Spatial representation for planning and executing robot behaviors in complex environments

Robots are already improving our well-being and productivity in different applications such as industry, health-care and indoor service applications. However, we are still far from developing (and releasing) a fully functional robotic agent that can autonomously survive in tasks that require human-level cognitive capabilities. Robotic systems on the market, in fact, are designed to address specific applications, and can only run pre-defined behaviors to robustly repeat few tasks (e.g., assembling objects parts, vacuum cleaning). They internal representation of the world is usually constrained to the task they are performing, and does not allows for generalization to other scenarios. Unfortunately, such a paradigm only apply to a very limited set of domains, where the environment can be assumed to be static, and its dynamics can be handled before deployment. Additionally, robots configured in this way will eventually fail if their "handcrafted'' representation of the environment does not match the external world. Hence, to enable more sophisticated cognitive skills, we investigate how to design robots to properly represent the environment and behave accordingly. To this end, we formalize a representation of the environment that enhances the robot spatial knowledge to explicitly include a representation of its own actions. Spatial knowledge constitutes the core of the robot understanding of the environment, however it is not sufficient to represent what the robot is capable to do in it. To overcome such a limitation, we formalize SK4R, a spatial knowledge representation for robots which enhances spatial knowledge with a novel and "functional" point of view that explicitly models robot actions. To this end, we exploit the concept of affordances, introduced to express opportunities (actions) that objects offer to an agent. To encode affordances within SK4R, we define the "affordance semantics" of actions that is used to annotate an environment, and to represent to which extent robot actions support goal-oriented behaviors. We demonstrate the benefits of a functional representation of the environment in multiple robotic scenarios that traverse and contribute different research topics relating to: robot knowledge representations, social robotics, multi-robot systems and robot learning and planning. We show how a domain-specific representation, that explicitly encodes affordance semantics, provides the robot with a more concrete understanding of the environment and of the effects that its actions have on it. The goal of our work is to design an agent that will no longer execute an action, because of mere pre-defined routine, rather, it will execute an actions because it "knows'' that the resulting state leads one step closer to success in its task

Adaptive shared-control of a robotic walker to improve human-robot cooperation in gait biomechanical rehabilitation

Dissertação de mestrado integrado em Engenharia Biomédica (especialização em Eletrónica Médica)Sessões de reabilitação de pacientes com deficiências na marcha é importante para que a qualidade de vida dos mesmos seja recuperada. Quando auxiliadas por andarilhos robóticos inteligentes as sessões têm mostrado melhorias significativas, face aos resultados obtidos por métodos clássicos. O andarilho WALKit é um dos dispositivos mencionados e permite ser conduzido por parte do paciente enquanto um especialista supervisiona todo o processo de forma a evitar colisões e quedas. Este processo de supervisão é moroso e requer constante presença de um especialista para cada paciente. Nesta dissertação é proposto um controlador autónomo e inteligente capaz de partilhar a condução do andarilho pelo paciente e pelo supervisor evitando colisões com obstáculos. Para remover a necessidade constante do médico supervisor, um módulo de condução autónoma foi desenvolvido. O modo autónomo proposto usa um sensor Light Detection and Ranging e o algoritmo de Simultaneous Localization and Mapping (Cartographer) para obter mapas e a localização do andarilho. Seguidamente, os planeadores global e local , A* e Dynamic Window Approach respetivamente, traçam caminhos válidos para o destino, interpretáveis pelo andarilho. Usando o modo autónomo como especialista e as intenções do paciente, o controlador partilhado usa o algoritmo Proximal Policy Optimization, aprendendo o comportamento pretendido através de um processo de tentiva e erro, maximizando a recompensa recebida através de uma função pré-estabelecida. Uma rede neuronal com camadas convolucionais e lineares é capaz de inferir o risco enfrentado pelo sistema paciente-WALKit e determinar se o modo autónomo deve assumir controlo de forma a neutralizar o risco mencionado. Globalmente foram detetados erros inferiores a 38 cm no sistema de mapeamento e localização. Quer nos cenários de testagem do controlador autónomo, quer nos do controlador partilhado, nenhuma colisão foi registada garantindo em todas as tentativas a chegada ao destino escolhido. O modo autónomo, apesar de evitar obstáculos, não foi capaz de alcançar certos destinos não contemplados em ambientes de reabilitação. O modo partilhado mostrou também certas transições bruscas entre modo autónomo e intenção que podem comprometer a segurança do paciente. É necessário, como trabalho futuro, estabelecer métricas de validação objetivas e testar o controlador com pacientes de forma a corretamente estimar o desempenho.Rehabilitation sessions of patients with gait disabilities is important to restore quality of life. When aided by intelligent robotic walkers the sessions have shown significant improvements when compared to the results obtained by classical methods. The WALKit walker is one of the devices mentioned and allows the patient to drive it while a medical expert supervises the entire process in order to avoid collisions and falls. This supervision process takes time and requires constant presence of a medical expert for each patient. This dissertation proposes an intelligent controller capable of sharing the walker’s drivability by the patient and the supervisor, avoiding collisions with obstacles. To remove the constant need of a supervisor, an autonomous driving module was developed. The proposed autonomous mode uses a Light Detection and Ranging sensor and the Simultaneous Localization and Mapping (Cartographer ) algorithm to obtain maps and the location of the walker. Then, the global and local planners, A * and Dynamic Window Approach respectively, draw valid paths to the destination, interpretable by the walker. Using the autonomous mode as a expert and the patient’s intentions, the SC uses the Proximal Policy Optimization algorithm, learning the intended behavior through a trial and error process, maximizing the reward received through a pre-established function. One neural network with convolutional and linear layers is able to infer the risk faced by the patient-WALKit system and determine whether the autonomous mode should take control in order to neutralize the mentioned risk. Globally, errors smaller than 38 cm were detected in the mapping and localization system. In the testing scenarios of the autonomous controller and in the SC no collisions were recorded guaranteeing the arrival at the chosen destination in all attempts. The autonomous mode, despite avoiding obstacles, was not able to reach certain destinations not covered in rehabilitation environments. The shared mode has also shown certain sudden transitions between autonomous mode and intention that could compromise patient safety. It is necessary, as future work, to establish objective validation metrics and testing the controller with patients is necessary in order to correctly estimate performance

