Jorge Augusto Vasconcelos Alves
Universidade Federal do Rio Grande do Sul, Universidade Tecnológica Federal do Paraná
Papers
3
Total Citations
51
H-Index
2
About
Jorge Augusto Vasconcelos Alves is a control systems researcher whose work centers on the real-time navigation and stabilization of mobile robots, with a particular focus on differential-drive platforms. His most influential contribution is the application of linearized Model Predictive Control (MPC) to mobile robotics, as demonstrated in his 2006 paper, which has garnered 45 citations. This work pioneered a computationally efficient method for handling physical constraints on state and inputs while maintaining real-time performance—a critical challenge in autonomous navigation. Alves further advanced the field by exploring probabilistic control methods, including a cloud of particles approach that addresses uncertainty in pose estimation, contrasting with traditional deterministic laws like the extended Kalman filter. His 2007 paper on real-time point stabilization using MPC provided an implicit optimal control law that elegantly bypasses the need for explicit trajectory planning. While his citation counts reflect a specialized, technically deep impact rather than broad popularity, Alves’ contributions are foundational for researchers working on constrained, real-time control of wheeled robots, particularly in applications requiring robust handling of system limitations and sensor noise.
Research Focus
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Top Papers
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