Kenia Picos
Papers
12
Total Citations
249
H-Index
5
About
Kenia Picos is a robotics and autonomous systems researcher whose work centers on mobile robot navigation, path planning, and intelligent control. She has made significant contributions to the development of novel hybrid algorithms that merge bio-inspired computing with classical robotics frameworks. Her most celebrated work, the Membrane Pseudo-Bacterial Potential Field (MemPBPF) algorithm, published in 2019, introduced a groundbreaking approach to safe and efficient path generation by drawing on biochemical evolutionary processes, earning 115 citations and establishing her as a notable voice in the field. Building on this foundation, her 2022 QAPF learning algorithm — combining Q-learning reinforcement techniques with artificial potential fields — has garnered 91 citations, demonstrating her ability to address both known and unknown environments with adaptive, self-learning systems. Her broader research portfolio explores computer vision-based obstacle recognition, LiDAR and RGB-D camera-driven SLAM, fuzzy control systems for nonholonomic robots, and GPU-accelerated computation for real-time planning. Together, her publications reflect a consistent drive to bridge theoretical algorithmic innovation with practical autonomous robot deployment, making her research highly valuable to students and engineers working at the intersection of artificial intelligence and robotics.
Research Focus
Key Achievements
Top Papers
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- 3Environment Recognition for Path Generation in Autonomous Mobile Robots9 citations · 2019
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- 6Obstacle recognition for path planning in autonomous mobile robots5 citations · 2016
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