Digital Transformation

The amount of literature on Digital Transformation is staggering—and it keeps growing. Why, then, come out with yet another such document? Moreover, any text aiming at explaining the Digital Transformation by presenting a snapshot is going to become obsolete in a blink of an eye, most likely to be already obsolete at the time it is first published. The FDC Initiative on Digital Reality felt there is a need to look at the Digital Transformation from the point of view of a profound change that is pervading the entire society—a change made possible by technology and that keeps changing due to technology evolution opening new possibilities but is also a change happening because it has strong economic reasons. The direction of this change is not easy to predict because it is steered by a cultural evolution of society, an evolution that is happening in niches and that may expand rapidly to larger constituencies and as rapidly may fade away. This creation, selection by experimentation, adoption, and sudden disappearance, is what makes the whole scenario so unpredictable and continuously changing.The amount of literature on Digital Transformation is staggering—and it keeps growing. Why, then, come out with yet another such document? Moreover, any text aiming at explaining the Digital Transformation by presenting a snapshot is going to become obsolete in a blink of an eye, most likely to be already obsolete at the time it is first published. The FDC Initiative on Digital Reality felt there is a need to look at the Digital Transformation from the point of view of a profound change that is pervading the entire society—a change made possible by technology and that keeps changing due to technology evolution opening new possibilities but is also a change happening because it has strong economic reasons. The direction of this change is not easy to predict because it is steered by a cultural evolution of society, an evolution that is happening in niches and that may expand rapidly to larger constituencies and as rapidly may fade away. This creation, selection by experimentation, adoption, and sudden disappearance, is what makes the whole scenario so unpredictable and continuously changing

Intelligence in 5G networks

Over the past decade, Artificial Intelligence (AI) has become an important part of our daily lives; however, its application to communication networks has been partial and unsystematic, with uncoordinated efforts that often conflict with each other. Providing a framework to integrate the existing studies and to actually build an intelligent network is a top research priority. In fact, one of the objectives of 5G is to manage all communications under a single overarching paradigm, and the staggering complexity of this task is beyond the scope of human-designed algorithms and control systems. This thesis presents an overview of all the necessary components to integrate intelligence in this complex environment, with a user-centric perspective: network optimization should always have the end goal of improving the experience of the user. Each step is described with the aid of one or more case studies, involving various network functions and elements. Starting from perception and prediction of the surrounding environment, the first core requirements of an intelligent system, this work gradually builds its way up to showing examples of fully autonomous network agents which learn from experience without any human intervention or pre-defined behavior, discussing the possible application of each aspect of intelligence in future networks

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

A decoupled cross-layer design for symbiotic cognitive relaying with time incentive

The rationale of this work is that the incumbent primary user (PU) of a cognitive radio (CR) system relays its traffic through the secondary user (SU) network for an enhanced throughput. In return, it rewards the SUs with an incentive time during which they can use the complete licensed bandwidth to transmit their own data, without the need for spectrum sensing. With the objective of maximizing the time incentive, we develop a MAC layer resource allocation strategy and a corresponding routing technique. A low-complexity decoupled cross-layer design is proposed to make the symbiotic relaying scheme practically workable. Simulation results are provided, which are indicative of the effectiveness of the proposed design

