Browsing by Author "Limeira, Marcelo A."
Now showing 1 - 6 of 6
Results Per Page
Sort Options
- ARENA—augmented reality to enhanced experimentation in smart warehousesPublication . Piardi, Luis; Kalempa, Vivian Cremer; Limeira, Marcelo A.; Oliveira, Andre Schneider; Leitão, PauloThe current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems and failures that may only exist in real situations. This work presents an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements. The concept of ARENA introduces a novel approach to realistic and immersive experimentation in industrial environments, aiming to evaluate new technologies aligned with the Industry 4.0. The proposed method consists of a small-scale warehouse, inspired in a real scenario characterized in this paper, managing by a group of autonomous forklifts, fully interconnected, which are embodied by a swarm of tiny robots developed and prepared to operate in the small scale scenario. The AR is employed to enhance the capabilities of swarm robots, allowing box handling and virtual forklifts. Virtual laser range finders (LRF) are specially designed as segmentation of a global RGB-D camera, to improve robot perception, allowing obstacle avoidance and environment mapping. This infrastructure enables the evaluation of new strategies to improve manufacturing productivity, without compromising the production by automation faults.
- Augmented reality system for multi-robot experimentation in warehouse logisticsPublication . Limeira, Marcelo A.; Piardi, Luis; Kalempa, Vivian Cremer; Schneider, André; Leitao, PauloThe application of tools as augmented reality has been developing innovative solutions for the industrial scenario. In this context, this work presents an industrial plant of a warehouse, where augmented reality is used to represent virtual loads to be transported by multiple small mobile robots. The results promote an application developed in ROS, with virtual and real objects sharing the same environment, producing an excellent scenario to development and experimentation to new approaches for automation in warehouses or smart factories.
- DepthLiDAR: active segmentation of environment depth map into mobile sensorsPublication . Limeira, Marcelo A.; Piardi, Luis; Kalempa, Vivian Cremer; Leitão, Paulo; Oliveira, Andre SchneiderThis paper presents a novel approach for creating virtual LiDAR scanners through the active segmentation of point clouds. The method employs top-view point cloud segmentation in virtual LiDAR sensors that can be applied to the intelligent behavior of autonomous agents. Segmentation is correlated with the visual tracking of the agent for localization in the environmentand point cloud. Virtual LiDARsensors with different characteristicsand positions can then be generated. Thismethod is referred to as the DepthLiDAR approach, and is rigorously evaluated to quantify its performance and determine its advantages and limitations. An extensive set of experiments is conducted using real and virtual LiDAR sensors to compare both approaches. The objective is to propose a novel method to incorporate spatial perception in warehouses, aiming to achieve Industry 4.0. Thus, it is tested in a low-scale warehouse to incorporate realistic features. The analysis of the experiments shows a measurement improvement of 52.24% compared to the conventional LiDAR.
- Multi-robot preemptive task scheduling with fault recovery: a novel approach to automatic logistics of smart factoriesPublication . Kalempa, Vivian Cremer; Piardi, Luis; Limeira, Marcelo A.; Oliveira, Andre SchneiderThis paper presents a novel approach for Multi-Robot Task Allocation (MRTA) that introduces priority policies on preemptive task scheduling and considers dependencies between tasks, and tolerates faults. The approach is referred to as Multi-Robot Preemptive Task Scheduling with Fault Recovery (MRPF). It considers the interaction between running processes and their tasks for management at each new event, prioritizing the more relevant tasks without idleness and latency. The benefit of this approach is the optimization of production in smart factories, where autonomous robots are being employed to improve efficiency and increase flexibility. The evaluation of MRPF is performed through experimentation in small-scale warehouse logistics, referred to as Augmented Reality to Enhanced Experimentation in Smart Warehouses (ARENA). An analysis of priority scheduling, task preemption, and fault recovery is presented to show the benefits of the proposed approach.
- Multi-robot task scheduling for consensus-based fault-resilient intelligent behavior in smart factoriesPublication . Kalempa, Vivian Cremer; Piardi, Luis; Limeira, Marcelo A.; Oliveira, Andre SchneiderIn smart factories, several mobile and autonomous robots are being utilized in warehouses to reduce overhead and operating costs. In this context, this paper presents a consensus-based faultresilient intelligent mechanism called Consensual Fault-Resilient Behavior (CFRB). The proposed approach is based on three hierarchical plans: imposition, negotiation, and consensus. Fault resilience is achieved using the collective behavior of a multi-robot system that applies ternary decisions based on these plans. The difference between this paper and our previous work is on the consensual level. As it is suitable for the analysis and design of coordinated behavior between autonomous robots, the consensus plan is restructured and enhanced. The proposed approach is tested and evaluated in a virtual warehouse based on a real environment. In addition, it is compared with other current approaches, and the results are presented, demonstrating its efficiency.
- WsBot: a tiny, low-cost swarm robot for experimentation on industry 4.0Publication . Limeira, Marcelo A.; Piardi, Luis; Kalempa, Vivian Cremer; Oliveira, Andre Schneider; Leitão, PauloMulti-Robot Systems (MRS) are a powerful tool to achieve machine-to-machine connectivity and intelligent behaviors required to Industry 4.0. However, these systems require that a large number of resources such as software, hardware, and mechanical devices working together. For reasons of cost, complexity and time they are usually validated only in simulated environments, thus causing great difficulty in their practical experimentation. This paper presents the WsBot, a tiny swarm robot of low cost, designed mainly, but not restricted, for the testing in smart factories. This robot is specially designed to present similar features of industrial agents, e.g., forklifts aiming to achieve the autonomous intelligent behaviors, individually, in groups or terms of the global task. The WsBot is a tiny differential robot, ROS-based, capable of executing its behavior and connects with other agents through Wi-Fi. These characteristics allow this robot to serve as a bridge so that researches, that until then were restricted to the theoretical and academic environment can effectively bring real contributions to smart factories.