Alexandre Gomes Caldeira

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About

Alexandre Gomes Caldeira is a robotics researcher focused on advancing autonomous navigation for mobile robots and unmanned aerial vehicles (UAVs). His primary research areas include sensor data representation, object detection using 2D LiDAR, and path planning in geometrically constrained environments. Caldeira’s major contribution is the development of an analytical formalism for 2D LiDAR data representation and object detection, providing a unified mathematical framework that standardizes how mobile robots interpret sensor data for improved accuracy in both indoor and outdoor settings. This work has garnered 9 citations since 2024, signaling growing interest in his systematic approach to a traditionally fragmented problem. Additionally, his 2020 study on UAV path-following for crossing narrow passages introduces a smooth trajectory planning method that enables drones to navigate tight spaces where standard obstacle avoidance fails—a critical capability for inspection, search-and-rescue, and delivery tasks in cluttered environments. Though early in his career, Caldeira’s contributions address foundational challenges in robotics perception and control, offering practical solutions that bridge theory and real-world application. His work is particularly relevant for students and researchers developing autonomous systems for complex, unstructured environments.