Classifying types of gesture and inferring intent

In order to infer intent from gesture, a rudimentary classification of types of gestures into five main classes is introduced. The classification is intended as a basis for incorporating the understanding of gesture into human-robot interaction (HRI). Some requirements for the operational classification of gesture by a robot interacting with humans are also suggested

Towards gestural understanding for intelligent robots

Fritsch JN. Towards gestural understanding for intelligent robots. Bielefeld: Universität Bielefeld; 2012.A strong driving force of scientific progress in the technical sciences is the quest for systems that assist humans in their daily life and make their life easier and more enjoyable. Nowadays smartphones are probably the most typical instances of such systems. Another class of systems that is getting increasing attention are intelligent robots. Instead of offering a smartphone touch screen to select actions, these systems are intended to offer a more natural human-machine interface to their users. Out of the large range of actions performed by humans, gestures performed with the hands play a very important role especially when humans interact with their direct surrounding like, e.g., pointing to an object or manipulating it. Consequently, a robot has to understand such gestures to offer an intuitive interface. Gestural understanding is, therefore, a key capability on the way to intelligent robots. This book deals with vision-based approaches for gestural understanding. Over the past two decades, this has been an intensive field of research which has resulted in a variety of algorithms to analyze human hand motions. Following a categorization of different gesture types and a review of other sensing techniques, the design of vision systems that achieve hand gesture understanding for intelligent robots is analyzed. For each of the individual algorithmic steps – hand detection, hand tracking, and trajectory-based gesture recognition – a separate Chapter introduces common techniques and algorithms and provides example methods. The resulting recognition algorithms are considering gestures in isolation and are often not sufficient for interacting with a robot who can only understand such gestures when incorporating the context like, e.g., what object was pointed at or manipulated. Going beyond a purely trajectory-based gesture recognition by incorporating context is an important prerequisite to achieve gesture understanding and is addressed explicitly in a separate Chapter of this book. Two types of context, user-provided context and situational context, are reviewed and existing approaches to incorporate context for gestural understanding are reviewed. Example approaches for both context types provide a deeper algorithmic insight into this field of research. An overview of recent robots capable of gesture recognition and understanding summarizes the currently realized human-robot interaction quality. The approaches for gesture understanding covered in this book are manually designed while humans learn to recognize gestures automatically during growing up. Promising research targeted at analyzing developmental learning in children in order to mimic this capability in technical systems is highlighted in the last Chapter completing this book as this research direction may be highly influential for creating future gesture understanding systems

Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior

User-based gesture vocabulary for form creation during a product design process

There are inconsistencies between the nature of the conceptual design and the functionalities of the computational systems supporting it, which disrupt the designers’ process, focusing on technology rather than designers’ needs. A need for elicitation of hand gestures appropriate for the requirements of the conceptual design, rather than those arbitrarily chosen or focusing on ease of implementation was identified.The aim of this thesis is to identify natural and intuitive hand gestures for conceptual design, performed by designers (3rd, 4th year product design engineering students and recent graduates) working on their own, without instruction and without limitations imposed by the facilitating technology. This was done via a user centred study including 44 participants. 1785 gestures were collected. Gestures were explored as a sole mean for shape creation and manipulation in virtual 3D space. Gestures were identified, described in writing, sketched, coded based on the taxonomy used, categorised based on hand form and the path travelled and variants identified. Then they were statistically analysed to ascertain agreement rates between the participants, significance of the agreement and the likelihood of number of repetitions for each category occurring by chance. The most frequently used and statistically significant gestures formed the consensus set of vocabulary for conceptual design. The effect of the shape of the manipulated object on the gesture performed, and if the sequence of the gestures participants proposed was different from the established CAD solid modelling practices were also observed.Vocabulary was evaluated by non-designer participants, and the outcomes have shown that the majority of gestures were appropriate and easy to perform. Evaluation was performed theoretically and in the VR environment. Participants selected their preferred gestures for each activity, and a variant of the vocabulary for conceptual design was created as an outcome, that aims to ensure that extensive training is not required, extending the ability to design beyond trained designers only.There are inconsistencies between the nature of the conceptual design and the functionalities of the computational systems supporting it, which disrupt the designers’ process, focusing on technology rather than designers’ needs. A need for elicitation of hand gestures appropriate for the requirements of the conceptual design, rather than those arbitrarily chosen or focusing on ease of implementation was identified.The aim of this thesis is to identify natural and intuitive hand gestures for conceptual design, performed by designers (3rd, 4th year product design engineering students and recent graduates) working on their own, without instruction and without limitations imposed by the facilitating technology. This was done via a user centred study including 44 participants. 1785 gestures were collected. Gestures were explored as a sole mean for shape creation and manipulation in virtual 3D space. Gestures were identified, described in writing, sketched, coded based on the taxonomy used, categorised based on hand form and the path travelled and variants identified. Then they were statistically analysed to ascertain agreement rates between the participants, significance of the agreement and the likelihood of number of repetitions for each category occurring by chance. The most frequently used and statistically significant gestures formed the consensus set of vocabulary for conceptual design. The effect of the shape of the manipulated object on the gesture performed, and if the sequence of the gestures participants proposed was different from the established CAD solid modelling practices were also observed.Vocabulary was evaluated by non-designer participants, and the outcomes have shown that the majority of gestures were appropriate and easy to perform. Evaluation was performed theoretically and in the VR environment. Participants selected their preferred gestures for each activity, and a variant of the vocabulary for conceptual design was created as an outcome, that aims to ensure that extensive training is not required, extending the ability to design beyond trained designers only

