Learning robotics: a review

Purpose of Review: With the growing interest for STEM/STEAM, new robotic platforms are being created with different characteristics, extras and options. There are so many diverse solutions, that it is difficult for a teacher/student to choose the ideal one. This paper intends to provide an analysis to the most common robotic platforms existent on the market. The same is happening regarding robotic events all around the world, with objectives so distinctive, and with complexity from easy to very difficult. This paper also describes some of those events which occur in many countries. Recent Findings: As the literature is showing, there has been a visible effort from schools and educators to teach robotics from very young ages, not only because robotics is the future, but also as a tool to teach STEM/STEAM areas. But as time progresses, the options for the right platforms also evolves making difficult to choose among them. Some authors opt to first choose a robotic platform and carry on from there. Others choose first a development environment and then look for which robots can be programmed from it. Summary: An actual review on learning robotics is here presented, firstly showing some literature background on history and trends of robotic platforms used in education in general, the different development environments for robotics and finishing on competitions and events. A comprehensive characterization list of robotic platforms along with robotic competitions and events is also shown

Petri net plans: a formal model for representation and execution of multi-robot plans

The aim of this paper is to describe a novel representation framework for high level robot and multi-robot programming, called Petri Net Plans (PNP), that allows for representing all the action features that are needed for describing complex plans in dynamic environments. We provide a sound and complete execution algorithm for PNPs based on the semantics of Petri nets. Moreover, we show that multi-robot PNPs allow for a sound and complete distributed execution algorithm, given that a reliable communication channel is provided. PNPs have been used for describing effective plans for actual robotic agents which inhabit dynamic, partially observable and unpredictable environments, and experimented in different application scenarios. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved

Petri Net Plans A Formal Model for Representation and Execution of Multi-Robot Plans

The aim of this paper is to describe a novel representation framework for high level robot and multi-robot programming, called Petri Net Plans (PNP), that allows for representing all the action features that are needed for describing complex plans in dynamic environments. We provide a sound and complete execution algorithm for PNPs based on the semantics of Petri nets. Moreover, we show that multi-robot PNPs allow for a sound and complete distributed execution algorithm, given that a reliable communication channel is provided. PNPs have been used for describing effective plans for actual robotic agents which inhabit dynamic, partially observable and unpredictable environments, and experimented in different application scenarios. 1

A Robotic Soccer Passing Task Using Petri Net Plans (Demo Paper)

No abstract availabl

Delivery of an anti-transthyretin Nanobody to the brain through intranasal administration reveals transthyretin expression and secretion by motor neurons

Transthyretin (TTR) is a transport protein of retinol and thyroxine in serum and CSF, which is mainly secreted by liver and choroid plexus, and in smaller amounts in other cells throughout the body. The exact role of TTR and its specific expression in Central Nervous System (CNS) remains understudied. We investigated TTR expression and metabolism in CNS, through the intranasal and intracerebroventricular delivery of a specific anti-TTR Nanobody to the brain, unveiling Nanobody pharmacokinetics to the CNS. In TTR deficient mice, we observed that anti-TTR Nanobody was successfully distributed throughout all brain areas, and also reaching the spinal cord. In wild-type mice, a similar distribution pattern was observed. However, in areas known to be rich in TTR, reduced levels of Nanobody were found, suggesting potential targetmediated effects. Indeed, in wild-type mice, the anti-TTR Nanobody was specifically internalized in a receptor-mediated process, by neuronal-like cells, which were identified as motor neurons. Whereas in KO TTR mice Nanobody was internalized by all cells, for late lysosomal degradation. Moreover, we demonstrate that in vivo motor neurons also actively synthesize TTR. Finally, in vitro cultured primary motor neurons were also found to synthesize and secrete TTR into culture media. Thus, through a novel intranasal CNS distribution study with an anti-TTR Nanobody, we disclose a new cell type capable of synthesizing TTR, which might be important for the understanding of the physiological role of TTR, as well as in pathological conditions where TTR levels are altered in CSF, such as amyotrophic lateral sclerosisThis work was supported by FEDER funds through the Operational Competitiveness Programme – COMPETE, by national funding from the Portuguese Foundation for Science and Technology (FCT) under the project PEst-C/SAU/LA0001/2011, QREN Brainiac 13141 and a post-doctoral fellowship (SFRH/BPD/84178/2012) to João Gomes. The authors acknowledge Paul Moreira for support in recombinant protein production and Paula Gon©calves, for tissue processing. The authors of the manuscript have the following potential competing interest: IC, HS, PV and, AW (left in 04/2012) were employees of ABLYNX at the time of work development. The other authors have no conflict of interests. The anti-TTR Nanobody discovery and characterization, as well as the quantification of Nanobodies in brain samples was performed by ABLYNX, whereas Nanobody delivery, tissue imaging, biochemistry processing as well as cellular cultures and data processing was performed by IBMC

