2020
Autores
Santos, LC; Santos, FN; Solteiro Pires, EJS; Valente, A; Costa, P; Magalhaes, S;
Publicação
2020 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2020)
Abstract
The world's population is estimated to reach nine billion people by the year 2050, which indicates that agricultural productivity must increase sustainably. The mechanisation and automatisation of agricultural tasks is an essential step to face population growth. Ground robots have been developed along the last decade for several agricultural applications, being, the autonomous and safe navigation one of the hardest challenge in this development. Moving autonomously, a mobile platform involves different tasks, such as localisation, mapping, motion control, and path planning, a crucial step for autonomous operations. This article performs a survey of different applications for path planning techniques applied to various agricultural contexts. This paper analyses different agricultural applications and details about the employed path planning method. The conclusion indicates that path planning has been successfully applied to agrarian robots for field coverage and point-to-point navigation, being that coverage path planning is slightly more advanced in this field.
2020
Autores
Zawadniak, P; Piardi, L; Brito, T; Lima, J; Costa, P; Monteiro, ALR; Costa, P; Pereira, AI;
Publicação
2020 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2020)
Abstract
Micromouse is one of the most popular competitions among mobile robotics researchers. This competition brings together several challenges in the field of mobile robotics. It represents an excellent tool in competition field since it stimulates the development and multidisciplinary knowledge as well as group cooperation to carry out the best approach. This work presents a contribution to this issue on exploring the unknown environment and the robot location to obtain an optimized trajectory in the maze, using the modified Floodfill algorithm that considers the cost for the robot rotations around its axis. A comparison is conducted between the modified algorithm and the traditional Floodfill procedure.
2021
Autores
Zawadniak, PVF; Piardi, L; Brito, T; Lima, J; Costa, P; Monteiro, ALR; Costa, P; Pereira, AI;
Publicação
SN APPLIED SCIENCES
Abstract
The micromouse competition has been gaining prominence in the robotic atmosphere, due to the challenging and multidisciplinary characteristics provided by the teams' duels, being a gateway for those who intend to deepen their studies in autonomous robotics. In this context, this paper presents a realistic micromouse simulator developed with Unity software, a widely game engine with dynamics and 3D development platform used. The developed simulator has hardware-in-the-loop capabilities, aims to be simple to use, it can be customizable, and designed to be as similar as possible to the real robot configurations. In this way, the proposed simulator requires few modifications to port the microcontroller code to a real robot. Therefore, the framework presented in this work allows the user to simulate the development of new algorithm strategies dedicated to competition and also hardware updates. The simulation supports several mazes, from previous competitions and has the possibility to add different mazes elaborated by the user. Thus, the features and functionality of the simulator can serve to accelerate the project's development of the beginning and advanced competitors, using real models to reduce the gap between the mouse robot behavior in the simulation and the reality. The developed simulation environment is available to the community.
2021
Autores
Matos, D; Costa, P; Lima, J; Costa, P;
Publicação
ROBOTICS
Abstract
Most path planning algorithms used presently in multi-robot systems are based on offline planning. The Timed Enhanced A* (TEA*) algorithm gives the possibility of planning in real time, rather than planning in advance, by using a temporal estimation of the robot's positions at any given time. In this article, the implementation of a control system for multi-robot applications that operate in environments where communication faults can occur and where entire sections of the environment may not have any connection to the communication network will be presented. This system uses the TEA* to plan multiple robot paths and a supervision system to control communications. The supervision system supervises the communication with the robots and checks whether the robot's movements are synchronized. The implemented system allowed the creation and execution of paths for the robots that were both safe and kept the temporal efficiency of the TEA* algorithm. Using the Simtwo2020 simulation software, capable of simulating movement dynamics and the Lazarus development environment, it was possible to simulate the execution of several different missions by the implemented system and analyze their results.
2021
Autores
Santos, J; Rebelo, PM; Rocha, LF; Costa, P; Veiga, G;
Publicação
ROBOTICS
Abstract
A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV's route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*-Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented.
2021
Autores
Couto, T; Costa, P; Malaca, P; Tavares, P;
Publicação
2021 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)
Abstract
Welding physics is complex, and therefore the welding parametrization is time-consuming. In manual welding, the "hand", the experience, and the best sensor of all (the eyes) can compensate for the difficulties in finding the right settings (welding parameters, robot posture, speed,...) for a specific weld seam. In robotic welding the robotic arm and the sensors are limited, and the parametrization time escalates. This work aims to develop a flexible welding robotized system, through the introduction of (knowledge-based) decision support for welding parametrization in an advanced robotic work cell, in combination with advanced (collision-free) offline programming and advanced sensing. By selecting a specific application area, structural steel, this work will reduce the degree of complexity during the development, paving the way for the introduction of knowledge-based welding in the robotic arc welding sector.
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