Rafael Lírio Arrais

Abstract
This paper proposes a logistic planner with supplementary 3D spatial representations to enhance and interact with traditional logistic systems on the context of mobile manipulators performing internal logistics operations. By defining a hierarchical structure, the logistic world model, as the central entity synchronized between multiple system components, the reliability and accuracy of the logistic system is strengthened. The proposed approach aims at implementing a robust and intuitive solution for the set-up of mobile manipulator based logistic systems. The logistic planner includes a web based interface for fast setup of the warehouse layout based on robot sensing, as well as the definition of missions for the fleet of robotic systems. © Springer International Publishing AG 2018.

Abstract
The contemporary adoption of Cyber-Physical Systems and improvements in robotic applications in industrial scenarios demands for horizontal integration mechanisms with already existing automation equipment, controlled by PLCs. This paper aims to shorten the gap between the automation and robotics domain, by proposing an Interprocess Communication method to establish interoperability between robotic systems and automation equipment in a reliable and straightforward manner. In particular, this paper introduces a novel approach for linking ROS and IEC 61131-3 by way of shared memory interfaces, enabling and promoting their interactions. Moreover, this paper addresses the applied synchronization mechanism for handling concurrent accesses to the shared memory location, explores data type mapping between ROS and IEC 61131-3, and identifies some practical industrial applications.

Abstract
This paper demonstrates the potential benefits of the integration of robot based sensing and Enterprise Information Systems extended with information about the geometric location and volumetric information of the parts contained in logistic supermarkets. The comparison of this extended world model with hierarchical spatial representations produced by a fleet of robots traversing the logistic supermarket corridors enables the continuous assessment of inconsistencies between reality, i.e., the spatial representations collected from online 3D data, and the modelled information, i.e., the world model. Results show that it is possible to detect inconsistencies reliably and in real time. The proposed approach contributes to the development of more robust and effective Enterprise Information Systems. © 2017 The Society of Manufacturing Engineers

Abstract

Abstract
While bottom-up approaches to object recognition are simple to design and implement, they do not yield the same performance as top-down approaches. On the other hand, it is not trivial to obtain a moderate number of plausible hypotheses to be efficiently verified by top-down approaches. To address these shortcomings, we propose a hybrid top-down bottom-up approach to object recognition where a bottom-up procedure that generates a set of hypothesis based on data is combined with a top-down process for evaluating those hypotheses. We use the recognition of rectangular cuboid shaped objects from 3D point cloud data as a benchmark problem for our research. Results obtained using this approach demonstrate promising recognition performances.