Analysis and synthesis of bipedal humanoid movement : a physical simulation approach

textAdvances in graphics and robotics have increased the importance of tools for synthesizing humanoid movements to control animated characters and physical robots. There is also an increasing need for analyzing human movements for clinical diagnosis and rehabilitation. Existing tools can be expensive, inefficient, or difficult to use. Using simulated physics and motion capture to develop an interactive virtual reality environment, we capture natural human movements in response to controlled stimuli. This research then applies insights into the mathematics underlying physics simulation to adapt the physics solver to support many important tasks involved in analyzing and synthesizing humanoid movement. These tasks include fitting an articulated physical model to motion capture data, modifying the model pose to achieve a desired configuration (inverse kinematics), inferring internal torques consistent with changing pose data (inverse dynamics), and transferring a movement from one model to another model (retargeting). The result is a powerful and intuitive process for analyzing and synthesizing movement in a single unified framework.Computer Science

MULTI-MODAL TASK INSTRUCTIONS TO ROBOTS BY NAIVE USERS

This thesis presents a theoretical framework for the design of user-programmable robots. The objective of the work is to investigate multi-modal unconstrained natural instructions given to robots in order to design a learning robot. A corpus-centred approach is used to design an agent that can reason, learn and interact with a human in a natural unconstrained way. The corpus-centred design approach is formalised and developed in detail. It requires the developer to record a human during interaction and analyse the recordings to find instruction primitives. These are then implemented into a robot. The focus of this work has been on how to combine speech and gesture using rules extracted from the analysis of a corpus. A multi-modal integration algorithm is presented, that can use timing and semantics to group, match and unify gesture and language. The algorithm always achieves correct pairings on a corpus and initiates questions to the user in ambiguous cases or missing information. The domain of card games has been investigated, because of its variety of games which are rich in rules and contain sequences. A further focus of the work is on the translation of rule-based instructions. Most multi-modal interfaces to date have only considered sequential instructions. The combination of frame-based reasoning, a knowledge base organised as an ontology and a problem solver engine is used to store these rules. The understanding of rule instructions, which contain conditional and imaginary situations require an agent with complex reasoning capabilities. A test system of the agent implementation is also described. Tests to confirm the implementation by playing back the corpus are presented. Furthermore, deployment test results with the implemented agent and human subjects are presented and discussed. The tests showed that the rate of errors that are due to the sentences not being defined in the grammar does not decrease by an acceptable rate when new grammar is introduced. This was particularly the case for complex verbal rule instructions which have a large variety of being expressed

Review of practice-led research in art, design & architecture

This review report sets out the outcomes of a 10 month investigation to describe the landscape of practice-led research in Art, Design and Architecture (ADA) in the UK and beyond. We were asked for a qualitative review but of course it has been important to gather some numbers to check and illustrate our observations. We have consulted widely, both face to face and in the virtual world, with experts and novices in the UK and around the world. We have tried to strike a balance between the natural desire of our colleagues to debate the more contentious aspects of this territory (they were never going to forgo that opportunity) and the equally strong wish of the AHRC that we should provide a clear description of what is happening. We have collected some diverse examples of research and subjected them to various examinations. We have also examined a selection of research projects funded by AHRC and other projects by creative practitioners, funded by a non-research organisation. From all this we have been able to describe the landscape in a straightforward sense: We have measures of the proportions of ADA academics involved in practice-led research. We have clarified differences in the ways that the different ADA disciplines engage with practice-led research and identified some problems that indicate possible future support strategies. We have discussed some problems with general definitions of research and identified issues that should be addressed to ensure that the AHRC definition can be applied to the full range of practice-led research. We have picked out some specific case examples that illustrate the range of contexts, methods and contributions made by practice-led researchers, and more are described in detail in Appendix F. We have also sought to assess how this research relates to the wider international picture in which the UK appears to have a strong position in both volume and development of research. We have also set out some issues that affect this community of researchers: What strengths and weaknesses have we observed and where is there a need to support development? Do the AHRC definition of research and guidance on practice-led research provide an effective framework? We have illustrated the state of development of research in ADA, and some reasons why it is less robust than might be expected from such long established disciplines. We recommend that the career path of researchers in ADA needs some attention and make some suggestions about how that could be achieved. We have also indicated some areas of inquiry that might be supported to advance the theory and methods of practice-led research. In particular we have come to the conclusion that conventional ideas of contribution to knowledge or understanding may not be serving us well. This is significant to fine artists but we believe that it relevant across ADA and a shared effort to develop appropriate new models would be a constructive development. The full set of recommendations can be found in chapter 5

Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Actor & Avatar: A Scientific and Artistic Catalog

What kind of relationship do we have with artificial beings (avatars, puppets, robots, etc.)? What does it mean to mirror ourselves in them, to perform them or to play trial identity games with them? Actor & Avatar addresses these questions from artistic and scholarly angles. Contributions on the making of "technical others" and philosophical reflections on artificial alterity are flanked by neuroscientific studies on different ways of perceiving living persons and artificial counterparts. The contributors have achieved a successful artistic-scientific collaboration with extensive visual material

