Abstract
The shotcrete process has been extensively used for many years in different civil and mining operations. Nevertheless, it is still either applied by an operator which controls the shotcrete nozzle manually or through a remote control. In either case, the operation is entirely controlled by the operator. Automating the shotcrete process involves developments in different parts of the process, such as the tunnel scanning for 3D model generation and the shotcrete path automatic generation and execution. This paper describes the work developed for this last part, namely the automatic generation and execution of a shotcrete path, given the mesh of a tunnel and a set of input parameters, for application in railway tunnels. The developed path also considers specificities of the concrete projection process, such as the uncontrolled flow variation due to the pumping systems, generating a trajectory that aims at minimizing this effect. Results are shown using a realistic simulator and an uneven railway tunnel, using an industrial robot mounted on a railway wagon.

Abstract
This paper describes the relevant research activities that are being carried out on the development of a novel shotcrete technology capable of applying, autonomously and in real time, fibre reinforced shotcrete (FRS) with tailored properties regarding the optimum structural strengthening of railway tunnels (RT). This technique allows to apply fibre reinforced concrete (FRC) of strain softening (SSFRC) and strain hardening (SHFRC) according to a multi -level advanced numerical simulation that considers the relevant nonlinear features of these FRC, as well as their interaction with the surrounding soil, for an intended strengthening performance of the RT. Building information modelling (BIM) is used for assisting on the development of data files of the involved design software, integrating geometric assessment of a RT, damages from inspection and diagnosis, and the characteristics of the FRS strengthening solution. A dedicated computational tool was developed to design FRC with target properties. The preliminary experimental results on the evaluation of the relevant mechanical properties of the FRS are presented and discussed, as well as the experimental tests on the bond between FRS and current substrates found in RT. Representative numerical simulations were performed to demonstrate the structural performance of the proposed FRS -based strengthening technique. Computational tools capable of assuring, in real time, the aimed thickness of the layers forming the FRS strengthening shell were also developed. The first generation of a mechanical device for controlling the amount of fibres to be added, in real time, to the FRS mixture was conceived, built and tested. A mechanism is also being developed to improve the fibre distribution during its introduction through the mechanical device to avoid fibre balling. This work describes the relevant achievements already attained, as introduces the planned future initiatives in the scope of this project.

Abstract
This paper describes a topological navigation system, based on the description of key-places by a reduced number of parameters that represent images associated to specific locations in configuration space, and the application of the developed system to robotic soccer, through the implementation of the developed algorithms to RoboCup Middle-Size League (MSL) robots, under the scope of the SocRob project (Soccer Robots or Society of Robots). A topological map is associated with a graph, where each node corresponds to a key-place. Using this approach, navigation is reduced to a graph path search. Principal Components Analysis was used to represent key-places from pre-acquired images and to recognize them at navigation time. The method revealed a promising performance navigating between key-places and proved to adapt to different graphs. Furthermore, it leads to a robot programming language based on qualitative descriptions of the target locations in configuration space (e.g., Near Blue Coal with the Goal on its Left). Simulation results of the method application are presented, using a realistic simulator.

Abstract

Abstract
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

Abstract
This paper introduces Petri net (PN) based models of cooperative robotic tasks, namely those involving the coordination of two or more robots, thus requiring the exchange of synchronisation messages, either using explicit (e.g., wireless) or implicit (e.g., vision-based observation of teammates) communication. In the models, PN places represent primitive actions, subtasks and predicates set by sensor readings and communicated messages. Events are associated to PN transitions. The PN models can be used for task planning, plan execution and plan analysis. Different PN views enable the analysis of different properties. In this work we focus on plan analysis, namely on properties such as boundedness and liveness, corresponding to checking if resources usage is stable and plans have no deadlocks, as well as on stochastic performance, concerning the plan success probability. One novel feature of our work is that the analysis consists of composing several small action PN models with environment PN models, leading to a closed loop robot team/environment analysis methodology. Examples of application to simulated robotic soccer scenarios are presented. Copyright