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About

Robyn Verrinder’s research focuses on autonomous navigation in extreme, sensor-limited environments, with significant contributions to both subterranean and marine robotics. Her most cited work tackles the Simultaneous Localization and Mapping (SLAM) problem in GPS-denied underground mining settings, where few features and no satellite signals are available. By integrating RFID tags for localisation and mapping, her 2012 paper (10 citations) enables safe autonomous vehicle navigation in hazardous, feature-sparse mines—a critical step for improving safety and efficiency in the mining industry. In a more recent study (2017, 2 citations), Verrinder addresses the challenge of estimating sea state from a slow-moving marine platform. She develops a novel Phase-Locked Loop and Kalman Filter strategy to track ocean waves using only inertial measurement unit (IMU) data, allowing for short-term local wave prediction without external references. This work, supported by a joint South African DST and CSIR Robotics Strategy grant, demonstrates her versatility in applying advanced estimation techniques across domains. Verrinder’s research is notable for its practical impact in hazardous, unstructured environments, bridging theory and real-world application.