Emerson Cassiano da Silva
Papers
2
Total Citations
6
H-Index
2
About
Emerson Cassiano da Silva is a robotics researcher whose work lies at the intersection of artificial intelligence and autonomous navigation. His primary research focus is on developing advanced Deep Reinforcement Learning (Deep-RL) techniques to solve the challenging problem of mapless navigation for terrestrial mobile robots. In his most cited work, he presents a comparative study of two Deep-RL approaches: one based on the classic Deep Q-Network (DQN) algorithm and another leveraging the more sophisticated Double Deep Q-Network (DDQN). By systematically evaluating these algorithms for low-dimensional sensing scenarios, his research demonstrates how Double Deep Q-Learning can enhance decision-making stability and reduce the overestimation bias inherent in standard DQN methods. This work, which has accumulated 6 citations, contributes directly to the development of more reliable and efficient autonomous robots capable of navigating unfamiliar environments without pre-existing maps. Emerson’s contributions are particularly valuable for real-world applications in search-and-rescue, warehouse logistics, and service robotics, where adaptability and robust sensor processing are critical.
Research Focus
Key Achievements
Top Papers
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