Rubens J. M. Afonso
Papers
11
Total Citations
74
H-Index
5
About
Rubens J. M. Afonso is a control systems and robotics researcher whose work sits at the intersection of optimization-based planning, humanoid locomotion, and multi-robot coordination. His research is anchored in Model Predictive Control (MPC) and Mixed-Integer Programming (MIP), which he applies to some of the most computationally demanding problems in modern robotics. Afonso's most influential contribution — his 2016 paper on mixed-integer programming for automatic walking step duration, with 19 citations — introduced a framework enabling humanoid robots to simultaneously optimize center-of-mass trajectories, footstep positions, and step timing in real time, a genuinely difficult combinatorial challenge. This thread continues through his 2025 work on imitation learning for MPC-based humanoid walking, reflecting a trajectory toward computationally efficient, learning-augmented control. Beyond bipedal locomotion, Afonso has made notable contributions to multi-robot systems, developing robust MPC strategies that maintain communication connectivity and coordinate task assignment under realistic constraints, including novel work on Visible Light Communication networks. His minimum-time trajectory planning paper (2020, 15 citations) demonstrates additional breadth in nonholonomic robot motion planning. With over 70 cumulative citations spanning humanoid robotics, autonomous navigation, and multi-agent systems, Afonso represents a productive voice in applied optimization for robotics.
Research Focus
Key Achievements
Top Papers
- 1Mixed-integer programming for automatic walking step duration19 citations · 2016
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- 5Risk Constrained Navigation Using MILP-MPC Formulation7 citations · 2017
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- 8Requirements Derivation for RoboCup Small Size League Robot2 citations · 2020
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