Robotic Manipulator
Robotic manipulators are multi-jointed robotic arms designed to perform a wide variety of tasks, with current research focusing on improving their robustness, adaptability, and ease of programming. Key areas of investigation include enhancing manipulator resilience to joint failures using reinforcement learning and other AI-driven methods, developing more efficient and robust control algorithms (e.g., adaptive control, model predictive control), and improving human-robot interaction through intuitive interfaces and learning from demonstration techniques. These advancements are crucial for expanding the capabilities of robotic manipulators in manufacturing, healthcare, and other fields requiring precise and adaptable automation.
Papers
Applying PBL in the Development and Modeling of kinematics for Robotic Manipulators with Interdisciplinarity between Computer-Assisted Project, Robotics, and Microcontrollers
Afonso Henriques Fontes Neto Segundo, Joel Sotero da Cunha Neto, Paulo Cirillo Souza Barbosa, Raul Fontenele Santana
Development of a robotic manipulator: Applying interdisciplinarity in Computer Assister Project, Microcontrollers and Industrial Robotics
Afonso Henriques Fontes Neto Segundo, Joel Sotero da Cunha Neto, Reginaldo Florencio da Silva, Paulo Cirillo Souza Barbosa, Raul Fontenele Santana
Aplica\c{c}\~ao de ros como ferramenta de ensino a rob\'otica / using ros as a robotics teaching tool
Daniel Maia Evangelista, Pedro Benevides Cavalcante, Afonso Henriques Fontes Neto Segundo
Desenvolvimento de ferramenta de simula\c{c}\~ao para aux\'ilio no ensino da disciplina de rob\'otica industrial
Afonso Henriques Fontes Neto Segundo, Joel Sotero da Cunha Neto, Halisson Alves de Oliveira, Átila Girão de Oliveira, Reginaldo Florencio da Silva