Papers
9
Total Citations
79
H-Index
5
About
M.J. Rendas is a leading researcher in autonomous underwater vehicle (AUV) navigation and perception, whose work has fundamentally advanced how robots interact with and understand natural underwater environments. Her primary research areas include sonar and vision-based environmental sensing, autonomous boundary tracking, and sensor fusion for robotic guidance. Rendas made a landmark contribution with her work on benthic boundary tracking using profiler sonar (25 citations), where she developed a classical control loop that enables AUVs to autonomously follow transitions between distinct seafloor regions. She further pioneered the use of unsupervised adaptive clustering for video-based guidance along sea-bed boundaries (14 citations), allowing robots to navigate using biological features without external positioning systems. Her innovative approach to automatic sonar-to-video calibration (13 citations) solved the critical challenge of coregistering data from different exteroceptive sensors, enabling more robust underwater mapping. Rendas has also contributed to statistical environment representation, genetic algorithm-based trajectory planning, and incorporating a priori current knowledge into AUV navigation systems. Her work has been instrumental in developing autonomous robots capable of long-duration, adaptive exploration in complex, uncertain marine environments.
Research Focus
Key Achievements
Top Papers
- 1Benthic boundary tracking using a profiler sonar25 citations · 2004
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- 3Exploiting natural contours for automatic sonar-to-video calibration13 citations · 2005
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- 7Shape recognition: a fuzzy approach4 citations · 2002
- 8Using a priori current knowledge on AUV navigation4 citations · 2002
- 9Learning safe navigation in uncertain environments4 citations · 2000