Anna Konrad

National University of Ireland, Maynooth

Papers

Total Citations

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About

Anna Konrad is a robotics and computer vision researcher whose work bridges perception and manipulation for autonomous systems. Her primary research areas include keypoint detection for non-standard camera systems, robotic simulation, and grasp quality prediction. Konrad’s most influential contribution is the development of **FisheyeSuperPoint** (2022, 10 citations), a keypoint detection and description network specifically designed for fisheye cameras—a critical advancement for robotics and autonomous driving, where wide-angle lenses are common but poorly supported by existing techniques. She also introduced **VGQ-CNN** (2022, 4 citations), a versatile grasp quality prediction network that operates beyond fixed-camera setups, enabling mobile robots to evaluate 6-DOF grasps from varied viewpoints without retraining. In simulation, Konrad conducted a landmark case-study comparing Unity and ROS with Gazebo (2019, 9 citations), providing the robotics community with practical guidance for evaluating localization, motion planning, and control in virtual environments. Her work directly addresses real-world deployment challenges, making robotic systems more adaptable and reliable. With a growing citation record and a focus on practical, transferable solutions, Konrad is establishing herself as a key contributor to the next generation of autonomous robotic systems.