Abstract
Usually the Industrial Automatic Guide Vehicles (AGVs) have two kind of lasers. One for navigation on the top and others for obstacle detection (security lasers). Recently, security lasers extended its output data with obstacle distance (contours) and reflectivity, that allows the development of a novel localization system based on a security laser. This paper addresses a localization system that avoids a dedicated laser scanner reducing the implementations cost and robot size. Also, performs a tracking system with precision and robustness that can operate AVGs in an industrial environment. Artificial beacons detection algorithm combined with a Kalman filter and outliers rejection method increase the robustness and precision of the developed system. A comparison between the presented approach and a commercial localization system for industry is presented. Finally, the proposed algorithms were tested in an industrial application under realistic working conditions.

Abstract
The organizational struck of the companies in the biomass energy sector, regarding the supply chain management, services, can be greatly improved through the use of software decision support. tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. to particular, this work presents the modelling a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided.

Abstract
The fast development in the field of Robotics has become more and more notorious throughout the past years. Nowadays technology in general and robotics in particular search for modular and flexible applications in order to answer the demands of a wide range of problems in an efficient manner. However there are several robotic solutions already implemented and some still available to be implemented that do not use modular tools. The Robotic Operative System (ROS) appears to be the unifying tool to connect all software developers allowing any developer in both education and professional areas to be able to develop complex software using small iterations of simple software. Still, despite of the several robotic solutions available, there are several robots that do not use the Robotic Operative System (ROS) and have limitations in terms of autonomously correct errors during their tasks. Moreover when developing new robots and software to the robotic area there is an important aspect to be consider: the selection of the methodology to be used. In this paper, it will be presented a challenge propose to college students using the ROS framework in a common robotic problem, the pick and place operations. The main aim for this challenge is to show how to produce software in a modular and flexible way using ROS can prompt the rapid development in all robotic applications. Moreover the challenge had one particular real end, the European Robotics Challenges (EUROC) - a challenge aiming to develop a robot for shop floor logistics and manipulation. Furthermore this challenge was based in the three tiers paradigm: 1 recognition/sensing tier, 2-effector tier and 3-the control tier and was built using the ROS framework. Another advantage of our proposed pick and place approach is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to the insertion of an adaptive control tier in our methodology. The proposed approach can be valuable in the field of robotics and can be potentially applied in multiple tasks and it has already allowed us to advance to the next stage of EUROC. Based on this information, the challenge propose to the students will primarily reinforce the need for modular and flexible software while showing how the ROS framework can be a simple tool for present and future developments.

Abstract
Purpose - Streamlining automated processes is currently undertaken by developing optimization methods and algorithms for robotic manipulators. This paper aims to present a new approach to improve streamlining of automatic processes. This new approach allows for multiple robotic manipulators commonly found in the industrial environment to handle different scenarios, thus providing a high-flexibility solution to automated processes. Design/methodology/approach - The developed system is based on a spatial discretization methodology capable of describing the surrounding environment of the robot, followed by a novel path-planning algorithm. Gazebo was the simulation engine chosen, and the robotic manipulator used was the Universal Robot 5 (UR5). The proposed system was tested using the premises of two robotic challenges: EuRoC and Amazon Picking Challenge. Findings - The developed system was able to identify and describe the influence of each joint in the Cartesian space, and it was possible to control multiple robotic manipulators safely regardless of any obstacles in a given scene. Practical implications - This new system was tested in both real and simulated environments, and data collected showed that this new system performed well in real- life scenarios, such as EuRoC and Amazon Picking Challenge. Originality/ value - The new proposed approach can be valuable in the robotics field with applications in various industrial scenarios, as it provides a flexible solution for multiple robotic manipulator path and motion planning.

Abstract
In this paper we present a new concept of robot-dependent reachability map (RDReachMap) for mobile platforms. In heterogeneous multi-robot systems, the reachability limit of robots motion and actuation must be considered when assigning tasks to them. We created an algorithm that generates those reachability maps, separating regions that can be covered by a robot from the unreachable ones, using morphological operations. Our method is dependent on the robot position, and is parameterized with the robot's size and actuation radius. For this purpose we introduce a new technique, the partial morphological closing operation. The algorithm was tested both in simulated and real environment maps. We also present a common problem of multi robot routing, which we solve with a planner that uses our reachability maps in order to generate valid plans. We contribute a heuristic that generates paths for two robots using the reachability concept.

Abstract
Aim of study: This work aims to provide an overview of Model Predictive Controllers (MPC) applications in supply chains, to describe the forest-based supply chain and to analyse the potential use and benefits of MPC in a case study concerning a biomass supply chain. Area of study: The proposed methods are being applied to a company located in Finland. Material and methods: Supply chains are complex systems where actions and partners' coordination influence the whole system performance. The increase of competitiveness and need of quick responses to the costumers implies the use of efficient management techniques. The control theory, particularly MPC, has been successfully used as a supply chain management tool. MPC is able to deal with dynamic interactions between the partners and to globally optimize the supply chain performance in the presence of disturbances. However, as far as is authors' knowledge, there are no applications of this methodology in the forest-based supply chains. This work proposes a control architecture to improve the performance of the forest supply chain. The controller is based on prediction models which are able to simulate the system and deal with disturbances. Main results: The preliminary results enable to evaluate the impacts of disturbances in the supply chain. Thus, it is possible to react beforehand, controlling the schedules and tasks' allocation, or alert the planning level in order to generate a new plan. Research highlights: Overview of MPC applications in supply chains; forest-based supply chain description; case study presentation: wood biomass supply chain for energy production; MPC architecture proposal to decrease the operation times.