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About

Tiana Rakotovao is a leading researcher in robotic perception and sensor fusion, with a focus on occupancy grid mapping for autonomous systems. Her work centers on developing efficient, real-time methods for environment perception, particularly for obstacle detection and navigation in vehicles and robots. Rakotovao’s major contribution is her pioneering approach to multi-sensor fusion using integer arithmetic, which dramatically reduces computational complexity while maintaining accuracy—a breakthrough detailed in her most-cited paper, “Multi-sensor fusion of occupancy grids based on integer arithmetic” (2016, 15 citations). This work has influenced real-time robotic applications by enabling faster, more reliable integration of heterogeneous sensors. She also led the INSPEX project (2019, 7 citations), which optimized portable range sensors for environment perception in reduced visibility, benefiting both autonomous systems and human navigation. More recently, her 2023 study on vehicle detection in occupancy grid maps (6 citations) compared five detectors for real-time performance, advancing autonomous vehicle safety. With a career spanning foundational theory to applied systems, Rakotovao’s research remains vital for engineers and scientists developing robust, low-latency perception systems.