluciona
temporalmente a la solución que contempla el menor resultado en la función de
coste.
Puesto que el propósito final de este trabajo de investigación es proveer de información valiosa a las aplicaciones de prensión, se ha desarrollado un reconstructor
de modelos completos. El método propuesto posee diferentes características
como robustez a giros abruptos, optimización multidimensional, extensión a otras
características, compatibilidad con otras técnicas de reconstrucción, manejo de incertidumbres
y un proceso de inicialización para reducir el tiempo de convergencia. Ha sido diseñado usando un registro optimizado mediante técnicas evolutivas
que tienen en cuenta las particularidades de la superficie del objeto, su forma
global y la información relativa a la textura.
El último problema abordado está relacionado con el reconocimiento de objetos. Con la intención de abastecer al robot con la mayor información posible sobre el entorno, se ha implementado un meta clasificador que diferencia de manera eficaz los objetos observados. Ha sido capacitado para distinguir objetos confundibles como tazas o platos con formas similares pero con diferentes colores o tamaños.
Las contribuciones presentes en esta tesis han sido completamente implementadas y probadas de manera empírica en la plataforma. Se ha desarrollado un sistema que cubre el problema de agarre desde la percepción al cálculo de la trayectoria
incluyendo el sistema de reconocimiento de objetos confundibles. Para ello, se ha presentado una mesa con objetos en un entorno cerrado cercano al robot. Los elementos son comparados con una base de datos y si se desea agarrar uno de ellos,
el robot estimará cómo cogerlo teniendo en cuenta las restricciones cinemáticas asociadas a una mano antropomórfica y el modelo tridimensional generado del objeto en cuestión
A Sensing Platform to Monitor Sleep Efficiency
Sleep plays a fundamental role in the human life. Sleep research is mainly focused on the understanding of the sleep patterns, stages and duration. An accurate sleep monitoring can detect early signs of sleep deprivation and insomnia consequentially implementing mechanisms for preventing and overcoming these problems. Recently, sleep monitoring has been achieved using wearable technologies, able to analyse also the body movements, but old people can encounter some difficulties in using and maintaining these devices. In this paper, we propose an unobtrusive sensing platform able to analyze body movements, infer sleep duration and awakenings occurred along the night, and evaluating the sleep efficiency index. To prove the feasibility of the suggested method we did a pilot trial in which several healthy users have been involved. The sensors were installed within the bed and, on each day, each user was administered with the Groningen Sleep Quality Scale questionnaire to evaluate the user’s perceived sleep quality. Finally, we show potential correlation between a perceived evaluation with an objective index as the sleep efficiency.</p
Towards Robust Bipedal Locomotion:From Simple Models To Full-Body Compliance
Thanks to better actuator technologies and control algorithms, humanoid robots to date can perform a wide range of locomotion activities outside lab environments. These robots face various control challenges like high dimensionality, contact switches during locomotion and a floating-base nature which makes them fall all the time. A rich set of sensory inputs and a high-bandwidth actuation are often needed to ensure fast and effective reactions to unforeseen conditions, e.g., terrain variations, external pushes, slippages, unknown payloads, etc. State of the art technologies today seem to provide such valuable hardware components. However, regarding software, there is plenty of room for improvement. Locomotion planning and control problems are often treated separately in conventional humanoid control algorithms. The control challenges mentioned above are probably the main reason for such separation. Here, planning refers to the process of finding consistent open-loop trajectories, which may take arbitrarily long computations off-line. Control, on the other hand, should be done very fast online to ensure stability. In this thesis, we want to link planning and control problems again and enable for online trajectory modification in a meaningful way. First, we propose a new way of describing robot geometries like molecules which breaks the complexity of conventional models. We use this technique and derive a planning algorithm that is fast enough to be used online for multi-contact motion planning. Similarly, we derive 3LP, a simplified linear three-mass model for bipedal walking, which offers orders of magnitude faster computations than full mechanical models. Next, we focus more on walking and use the 3LP model to formulate online control algorithms based on the foot-stepping strategy. The method is based on model predictive control, however, we also propose a faster controller with time-projection that demonstrates a close performance without numerical optimizations. We also deploy an efficient implementation of inverse dynamics together with advanced sensor fusion and actuator control algorithms to ensure a precise and compliant tracking of the simplified 3LP trajectories. Extensive simulations and hardware experiments on COMAN robot demonstrate effectiveness and strengths of our method. This thesis goes beyond humanoid walking applications. We further use the developed modeling tools to analyze and understand principles of human locomotion. Our 3LP model can describe the exchange of energy between human limbs in walking to some extent. We use this property to propose a metabolic-cost model of human walking which successfully describes trends in various conditions. The intrinsic power of the 3LP model to generate walking gaits in all these conditions makes it a handy solution for walking control and gait analysis, despite being yet a simplified model. To fill the reality gap, finally, we propose a kinematic conversion method that takes 3LP trajectories as input and generates more human-like postures. Using this method, the 3LP model, and the time-projecting controller, we introduce a graphical user interface in the end to simulate periodic and transient human-like walking conditions. We hope to use this combination in future to produce faster and more human-like walking gaits, possibly with more capable humanoid robots
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