Teaching humanoid robotics by means of human teleoperation through RGB-D sensors

This paper presents a graduate course project on humanoid robotics offered by the University of Padova. The target is to safely lift an object by teleoperating a small humanoid. Students have to map human limbs into robot joints, guarantee the robot stability during the motion, and teleoperate the robot to perform the correct movement. We introduce the following innovative aspects with respect to classical robotic classes: i) the use of humanoid robots as teaching tools; ii) the simplification of the stable locomotion problem by exploiting the potential of teleoperation; iii) the adoption of a Project-Based Learning constructivist approach as teaching methodology. The learning objectives of both course and project are introduced and compared with the students\u2019 background. Design and constraints students have to deal with are reported, together with the amount of time they and their instructors dedicated to solve tasks. A set of evaluation results are provided in order to validate the authors\u2019 purpose, including the students\u2019 personal feedback. A discussion about possible future improvements is reported, hoping to encourage further spread of educational robotics in schools at all levels

Horizon Report 2009

El informe anual Horizon investiga, identifica y clasifica las tecnologías emergentes que los expertos que lo elaboran prevén tendrán un impacto en la enseñanza aprendizaje, la investigación y la producción creativa en el contexto educativo de la enseñanza superior. También estudia las tendencias clave que permiten prever el uso que se hará de las mismas y los retos que ellos suponen para las aulas. Cada edición identifica seis tecnologías o prácticas. Dos cuyo uso se prevé emergerá en un futuro inmediato (un año o menos) dos que emergerán a medio plazo (en dos o tres años) y dos previstas a más largo plazo (5 años)

Digital strategy

The digital strategy presents a framework for digital business transformation and an inevitable requirement for achieving success in a digital world. The pace of change and innovation in digital businesses is not slowing down and today almost no business can ignore its digital aspect but what drives digital transformation is a strategy, not technology. Therefore, the ability to digitally reimagine the business is determined by a clear digital strategy, and the leaders able to implement it in the organization. Inertia is not the solution to uncertainty. Having a clear vision, goals and objectives help organizations to reduce this ambiguity and adapt to an everchanging digital environment. Agile outperforms the traditional approach and new, innovative organizations replace incumbents that do not adapt fast enough in a process known as creative destruction

The organization of interaction design pattern languages alongside the design process

This work explores the possibility of taking the structural characteristics of approaches to interaction design as a basis for the organization of interaction design patterns. The Universal Model of the User Interface (Baxley, 2003) is seen as well suited to this; however, in order to cover the full range of interaction design patterns the model had to be extended slightly. Four existing collections of interaction design patterns have been selected for an analysis in which the patterns have been mapped onto the extended model. The conclusion from this analysis is that the use of the model supports the process of building a pattern language, because it is predictive and helps to complete the language. If several pattern writers were to adopt the model, a new level of synergy could be attained among these pattern efforts. A concluding vision would be that patterns could be transferred freely between pattern collections to make them as complete as possibl

LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms

Continual Learning (CL) allows applications such as user personalization and household robots to learn on the fly and adapt to context. This is an important feature when context, actions, and users change. However, enabling CL on resource-constrained embedded systems is challenging due to the limited labeled data, memory, and computing capacity. In this paper, we propose LifeLearner, a hardware-aware meta continual learning system that drastically optimizes system resources (lower memory, latency, energy consumption) while ensuring high accuracy. Specifically, we (1) exploit meta-learning and rehearsal strategies to explicitly cope with data scarcity issues and ensure high accuracy, (2) effectively combine lossless and lossy compression to significantly reduce the resource requirements of CL and rehearsal samples, and (3) developed hardware-aware system on embedded and IoT platforms considering the hardware characteristics. As a result, LifeLearner achieves near-optimal CL performance, falling short by only 2.8% on accuracy compared to an Oracle baseline. With respect to the state-of-the-art (SOTA) Meta CL method, LifeLearner drastically reduces the memory footprint (by 178.7x), end-to-end latency by 80.8-94.2%, and energy consumption by 80.9-94.2%. In addition, we successfully deployed LifeLearner on two edge devices and a microcontroller unit, thereby enabling efficient CL on resource-constrained platforms where it would be impractical to run SOTA methods and the far-reaching deployment of adaptable CL in a ubiquitous manner. Code is available at https://github.com/theyoungkwon/LifeLearner.Comment: Accepted for publication at SenSys 202