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
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.

Abstract
Purpose - This paper aims to address a mobile robot localization system that avoids using a dedicated laser scanner, making it possible to reduce implementation costs and the robot's size. The system has enough precision and robustness to meet the requirements of industrial environments. Design/methodology/approach - Using an algorithm for artificial beacon detection combined with a Kalman Filter and an outlier rejection method, it was possible to enhance the precision and robustness of the overall localization system. Findings - Usually, industrial automatic guide vehicles feature two kinds of lasers: one for navigation placed on top of the robot and another for obstacle detection (security lasers). Recently, security lasers extended their output data with obstacle distance (contours) and reflectivity. These new features made it possible to develop a novel localization system based on a security laser. Research limitations/implications - Once the proposed methodology is completely validated, in the future, a scheme for global localization and failure detection should be addressed. Practical implications - This paper presents a comparison between the presented approach and a commercial localization system for industry. The proposed algorithms were tested in an industrial application under realistic working conditions. Social implications - The presented methodology represents a gain in the effective cost of the mobile robot platform, as it discards the need for a dedicated laser for localization purposes. Originality/value - This paper presents a novel approach that benefits from the presence of a security laser on mobile robots (mandatory sensor when considering industrial applications), using it simultaneously with other sensors, not only to guarantee safety conditions during operation but also to locate the robot in the environment. This paper is also valuable because of the comparison made with a commercialized system, as well as the tests conducted in real industrial environments, which prove that the approach presented is suitable for working under these demanding conditions.