A NEUROMORPHIC APPROACH TO TACTILE PERCEPTION

Ph.DDOCTOR OF PHILOSOPH

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Reconstructing the Present Through Kinesthetic History: An Investigation into Modes of Preserving, Transmitting, and Restaging Contemporary Dance

Methods of dance preservation have evolved alongside conceptual themes that have framed dance’s historical narrative. The tradition of written dance notation developed in accordance with notions that prioritized logocentricity, and placed historical legitimacy on tangible artifacts and irrefutable archives; whereas the technical revolution of the late twentieth century saw dance preservation practices shift to embrace film and video documentation because they provided more accessible, and more convenient records. Since the 1970s video recordings have generally been considered to provide authentic visual representations of dance works, and the tradition of score writing has begun to wane. However, scholarly criticism has unveiled both philosophical and practical challenges posed by these two modes of documentation, thus illuminating a gap between theories of embodiment and the practice of dance preservation. In alignment with contemporary discourse, which legitimizes the body as a site of generating and storing knowledge, this dissertation suggests ‘kinesthetic history’ as a valid mode of dance preservation. Operating as a counterpart to oral history, and borrowing theoretical concepts from contemporary historiography, existential phenomenology and ethnography, the term ‘kinesthetic history’ suggests a mode of corporeal inscription and transmission that relies on the reciprocal interaction of bodies in space. The use of ‘kinesthetic history’ as a methodological approach to the preservation, translation, and reconstruction of movement material reflects the elements of fluidity, plurality and subjectivity that are often characteristic of contemporary choreographic practices. This theory is interrogated through a case study, which explores the ways in which both a written and digitized score, video recordings, and the ‘kinesthetic history’ of an original cast member operated as modes of transmission in a 2013 restaging of William Forsythe’s One Flat Thing, reproduced (2000) at The Juilliard School. Conclusions drawn from the case study challenge the traditional notions of reconstruction and restaging and suggest ‘regeneration’ as an alternative term to describe the process of preserving and transmitting contemporary dance works

Robotic learning of force-based industrial manipulation tasks

Even with the rapid technological advancements, robots are still not the most comfortable machines to work with. Firstly, due to the separation of the robot and human workspace which imposes an additional financial burden. Secondly, due to the significant re-programming cost in case of changing products, especially in Small and Medium-sized Enterprises (SMEs). Therefore, there is a significant need to reduce the programming efforts required to enable robots to perform various tasks while sharing the same space with a human operator. Hence, the robot must be equipped with a cognitive and perceptual capabilities that facilitate human-robot interaction. Humans use their various senses to perform tasks such as vision, smell and taste. One sensethat plays a significant role in human activity is ’touch’ or ’force’. For example, holding a cup of tea, or making fine adjustments while inserting a key requires haptic information to achieve the task successfully. In all these examples, force and torque data are crucial for the successful completion of the activity. Also, this information implicitly conveys data about contact force, object stiffness, and many others. Hence, a deep understanding of the execution of such events can bridge the gap between humans and robots. This thesis is being directed to equip an industrial robot with the ability to deal with force perceptions and then learn force-based tasks using Learning from Demonstration (LfD).To learn force-based tasks using LfD, it is essential to extract task-relevant features from the force information. Then, knowledge must be extracted and encoded form the task-relevant features. Hence, the captured skills can be reproduced in a new scenario. In this thesis, these elements of LfD were achieved using different approaches based on the demonstrated task. In this thesis, four robotics problems were addressed using LfD framework. The first challenge was to filter out robots’ internal forces (irrelevant signals) using data-driven approach. The second robotics challenge was the recognition of the Contact State (CS) during assembly tasks. To tackle this challenge, a symbolic based approach was proposed, in which a force/torque signals; during demonstrated assembly, the task was encoded as a sequence of symbols. The third challenge was to learn a human-robot co-manipulation task based on LfD. In this case, an ensemble machine learning approach was proposed to capture such a skill. The last challenge in this thesis, was to learn an assembly task by demonstration with the presents of parts geometrical variation. Hence, a new learning approach based on Artificial Potential Field (APF) to learn a Peg-in-Hole (PiH) assembly task which includes no-contact and contact phases. To sum up, this thesis focuses on the use of data-driven approaches to learning force based task in an industrial context. Hence, different machine learning approaches were implemented, developed and evaluated in different scenarios. Then, the performance of these approaches was compared with mathematical modelling based approaches.</div

Performativity and Performance: Representing the Tattooed Body.

