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Publicações

Publicações por José Lima

2008

Sensor and actuator modeling of a realistic wheeled mobile robot simulator

Autores
Goncalves, J; Lima, J; Oliveira, H; Costa, P;

Publicação
2008 IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION, PROCEEDINGS

Abstract
This paper describes the sensor and actuator modeling of a realistic wheeled mobile robot simulator The motivation of developing such simulator is to produce a personalized versatile tool that allows production and validation of robot software reducing considerably the development time. The mobile robot simulator was developed in Object Pascal with its dynamics based on the ODE (Open Dynamics Engine), allowing to develop robot software for a three wheel omnidirectional robot equipped with Infra-Red distance sensors and brushless motors.

2023

Modeling and Realistic Simulation of a Dexterous Robotic Hand: SVH Hand use-case

Autores
Ribeiro, FM; Correia, T; Lima, J; Goncalves, G; Pinto, VH;

Publicação
2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
Recent developments in dexterous robotic manipulation technologies allowed for the design of very compact, yet capable, multi-fingered robotic hands. These can be designed to emulate the human touch and feel, reducing the aforementioned need for human expertise in highly detailed tasks. The presented work focused on the application of two simulation platforms Gazebo and MuJoCo - to a use-case of a Schunk Five Finger Robotic Hand, coupled to the UR5 collaborative manipulator. This allowed to assess the relative appropriateness of each of these platforms.

2023

Using Machine Learning Approaches to Localization in an Embedded System on RobotAtFactory 4.0 Competition: A Case Study

Autores
Klein, LC; Braun, J; Martins, FN; Wortche, H; de Oliveira, AS; Mendes, J; Pinto, VH; Costa, P; Lima, J;

Publicação
2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
The use of machine learning in embedded systems is an interesting topic, especially with the growth in popularity of the Internet of Things (IoT). The capacity of a system, such as a robot, to self-localize, is a fundamental skill for its navigation and decision-making processes. This work focuses on the feasibility of using machine learning in a Raspberry Pi 4 Model B, solving the localization problem using images and fiducial markers (ArUco markers) in the context of the RobotAtFactory 4.0 competition. The approaches were validated using a realistically simulated scenario. Three algorithms were tested, and all were shown to be a good solution for a limited amount of data. Results also show that when the amount of data grows, only Multi-Layer Perception (MLP) is feasible for the embedded application due to the required training time and the resulting size of the model.

2023

FLOOR - Forklift Laser OmnidirectiOnal Robot

Autores
Pinto, VH; Ribeiro, FM; Brito, T; Pereira, AI; Lima, J; Costa, P;

Publicação
2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
The robot presented in this paper was developed with the main focus on participating in robotic competitions. Therefore, the subsystems here presented were developed taking into account performance criteria instead of simplicity. Nonetheless, this paper also presents background knowledge in some basic concepts regarding robot localization, navigation, color identification and control, all of which are key for a more competitive robot.

2023

Data Fusion Using Ultra Wideband Time-of-Flight Positioning for Mobile Robot Applications

Autores
Lima, J; Pinto, AF; Ribeiro, F; Pinto, M; Pereira, AI; Pinto, VH; Costa, P;

Publicação
2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
Self-localization of a robot is one of the most important requirements in mobile robotics. There are several approaches to providing localization data. The Ultra Wide Band Time of Flight provides position information but lacks the angle. Odometry data can be combined by using a data fusion algorithm. This paper addresses the application of data fusion algorithms based on odometry and Ultra Wide Band Time of Flight positioning using a Kalman filter that allows performing the data fusion task which outputs the position and orientation of the robot. The proposed solution, validated in a real developed platform can be applied in service and industrial robots.

2023

Modeling of a Lithium-Ion Battery for Enhanced Power Management in Robotics Domain

Autores
Chellal, AA; Braun, J; Lima, J; Goncalves, J; Costa, P;

Publicação
2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
The aspect of energy constraint and simulation of battery behavior in robotic simulators has been partially neglected by most of the available simulation software and is offered unlimited energy instead. This lack does not reflect the importance of batteries in robots, as the battery is one of the most crucial elements. With the implementation of an adequate battery simulation, it is possible to perform a study on the energy requirements of the robot through these simulators. Thus, this paper describes a Lithium-ion battery model implemented on SimTwo robotic simulator software, in which various physical parameters such as internal resistance and capacity are modeled to mimic real-world battery behavior. The experiments and comparisons with a real robot have assessed the viability of this model. This battery simulation is intended as an additional tool for the roboticists, scientific community, researchers, and engineers to implement energy constraints in the early stages of robot design, architecture, or control.

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