Delivery of an anti-transthyretin Nanobody to the brain through intranasal administration reveals transthyretin expression and secretion by motor neurons

Transthyretin (TTR) is a transport protein of retinol and thyroxine in serum and CSF, which is mainly secreted by liver and choroid plexus, and in smaller amounts in other cells throughout the body. The exact role of TTR and its specific expression in Central Nervous System (CNS) remains understudied. We investigated TTR expression and metabolism in CNS, through the intranasal and intracerebroventricular delivery of a specific anti-TTR Nanobody to the brain, unveiling Nanobody pharmacokinetics to the CNS. In TTR deficient mice, we observed that anti-TTR Nanobody was successfully distributed throughout all brain areas, and also reaching the spinal cord. In wild-type mice, a similar distribution pattern was observed. However, in areas known to be rich in TTR, reduced levels of Nanobody were found, suggesting potential targetmediated effects. Indeed, in wild-type mice, the anti-TTR Nanobody was specifically internalized in a receptor-mediated process, by neuronal-like cells, which were identified as motor neurons. Whereas in KO TTR mice Nanobody was internalized by all cells, for late lysosomal degradation. Moreover, we demonstrate that in vivo motor neurons also actively synthesize TTR. Finally, in vitro cultured primary motor neurons were also found to synthesize and secrete TTR into culture media. Thus, through a novel intranasal CNS distribution study with an anti-TTR Nanobody, we disclose a new cell type capable of synthesizing TTR, which might be important for the understanding of the physiological role of TTR, as well as in pathological conditions where TTR levels are altered in CSF, such as amyotrophic lateral sclerosisThis work was supported by FEDER funds through the Operational Competitiveness Programme – COMPETE, by national funding from the Portuguese Foundation for Science and Technology (FCT) under the project PEst-C/SAU/LA0001/2011, QREN Brainiac 13141 and a post-doctoral fellowship (SFRH/BPD/84178/2012) to João Gomes. The authors acknowledge Paul Moreira for support in recombinant protein production and Paula Gon©calves, for tissue processing. The authors of the manuscript have the following potential competing interest: IC, HS, PV and, AW (left in 04/2012) were employees of ABLYNX at the time of work development. The other authors have no conflict of interests. The anti-TTR Nanobody discovery and characterization, as well as the quantification of Nanobodies in brain samples was performed by ABLYNX, whereas Nanobody delivery, tissue imaging, biochemistry processing as well as cellular cultures and data processing was performed by IBMC

Interacting with team oriented plans in multi-robot systems

Team oriented plans have become a popular tool for operators to control teams of autonomous robots to pursue complex objectives in complex environments. Such plans allow an operator to specify high level directives and allow the team to autonomously determine how to implement such directives. However, the operators will often want to interrupt the activities of individual team members to deal with particular situations, such as a danger to a robot that the robot team cannot perceive. Previously, after such interrupts, the operator would usually need to restart the team plan to ensure its success. In this paper, we present an approach to encoding how interrupts can be smoothly handled within a team plan. Building on a team plan formalism that uses Colored Petri Nets, we describe a mechanism that allows a range of interrupts to be handled smoothly, allowing the team to efficiently continue with its task after the operator intervention. We validate the approach with an application of robotic watercraft and show improved overall efficiency. In particular, we consider a situation where several platforms should travel through a set of pre-specified locations, and we identify three specific cases that require the operator to interrupt the plan execution: (i) a boat must be pulled out; (ii) all boats should stop the plan and move to a pre-specified assembly position; (iii) a set of boats must synchronize to traverse a dangerous area one after the other. Our experiments show that the use of our interrupt mechanism decreases the time to complete the plan (up to 48 % reduction) and decreases the operator load (up to 80 % reduction in number of user actions). Moreover, we performed experiments with real robotic platforms to validate the applicability of our mechanism in the actual deployment of robotic watercraft