2,675 research outputs found

    Setting the stage ā€“ embodied and spatial dimensions in emerging programming practices.

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    In the design of interactive systems, developers sometimes need to engage in various ways of physical performance in order to communicate ideas and to test out properties of the system to be realised. External resources such as sketches, as well as bodily action, often play important parts in such processes, and several methods and tools that explicitly address such aspects of interaction design have recently been developed. This combined with the growing range of pervasive, ubiquitous, and tangible technologies add up to a complex web of physicality within the practice of designing interactive systems. We illustrate this dimension of systems development through three cases which in different ways address the design of systems where embodied performance is important. The first case shows how building a physical sport simulator emphasises a shift in activity between programming and debugging. The second case shows a build-once run-once scenario, where the fine-tuning and control of the run-time activity gets turned into an act of in situ performance by the programmers. The third example illustrates the explorative and experiential nature of programming and debugging systems for specialised and autonomous interaction devices. This multitude in approaches in existing programming settings reveals an expanded perspective of what practices of interaction design consist of, emphasising the interlinking between design, programming, and performance with the system that is being developed

    Collaborative Task Completion for Simulated Hexapod Robots Using Reinforcement Learning

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    There is growing interest in developing autonomous systems capable of exhibiting collaborative behaviors. Using methods such as reinforcement learning is another way to train multiple robots for collaborative task completion. This study was able to successfully in simulation train multiple hexapod robots to push a target to a designated goal collaboratively. This required each robot to learn how find the target and push that target to a goal. This work suggests that using reinforcement learning for collaborative task completion for hexapod robots may simplify the complexity of the software and improve the decisions that they make

    Team-level programming of drone sensor networks

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    Autonomous drones are a powerful new breed of mobile sensing platform that can greatly extend the capabilities of traditional sensing systems. Unfortunately, it is still non-trivial to coordinate multiple drones to perform a task collaboratively. We present a novel programming model called team-level programming that can express collaborative sensing tasks without exposing the complexity of managing multiple drones, such as concurrent programming, parallel execution, scaling, and failure recovering. We create the Voltron programming system to explore the concept of team-level programming in active sensing applications. Voltron offers programming constructs to create the illusion of a simple sequential execution model while still maximizing opportunities to dynamically re-task the drones as needed. We implement Voltron by targeting a popular aerial drone platform, and evaluate the resulting system using a combination of real deployments, user studies, and emulation. Our results indicate that Voltron enables simpler code and produces marginal overhead in terms of CPU, memory, and network utilization. In addition, it greatly facilitates implementing correct and complete collaborative drone applications, compared to existing drone programming systems

    RAF | A framework for symbiotic agencies in robotic ā€“ aided fabrication

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    The research presented in this paper utilizes industrial robotic arms and new material technologies to model and explore a different conceptual framework for ā€˜robotic-aided fabricationā€™ based on material formation processes, collaboration, and feedback loops. Robotic-aided fabrication as a performative design process needs to develop and demonstrate itself through projects that operate at a discrete level, emphasizing the role of the different agents and prioritizing their relationships over their autonomy. It encourages a process where the robot, human and material are not simply operational entities but a related whole. In the pre-actual state of this agenda, the definition and understanding of agencies and the inventory of their relations is more relevant than their implementation. Three test scenarios are described using human designers, phase-changing materials, and a six-axis industrial robotic arm with an external sensor. The common thread running through the three scenarios is the facilitation of interaction within a digital fabrication process. The process starts with a description of the different agencies and their potentiality before any relation is formed. Once the contributions of each agent are understood they start to form relations with different degrees of autonomy. A feedback loop is introduced to create negotiation opportunities that can result in a rich and complex design process. The paper concludes with speculation on the advantages and possible limitations of semi-organic design methods through the emergence of patterns of interaction between the material, machine and designer resulting in new vistas towards how design is conceived, developed, and realised

    Investigating Human Perceptions of Trust and Social Cues in Robots for Safe Human-Robot Interaction in Human-oriented Environments

