Cabral Lima
Papers
6
Total Citations
23
H-Index
3
About
Cabral Lima’s research lies at the intersection of robotics, fuzzy control systems, and brain-computer interfaces (BCIs), with a focus on enabling autonomous navigation in complex environments. His most cited work, “Analysis of the Stability of a Fuzzy Control System Developed to Control a Simulated Robot” (2005, 7 citations), introduces a fuzzy logic controller that simultaneously manages a robot’s direction and speed while navigating obstacle-filled virtual worlds. This foundational study established a framework for robust, real-time decision-making in uncertain settings. Lima further advanced path planning by critically evaluating probabilistic roadmap (PRM) methods in “Which Probabilistic Roadmap Method Should Be Used by a Robot in an Actual Environment?” (2016, 5 citations), offering practical guidance for deploying PRM techniques in real-world scenarios. His comparative analyses of Mamdani and Takagi-Sugeno fuzzy controllers (2006) highlight his commitment to optimizing system performance and robustness. Notably, his recent work “Meditation as an Effective BCI Training Protocol for Controlling Wheeled Robots” (2023, 2 citations) pioneers the use of meditative states to enhance BCI control, opening new avenues for assistive technology. With over 20 citations across his portfolio, Lima’s contributions demonstrate a sustained effort to bridge theoretical control methods with practical robotic applications, from simulation to human-centered interfaces.
Research Focus
Key Achievements
Top Papers
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- 4Analysis of the Performance of Different Fuzzy System Controllers3 citations · 2005
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