In this study I examine visual representations of tattooed bodies in three arenas of cultural production: tattoo conventions, advertising, and neo-tribal books. Through the methodological lens of genealogies of performance, I analyze these texts\u27 construction of the tattooed body as classed, gendered, and exotic. I argue that contemporary representations of the tattooed body resist and reproduce discursive power regimes by surrogating prior cultural performances and representations of performance. I argue that contemporary visual representations of the tattooed body succeed in resisting discursive authority when they performatively cite multiple and transgressive authorities. I additionally indicate that the body in representation transgresses cultural normalization strategies when it refuses to be categorized as a system of separate and, in their separation, silenced parts. The first case study traces the discursive history of the social status of tattooed bodies performing at the Southern Comfort Tattoo Expo. I link the performance styles and spatial logic of this tattoo convention to the illustrated men and women performing on sideshow stages in circus and carnival venues at the turn of the last century. The second case study situates the tattooed body within gender discourse. I begin with an interpretation of a late 1990s Tampax advertising campaign featuring a tattooed Rosie the Riveter. I then draw interpretive connections between that advertisement and the Marlboro Man advertising campaign initiated during the 1950s before returning again to the 1990s and an evaluation of a Sony PlaySation advertisement. The third case study addresses the construction of the tattooed body as an exotic modern primitive within three books: Modern Primitives, Return of the Tribal, and Customizing the Body. The analysis of these texts suggests that modern primitive discourse creates its own authoritative history as well as attempts to occlude the histories of the sideshow at the turn of the century and the working-class masculine history of the mid-century

Computer-supported movement guidance: investigating visual/visuotactile guidance and informing the design of vibrotactile body-worn interfaces

This dissertation explores the use of interactive systems to support movement guidance, with applications in various fields such as sports, dance, physiotherapy, and immersive sketching. The research focuses on visual, haptic, and visuohaptic approaches and aims to overcome the limitations of traditional guidance methods, such as dependence on an expert and high costs for the novice. The main contributions of the thesis are (1) an evaluation of the suitability of various types of displays and visualizations of the human body for posture guidance, (2) an investigation into the influence of different viewpoints/perspectives, the addition of haptic feedback, and various movement properties on movement guidance in virtual environments, (3) an investigation into the effectiveness of visuotactile guidance for hand movements in a virtual environment, (4) two in-depth studies of haptic perception on the body to inform the design of wearable and handheld interfaces that leverage tactile output technologies, and (5) an investigation into new interaction techniques for tactile guidance of arm movements. The results of this research advance the state of the art in the field, provide design and implementation insights, and pave the way for new investigations in computer-supported movement guidance

Sensorimotor Representation Learning for an “Active Self” in Robots: A Model Survey

Safe human-robot interactions require robots to be able to learn how to behave appropriately in spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to our ability to perceive our body in space, sensing the location of our limbs during movement, being aware of other objects and agents, and controlling our body parts to interact with them intentionally. Toward the next generation of robots with bio-inspired capacities, in this paper, we first review the developmental processes of underlying mechanisms of these abilities: The sensory representations of body schema, peripersonal space, and the active self in humans. Second, we provide a survey of robotics models of these sensory representations and robotics models of the self; and we compare these models with the human counterparts. Finally, we analyze what is missing from these robotics models and propose a theoretical computational framework, which aims to allow the emergence of the sense of self in artificial agents by developing sensory representations through self-exploration.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Projekt DEALPeer Reviewe

Sensorimotor representation learning for an "active self" in robots: A model survey

Safe human-robot interactions require robots to be able to learn how to behave appropriately in \sout{humans' world} \rev{spaces populated by people} and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to our ability to perceive our body in space, sensing the location of our limbs during movement, being aware of other objects and agents, and controlling our body parts to interact with them intentionally. Toward the next generation of robots with bio-inspired capacities, in this paper, we first review the developmental processes of underlying mechanisms of these abilities: The sensory representations of body schema, peripersonal space, and the active self in humans. Second, we provide a survey of robotics models of these sensory representations and robotics models of the self; and we compare these models with the human counterparts. Finally, we analyse what is missing from these robotics models and propose a theoretical computational framework, which aims to allow the emergence of the sense of self in artificial agents by developing sensory representations through self-exploration