Daniel Castro

University of Algarve, Institute for Systems Engineering and Computers, University of Coimbra

Papers

Total Citations

226

H-Index

About

Daniel Castro is a robotics researcher whose work centers on autonomous navigation, sensor integration, and real-time perception for mobile robots. His most influential contribution is the development of a fast feature detection system for laser scan data, published in 2006, which enables real-time identification of lines, arcs, circles, and even human legs. This work, cited 185 times, introduced the novel Inscribed Angle Variance (IAV) method for arc and circle detection, alongside recursive line fitting, and has become a foundational tool for robot localization and people tracking in dynamic environments. Castro has also made significant strides in reactive local navigation, proposing obstacle detection and collision avoidance methods that allow nonholonomic robots to navigate safely in cluttered, dynamic settings. His research extends to sensor design, including a tactile force control system for parallel jaw grippers and an optoelectronic proximity sensor, both aimed at enhancing robot-environment interaction. Through these contributions, Castro has advanced the practical deployment of autonomous robots, particularly in applications requiring robust, low-latency perception and control.