Video Games for Earthly Survival: Gaming in the Post-Anthropocene

In this paper I evaluate the sixth mass extinction on planet Earth, and its implications for the medium of the video game. The Anthropocene, a term popularized by the end of the 20th century to refer to the geological impact of human beings on planet Earth, assumes temporal development, a ‘before’ and ‘after’ the appearance of humankind. The ‘after’ period, the Post-Anthropocene, is repeatedly claimed by scientists to be approaching within the next few decades, as over-consumption is destroying vital resources of the planet. Allegedly, the sixth mass extinction in the history of our planet is already unfolding, and might determine the disappearance of life from Earth and, as far as we know, from the Universe and beyond. Video games responding to the arrival of the future is not just imagined in fictional settings (e.g. The Legenda of Zelda: Majora’s Mask, Nintendo, 2000; Horizon: Zero Dawn, Guerrilla Games, 2017), but within game design. In the last decade an increasing number of video games requiring limited human intervention has been released. Incremental/ idle games such as Cookie Clicker (Julien Thiennot, 2013) and AdVenture Capitalist (Hyper Hippo Productions, 2014) require an initial input from the player to start, and then keep playing themselves in the background operations of a laptop or smartphone. Virtual environments can be entirely designed by algorithms, as experimented by Hello Games for No Man’s Sky (2016). Artificial Intelligence is also used to play games. Screeps, a massive-multiplayer online game, requires players to program an AI that will play the game in their place, and which will “live within the game even while you are offline” (Screeps Team, 2014). Ghost cars in racing games replace the human actor with a representation of their performance. The same concept is further explored by the Drivatar of the Forza Motorsport series (Microsoft Studios, 2005-2017), which simulates the driving style of the player and competes online against other AI-controlled cars. These are only some of the examples that suggest that human beings are becoming peripheral in the act of playing games. In short, it is probably becoming ‘easier to imagine the end of the world than the end of gaming’. While studies on games with no players, and on the non-human side of gaming, have been proposed in the past, my presentation takes a non-normative and non-systemic approach to the study of games for the Post-Anthropocene. I am concerned with the creative potential of the paradoxes, spoofs, and contradictions opened by games that take Man/Anthropos as being no longer at the centre of ‘interaction’, ‘fun’, and many other mythological aspects of digital gaming. Nonhuman gaming questions the historical, political, ecological and even geological situatedness of our knowledge on games and gamers, interaction and passivity, life and death

The Paranoiac-Critical Method of Reflectance Transformation Imaging

A performative talk examining Reflectance Transformation Imaging (RTI), an open source computational photographic process that is transforming methodologies in archaeology and heritage conservation for its ability to interactively re-light artefacts within a virtual hemisphere of illumination and extrude a digital topography that is hyper-legible in space-time, from its contemporary application in facial recognition via Bertrand Tavernier's 1980 science fiction film La Mort en Direct and a return of the death mask through digital extrusion, ultimately locating a progenitor of the heightened objectivity promised by RTI paradoxically in Surrealist photography and the fugitive facialities of Salvador Dali's Paranoiac-Critical Method. As emerging imaging technologies such as RTI are seen to open novel ways of extracting latent data from historical artefacts, reassembling objects of study in a new (virtual) light, collateral opportunities provided by these technologies to re-enter archival still and moving image recordings inadvertently recalibrate their spatio-temporal ground and destabilise their indexical reading through an excessive production of new traces and signs. If methodologies can be seen to play a significant role in constructing their objects of study, then emerging computational imaging operations such as RTI have their own subjectivities to disclose: In performing a media archaeology of this digital process, the talk proposes that we not only narrate the subjects of our study but the very tools of investigation themselves

Urban food strategies in Central and Eastern Europe: what's specific and what's at stake?

Integrating a larger set of instruments into Rural Development Programmes implied an increasing focus on monitoring and evaluation. Against the highly diversified experience with regard to implementation of policy instruments the Common Monitoring and Evaluation Framework has been set up by the EU Commission as a strategic and streamlined method of evaluating programmes’ impacts. Its indicator-based approach mainly reflects the concept of a linear, measure-based intervention logic that falls short of the true nature of RDP operation and impact capacity on rural changes. Besides the different phases of the policy process, i.e. policy design, delivery and evaluation, the regional context with its specific set of challenges and opportunities seems critical to the understanding and improvement of programme performance. In particular the role of local actors can hardly be grasped by quantitative indicators alone, but has to be addressed by assessing processes of social innovation. This shift in the evaluation focus underpins the need to take account of regional implementation specificities and processes of social innovation as decisive elements for programme performance.