Browsing by Author "Ferreira, Edilson Santos"
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- Development of a Low-Cost 3D Mapping Technology with 2D LIDAR for Path Planning Based on the A* AlgorithmPublication . Ferreira, Edilson Santos; Grilo, Vinicius F.S.B.; Braun, João; Santos, Murillo F. dos; Pereira, Ana I.; Costa, Paulo Gomes da; Lima, JoséThis article presents the development of a low-cost 3D mapping technology for trajectory planning using a 2D LiDAR and a stepper motor. The research covers the design and implementation of a circuit board to connect and control all components, including the LiDAR and motor. In addition, a 3D printed support structure was developed to connect the LiDAR to the motor shaft. System data acquisition and processing are addressed, as well as the generation of the point cloud and the application of the A* algorithm for trajectory planning. Experimental results demonstrate the effectiveness and feasibility of the proposed technology for low-cost 3D mapping and trajectory planning applications.
- Impact of EMG Signal Filters on Machine Learning Model Training: A Comparison with Clustering on Raw SignalPublication . Barbosa, Ana Carolina; Ferreira, Edilson Santos; Grilo, Vinicius F.S.B.; Mattos, Laercio; Lima, JoséOur current society faces challenges in integrating individuals with disabilities, making this process difficult and painful. People with disabilities (PwD) are often mistakenly considered incapable due to the difficulties they face in daily tasks due to the lack of adapted means and tools. In this context, assistive technologies play a crucial role in improving the quality of life for these individuals. However, assistive technologies still have various limitations, making research in this area essential to enhance existing solutions and develop new approaches that meet individual needs, aiming to promote inclusion and equal opportunities. This paper presents a research project that focuses on the study of electromyography (EMG) signal processing generated by individuals who have undergone amputations. These signals are essential in assistive technologies, such as myoelectric prostheses. The study focuses on the impact of different filters and machine learning training methods on this processing. The results of this study have the potential to provide relevant findings for the development of more efficient assistive technologies. By understanding the processing of EMG signals and applying machine learning techniques, it is possible to improve the accuracy and response speed of prosthetics, increasing the functionality and naturalness of movements performed by users, as well as paving the way for the emergence of new technologies.
- Three-dimensional mapping of an unknown environment based on 2D laser measurementPublication . Ferreira, Edilson Santos; Lima, José; Santos, Murillo Ferreira dos; Neto, João Afonso Braun3D mapping technology plays a key role in the field of robotics and autonomous navigation by enabling accurate perception and understanding of a robot’s surrounding environment. However, traditional 3D mapping systems can be expensive and inaccessible, limiting their application in low-cost scenarios. This work presents the development of a low-cost 3D mapping technology for trajec- tory planning using the A* algorithm. The main objective of this study is to provide a easible and cost-effective solution for 3D mapping, enabling accurate trajectory planning in robotic environments. The proposed approach combines a 2D LiDAR, a stepper motor, and the A* algorithm or trajectory planning. In addition, a circuit board for connecting and controlling the equipment and a 3D-printed support for attaching the LiDAR to the motor shaft are developed. The system is able to acquire data, perform the processing and generate a point cloud for use in trajectory planning with the A* algorithm. The experimental results demonstrate the effectiveness and feasibility of the proposed technology, opening doors to low-cost robotics applications, such as small autonomous vehicles. Furthermore, this approach offers an affordable alternative for research and development in the field of 3D mapping and trajectory planning. Finally, possible improvements to be implemented in future work are highlighted.