When it comes to intelligent and informative writers, political poetry is a furor. It is also natural, if we take into account that people have less and less experience, that traditions and beliefs die, while their ideologies and political correctness are gaining ground. So what about the new literature, if not about small obsessions, narcissism and boldness? Only geniuses can escape the fold of t

Margento's "computationally assembled" anthology (Raluca Tanasescu, Chris Tanasescu, Marius Surleac, Vaibhav Kesarwani, Diana Inkpen) has a bilingual title with different appearances: once "US" Poets Foreign Poets, then "New Poets". The first time is "foreign", the second time novelty. It is clear that the volume appearing at FrActalia Press in 2018 is a step further on the development of digital

During the last decades, the methods for intuitive task level programming of robots have become a fundamental point of interest for industrial application. The paper in hand presents SkiROS (Skill-based Robot Operating System) a novel software architecture based on the skills paradigm. The skill paradigm has already been used and tested within the FP7 project TAPAS, and we are going to use it in s

During the last decades, methods for intuitive task level robot programming have become a fundamental point of interest for industrial applications. A robot programming framework is needed to facilitate task-level programming of mobile manipulators, e.g. by providing the robot with a set of movement primitives and skills. Robot skills have already been used and tested successfully within the FP7 p

Cognitive robots have started to find their way into manufacturing halls. However, the full potential of these robots can only be exploited through an integration into the automation pyramid so that the system is able to communicate with the manufacturing execution system (MES). Integrating the robot with the MES allows the robot to get access to manufacturing environment and process data so that Cognitive robots have started to find their way into manufacturing halls. However, the full potential of these robots can only be exploited through an integration into the automation pyramid so that the system is able to communicate with the manufacturing execution system (MES). Integrating the robot with the MES allows the robot to get access to manufacturing environment and process data so that

The development of cognitive robots in ROS still lacks the support of some key components: a knowledge integration framework and a framework for autonomous mission execution. In this research chapter, we will discuss our skill-based platform SkiROS, that was developed on top of ROS in order to organize robot knowledge and its behavior. We will show how SkiROS offers the possibility to integrate diThe development of cognitive robots in ROS still lacks the support of some key components: a knowledge integration framework and a framework for autonomous mission execution. In this research chapter, we will discuss our skill-based platform SkiROS, that was developed on top of ROS in order to organize robot knowledge and its behavior. We will show how SkiROS offers the possibility to integrate di

The requirement of flexibility in the modern industries demands robots that can be efficiently and quickly adapted to different tasks. A way to achieve such a flexible programming paradigm is to instruct robots with task goals and leave planning algorithms to deduct the correct sequence of actions to use in the specific context. A common approach is to connect the skills that realize a semanticallhe requirement of flexibility in the modern industries demands robots that can be efficiently and quickly adapted to different tasks. A way to achieve such a flexible programming paradigm is to instruct robots with task goals and leave planning algorithms to deduct the correct sequence of actions to use in the specific context. A common approach is to connect the skills that realize a semantically

Task level programming based on skills has often been proposed as a mean to decrease programming complexity of industrial robots. Several models are based on encapsulating complex motions into self-contained primitive blocks. A semantic skill is then defined as a deterministic sequence of these primitives. A major limitation is that existing frameworks do not support the coordination of concurrentTask level programming based on skills has often been proposed as a mean to decrease programming complexity of industrial robots. Several models are based on encapsulating complex motions into self-contained primitive blocks. A semantic skill is then defined as a deterministic sequence of these primitives. A major limitation is that existing frameworks do not support the coordination of concurrent

In this paper we present a novel 3D sensing approach for industrial bin-picking applications that is low-cost, fast and precise. The system uses a simple laser-line emitter. While a robot arm moves the object through the laser light, a synchronized camera captures the laser line image on the object. A full point cloud as well as an edge point cloud suitable for subsequent pose estimation is genera

Despite the large scientific interest on robot learning forobject picking tasks, the research on object placingis too limited. Commonly, placing is simplistically consideredas a trivial task, but real life manipulation problems indicatethe exact opposite. A placing task can have different levels ofcomplexity, ranging from the simplest tabletop placing of anobject, to more complex cases such as loa

In certain cases analytical derivation of physics-based models of robots is difficult or even impossible. A potential workaround is the approximation of robot models from sensor data-streams employing machine learning approaches. In this paper, the inverse dynamics models are learned by employing a novel real-time deep learning algorithm. The algorithm exploits the methods of self-organized learni

In certain cases analytical derivation of physicsbased models of robots is difficult or even impossible. A potential workaround is the approximation of robot models fromsensor data-streams employing machine learning approaches.In this paper, the inverse dynamics models are learned byemploying a learning algorithm, introduced in [1], which isbased on reservoir computing in conjunction with self-org