Manuel Vega Heredia
Universidad de Occidente, Universidad Autónoma de Ciudad Juárez
Papers
5
Total Citations
165
H-Index
4
About
Manuel Vega Heredia is a robotics researcher whose work centers on self-reconfigurable robots for challenging real-world environments, from building facades to underground drains. His most impactful contribution is the development of a self-reconfigurable façade-cleaning robot equipped with deep-learning-based crack detection using convolutional neural networks—a paper that has garnered 92 citations and addresses the high-risk, labor-intensive maintenance of glass high-rise structures. Heredia’s research consistently focuses on autonomous systems that adapt their morphology to overcome geometric and terrain limitations. He designed an autonomous self-reconfigurable floor cleaning robot (46 citations) to improve cleaning coverage, and a self-reconfigurable drain mapping robot with level-shifting capability (14 citations), inspired by a giraffe’s leg folding pattern for navigating confined, uneven spaces. His work on collision avoidance and stability for drainage robots (10 citations) further advances safety in autonomous inspection. Notably, Heredia’s earlier research on unstructured terrain adaptive navigation for quadruped robots (2015) introduced a polynomial path generation method based on topographic analysis. Through these innovations, he is pushing the boundaries of adaptive robotics for maintenance, inspection, and hygiene applications.
Research Focus
Key Achievements
Top Papers
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- 2Autonomous Self-Reconfigurable Floor Cleaning Robot46 citations · 2020
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