Investigating Real-time Touchless Hand Interaction and Machine Learning Agents in Immersive Learning Environments

The recent surge in the adoption of new technologies and innovations in connectivity, interaction technology, and artificial realities can fundamentally change the digital world. eXtended Reality (XR), with its potential to bridge the virtual and real environments, creates new possibilities to develop more engaging and productive learning experiences. Evidence is emerging that thissophisticated technology offers new ways to improve the learning process for better student interaction and engagement. Recently, immersive technology has garnered much attention as an interactive technology that facilitates direct interaction with virtual objects in the real world. Furthermore, these virtual objects can be surrogates for real-world teaching resources, allowing for virtual labs. Thus XR could enable learning experiences that would not bepossible in impoverished educational systems worldwide. Interestingly, concepts such as virtual hand interaction and techniques such as machine learning are still not widely investigated in immersive learning. Hand interaction technologies in virtual environments can support the kinesthetic learning pedagogical approach, and the need for its touchless interaction nature hasincreased exceptionally in the post-COVID world. By implementing and evaluating real-time hand interaction technology for kinesthetic learning and machine learning agents for self-guided learning, this research has addressed these underutilized technologies to demonstrate the efficiency of immersive learning. This thesis has explored different hand-tracking APIs and devices to integrate real-time hand interaction techniques. These hand interaction techniques and integrated machine learning agents using reinforcement learning are evaluated with different display devices to test compatibility. The proposed approach aims to provide self-guided, more productive, and interactive learning experiences. Further, this research has investigated ethics, privacy, and security issues in XR and covered the future of immersive learning in the Metaverse.<br/

Investigating Real-time Touchless Hand Interaction and Machine Learning Agents in Immersive Learning Environments

The recent surge in the adoption of new technologies and innovations in connectivity, interaction technology, and artificial realities can fundamentally change the digital world. eXtended Reality (XR), with its potential to bridge the virtual and real environments, creates new possibilities to develop more engaging and productive learning experiences. Evidence is emerging that thissophisticated technology offers new ways to improve the learning process for better student interaction and engagement. Recently, immersive technology has garnered much attention as an interactive technology that facilitates direct interaction with virtual objects in the real world. Furthermore, these virtual objects can be surrogates for real-world teaching resources, allowing for virtual labs. Thus XR could enable learning experiences that would not bepossible in impoverished educational systems worldwide. Interestingly, concepts such as virtual hand interaction and techniques such as machine learning are still not widely investigated in immersive learning. Hand interaction technologies in virtual environments can support the kinesthetic learning pedagogical approach, and the need for its touchless interaction nature hasincreased exceptionally in the post-COVID world. By implementing and evaluating real-time hand interaction technology for kinesthetic learning and machine learning agents for self-guided learning, this research has addressed these underutilized technologies to demonstrate the efficiency of immersive learning. This thesis has explored different hand-tracking APIs and devices to integrate real-time hand interaction techniques. These hand interaction techniques and integrated machine learning agents using reinforcement learning are evaluated with different display devices to test compatibility. The proposed approach aims to provide self-guided, more productive, and interactive learning experiences. Further, this research has investigated ethics, privacy, and security issues in XR and covered the future of immersive learning in the Metaverse.<br/

Discovery learning with tangible technologies: the case of children with intellectual disabilities

Intellectual disabilities cause significant sub--‐average achievement in learning, with difficulties in perception, attention, communication of ideas, language acquisition, abstraction and generalisation. From a socio--‐constructionist perspective, digital technologies can provide resources to help addressing these difficulties. Tangible technologies are considered particularly promising tools for children with intellectual disabilities, by enabling interaction through physical action and manipulation and facilitating representational concrete--‐ abstract links by integrating physical and digital worlds. However, hands--‐on learning activities remain a recommended but problematic approach for intellectually disabled students. This thesis investigates how and which characteristics of tangible interaction may support children with intellectual disabilities to productively engage in discovery learning. \ud Empirical studies were performed where children with intellectual disabilities used four tangible systems with distinct design characteristics. Four broad themes emerged from qualitative analysis which are central for identifying how to best support exploratory interaction: types of digital representations; physical affordances; representational mappings; and conceptual metaphors. Guidelines for the development of tangible artefacts and facilitation of discovery learning activities with tangibles were derived from these themes. A complementary quantitative analysis investigated the effects of external guidance in promoting episodes of discovery in tangible interaction. \ud This thesis argues that providing tangible interaction alone is not sufficient to bring significant benefits to the experience of intellectually disabled students in discovery learning. Visual digital representations, meaningful spatial configurations of physical representations, temporal and spatial contiguity between action and representations, simple causality and familiar conceptual metaphors are critical in providing informational intrinsic feedback to exploratory actions, which allied with external guidance that creates a minimal underlying structure for interaction, should establish an ideal environment for discovery. \u