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    As robots increasingly take part in daily living activities, humans will have to interact with them in domestic and other human-oriented environments. This thesis envisages a future where autonomous robots could be used as home companions to assist and collaborate with their human partners in unstructured environments without the support of any roboticist or expert. To realise such a vision, it is important to identify which factors (e.g. trust, participantsā€™ personalities and background etc.) that influence people to accept robotsā€™ as companions and trust the robots to look after their well-being. I am particularly interested in the possibility of robots using social behaviours and natural communications as a repair mechanism to positively influence humansā€™ sense of trust and companionship towards the robots. The main reason being that trust can change over time due to different factors (e.g. perceived erroneous robot behaviours). In this thesis, I provide guidelines for a robot to regain human trust by adopting certain human-like behaviours. I can expect that domestic robots will exhibit occasional mechanical, programming or functional errors, as occurs with any other electrical consumer devices. For example, these might include software errors, dropping objects due to gripper malfunctions, picking up the wrong object or showing faulty navigational skills due to unclear camera images or noisy laser scanner data respectively. It is therefore important for a domestic robot to have acceptable interactive behaviour when exhibiting and recovering from an error situation. In this context, several open questions need to be addressed regarding both individualsā€™ perceptions of the errors and robots, and the effects of these on peopleā€™s trust in robots. As a first step, I investigated how the severity of the consequences and the timing of a robotā€™s different types of erroneous behaviours during an interaction may have different impact on usersā€™ attitudes towards a domestic robot. I concluded that there is a correlation between the magnitude of an error performed by the robot and the corresponding loss of trust of the human in the robot. In particular, peopleā€™s trust was strongly affected by robot errors that had severe consequences. This led us to investigate whether peopleā€™s awareness of robotsā€™ functionalities may affect their trust in a robot. I found that peopleā€™s acceptance and trust in the robot may be affected by their knowledge of the robotā€™s capabilities and its limitations differently according the participantsā€™ age and the robotā€™s embodiment. In order to deploy robots in the wild, strategies for mitigating and re-gaining peopleā€™s trust in robots in case of errors needs to be implemented. In the following three studies, I assessed if a robot with awareness of human social conventions would increase peopleā€™s trust in the robot. My findings showed that people almost blindly trusted a social and a non-social robot in scenarios with non-severe error consequences. In contrast, people that interacted with a social robot did not trust its suggestions in a scenario with a higher risk outcome. Finally, I investigated the effects of robotsā€™ errors on peopleā€™s trust of a robot over time. The findings showed that participantsā€™ judgement of a robot is formed during the first stage of their interaction. Therefore, people are more inclined to lose trust in a robot if it makes big errors at the beginning of the interaction. The findings from the Human-Robot Interaction experiments presented in this thesis will contribute to an advanced understanding of the trust dynamics between humans and robots for a long-lasting and successful collaboration

    Using educational robotics in pre-service teacher training : orchestration between an exploration guide and teacher role

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    The proper integration of technology in teaching and learning processes must consider the role of teachers and students, as well as the design of tasks and the context in which they are implemented. Teachersā€™ perceived self-efficacy significantly influences their willingness to integrate educational robotics (ER) into their practice, so initial teacher training should provide opportunities for teachers to participate in structured activities that integrate ER. In this study, a class of pre-service teachers from an initial teacher training programme were provided with their first contact with an ER platform through the use of a simulator. We present the design process of a student exploration guide and teacher guide, developed over three iterative cycles of implementation, assessment and redesign. The analysis of the data collected allowed for improvements in the design of the tasks, the graphic component of the student exploration guide, and more precise indications for the teacherā€™s actions. The main contribution of this study is the chain orchestration between the simulator, student exploration guide and teacher guide, which allowed pre-service teachers to solve a set of challenges of increasing complexity, thereby progressively decreasing their difficulties and contributing to an adequate integration of ER in their future teaching practices.info:eu-repo/semantics/publishedVersio
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