Evaluating exemplary training accelerators for Programming-by-Demonstration

Hulin, Thomas; Schmirgel, Volker; Yechiam, Eldad; Zimmermann, Uwe E.; Preusche, Carsten; Pohler, Gloria

doi:10.1109/roman.2010.5598611

Cited by 11 publications

(10 citation statements)

References 14 publications

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“…Mobile learning or, simply, m-learning is the didactic-pedagogical expression used to designate a new educational "paradigm" based on the use of mobile technologies [58]. Also, McGreal [55] adds that "m-learning happens in [50], [76], [17], [52], [51], [8], [28], [27], [64], [32], [37], [80], [62], [7], [31], [45], [18], [30], [20] Not mentioned [74], [70], [9] Situated learning [33], [67], [39] Cognitive theory of multimedia learning and cognitive load theory [42], [82] Cognitive load theory [73], [39] Learning styles theory [35], [38] Mobile learning context in which it is needed and relevant and is situated within the active cognitive processes of individual and groups of learners. " Thus, it takes advantage of the widely available mobile devices to provide access to learning anywhere and anytime, which changes many paradigms of traditional education.…”

Section: Fig 4 Papers According To the Design Methodologymentioning

confidence: 99%

Perspectives on how to evaluate augmented reality technology tools for education: a systematic review

et al. 2019

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Education has benefited from augmented reality's (AR) potential to promote interactive experiences both inside and outside the classroom. A systematic review was conducted on how AR's impact in the learning process has been evaluated. We selected papers from 2009 to 2017 in three databases, IEEE, ACM, and Science Direct, using an open-source crawler, and in one Brazilian Conference, SBIE. We followed the PRISMA protocol. Forty-five works were selected and used to extract data for our research. They were also analyzed according to quantitative and qualitative criteria. The results from all the papers are available in an online database. Results evidenced an increase in the number of papers evaluating the AR's impact in education. They also showed that AR has been applied in different areas and contexts. Most papers reported positive outcomes as a result of AR insertion. However, most studies lacked the involvement of the teacher and the use of multiple metrics to evaluate educational gains.

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Section: Fig 4 Papers According To the Design Methodologymentioning

confidence: 99%

Perspectives on how to evaluate augmented reality technology tools for education: a systematic review

et al. 2019

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“…Most robot skill acquisition approaches focussed on trajectory learning, but recently, a growing interest has emerged toward extending this learning problem to the joint acquisition of movement, coordination and compliance [3,33,34,35,6,36]. Some skills remain difficult to transfer from demonstrations.…”

Section: Pancake Flipping Experimentsmentioning

confidence: 99%

“…While some tasks can most successfully be transferred by programming by demonstration (PbD) [1,2,3], other tasks can more effectively be acquired by reinforcement learning (RL) [4,5,6]. Often, the efficiency lies in the interconnections of these imitation and self-improvement strategies.…”

Section: Introductionmentioning

confidence: 99%

Compliant skills acquisition and multi-optima policy search with EM-based reinforcement learning

Calinon

Kormushev

Caldwell

2013

Robotics and Autonomous Systems

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The democratization of robotics technology and the development of new actuators progressively bring robots closer to humans. The applications that can now be envisaged drastically contrast with the requirements of industrial robots. In standard manufacturing settings, the criterions used to assess performance are usually related to the robot's accuracy, repeatability, speed or stiffness. Learning a control policy to actuate such robots is characterized by the search of a single solution for the task, with a representation of the policy consisting of moving the robot through a set of points to follow a trajectory. With new environments such as homes and offices populated with humans, the reproduction performance is portrayed differently. These robots are expected to acquire rich motor skills that can be generalized to new situations, while behaving safely in the vicinity of users. Skills acquisition can no longer be guided by a single form of learning, and must instead combine different approaches to continuously create, adapt and refine policies. The family of search strategies based on expectation-maximization (EM) looks particularly promising to cope with these new requirements. The exploration can be performed directly in the policy parameters space, by refining the policy together with exploration parameters represented in the form of covariances. With this formulation, RL can be extended to a multi-optima search problem in which several policy alternatives can be considered. We present here two applications exploiting EM-based exploration strategies, by considering parameterized policies based on dynamical systems, and by using Gaussian mixture models for the search of multiple policy alternatives.

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“…By altering the arrows' rotating direction and arrow width, the direction and magnitude of the respective joint parameter can be intuitively presented. They were originally designed to display the proximity to robot singularities [14]. For torque controlled robots it is especially useful to map the torque error of commanded and measured joint torques to the arrows, because first this difference indicates the direction and amount of acceleration of the robot joint, and second it helps detecting possible errors in the robotic system, either in the controller or the sensors.…”

Section: Visualizing Joint Parametersmentioning

confidence: 99%

Interactive Features for Robot Viewers

Hulin

Hertkorn

Preusche

2012

Intelligent Robotics and Applications

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Abstract. Robot viewers are an important tool for robot developers, programmers and users. This article presents interactive visual features that can be used for robot viewers, including rotating arrows for torque controlled serial robots and special positioned textfields for numerically displaying joint parameters. The presented features support intuitive interaction modes such that the displayed content can be switched or their visibility can be toggled. With these features the DLR SeRo-Viewer has been developed, which aims at minimizing the efforts for integrating new robots in the visualization system, and at the same time being flexible enough to visualize various robotic systems. The SeRo-Viewer has already been successfully applied on several robotic systems.

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Evaluating exemplary training accelerators for Programming-by-Demonstration

Cited by 11 publications

References 14 publications

Perspectives on how to evaluate augmented reality technology tools for education: a systematic review

Perspectives on how to evaluate augmented reality technology tools for education: a systematic review

Compliant skills acquisition and multi-optima policy search with EM-based reinforcement learning

Interactive Features for Robot Viewers

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