Bringing tabletop technologies to kindergarten children

Taking computer technology away from the desktop and into a more physical, manipulative space, is known that provide many benefits and is generally considered to result in a system that is easier to learn and more natural to use. This paper describes a design solution that allows kindergarten children to take the benefits of the new pedagogical possibilities that tangible interaction and tabletop technologies offer for manipulative learning. After analysis of children's cognitive and psychomotor skills, we have designed and tuned a prototype game that is suitable for children aged 3 to 4 years old. Our prototype uniquely combines low cost tangible interaction and tabletop technology with tutored learning. The design has been based on the observation of children using the technology, letting them freely play with the application during three play sessions. These observational sessions informed the design decisions for the game whilst also confirming the children's enjoyment of the prototype

Systematic literature review of hand gestures used in human computer interaction interfaces

Gestures, widely accepted as a humans' natural mode of interaction with their surroundings, have been considered for use in human-computer based interfaces since the early 1980s. They have been explored and implemented, with a range of success and maturity levels, in a variety of fields, facilitated by a multitude of technologies. Underpinning gesture theory however focuses on gestures performed simultaneously with speech, and majority of gesture based interfaces are supported by other modes of interaction. This article reports the results of a systematic review undertaken to identify characteristics of touchless/in-air hand gestures used in interaction interfaces. 148 articles were reviewed reporting on gesture-based interaction interfaces, identified through searching engineering and science databases (Engineering Village, Pro Quest, Science Direct, Scopus and Web of Science). The goal of the review was to map the field of gesture-based interfaces, investigate the patterns in gesture use, and identify common combinations of gestures for different combinations of applications and technologies. From the review, the community seems disparate with little evidence of building upon prior work and a fundamental framework of gesture-based interaction is not evident. However, the findings can help inform future developments and provide valuable information about the benefits and drawbacks of different approaches. It was further found that the nature and appropriateness of gestures used was not a primary factor in gesture elicitation when designing gesture based systems, and that ease of technology implementation often took precedence

On the role of gestures in human-robot interaction

This thesis investigates the gestural interaction problem and in particular the usage of gestures for human-robot interaction. The lack of a clear definition of the problem statement and a common terminology resulted in a fragmented field of research where building upon prior work is rare. The scope of the research presented in this thesis, therefore, consists in laying the foundation to help the community to build a more homogeneous research field. The main contributions of this thesis are twofold: (i) a taxonomy to define gestures; and (ii) an ingegneristic definition of the gestural interaction problem. The contributions resulted is a schema to represent the existing literature in a more organic way, helping future researchers to identify existing technologies and applications, also thanks to an extensive literature review. Furthermore, the defined problem has been studied in two of its specialization: (i) direct control and (ii) teaching of a robotic manipulator, which leads to the development of technological solutions for gesture sensing, detection and classification, which can possibly be applied to other contexts

Robot skill learning through human demonstration and interaction

Nowadays robots are increasingly involved in more complex and less structured tasks. Therefore, it is highly desirable to develop new approaches to fast robot skill acquisition. This research is aimed to develop an overall framework for robot skill learning through human demonstration and interaction. Through low-level demonstration and interaction with humans, the robot can learn basic skills. These basic skills are treated as primitive actions. In high-level learning, the complex skills demonstrated by the human can be automatically translated into skill scripts which are executed by the robot. This dissertation summarizes my major research activities in robot skill learning. First, a framework for Programming by Demonstration (PbD) with reinforcement learning for human-robot collaborative manipulation tasks is described. With this framework, the robot can learn low level skills such as collaborating with a human to lift a table successfully and efficiently. Second, to develop a high-level skill acquisition system, we explore the use of a 3D sensor to recognize human actions. A Kinect based action recognition system is implemented which considers both object/action dependencies and the sequential constraints. Third, we extend the action recognition framework by fusing information from multimodal sensors which can recognize fine assembly actions. Fourth, a Portable Assembly Demonstration (PAD) system is built which can automatically generate skill scripts from human demonstration. The skill script includes the object type, the tool, the action used, and the assembly state. Finally, the generated skill scripts are implemented by a dual-arm robot. The proposed framework was experimentally evaluated