Max Robotics — Global Service Robot Directory + US Certification

About

Miguel Velhote Correia is a researcher whose work lies at the intersection of computer vision, autonomous robotics, and advanced sensing technologies. His primary contributions focus on motion perception for autonomous systems, particularly through the development of flow-based techniques that enable robots to interpret and navigate dynamic environments. His highly cited paper, "A Flow-based Motion Perception Technique for an Autonomous Robot System" (2013, 15 citations), along with "Visual motion perception for mobile robots through dense optical flow fields" (2016, 14 citations) and "Unsupervised flow-based motion analysis for an autonomous moving system" (2014, 12 citations), collectively establish a robust framework for visual motion analysis in robotics. Correia also advanced video enhancement for surveillance and robotic applications with "Enhancing dynamic videos for surveillance and robotic applications: The robust bilateral and temporal filter" (2013, 14 citations). Notably, his work on "Cyclops: single-pixel imaging lidar system based on compressive sensing" (2017) explores cutting-edge imaging LIDAR technology for space exploration, targeting autonomous guidance on Mars and the Moon. With over 57 citations across his most-cited works, Correia’s research demonstrates significant impact in both terrestrial robotics and future space missions, making him a key figure in motion perception and sensing innovation.