Ben Beklisi Kwame Ayawli
Papers
5
Total Citations
227
H-Index
5
About
Ben Beklisi Kwame Ayawli is a robotics and artificial intelligence researcher whose work centers on autonomous mobile robot navigation and path planning. With a focus on developing intelligent algorithms for safe and efficient robot movement, Ayawli has made significant contributions to both theoretical and applied robotics. His highly cited 2018 overview of nature-inspired, conventional, and hybrid path planning methods (95 citations) established him as a authoritative voice in the field, providing a comprehensive framework that continues to guide researchers worldwide. Building on this foundation, his 2019 introduction of the Voronoi Diagram and Computation Geometry Technique (VD-CGT) for dynamic environments (64 citations) demonstrated a practical and novel approach to navigating real-world complexities involving moving obstacles. His 2021 Morphological Dilation Voronoi Diagram Roadmap (MVDRM) algorithm (38 citations) further advanced the field by addressing computational efficiency challenges in complex settings. Across his body of work, Ayawli consistently integrates classical geometric methods with modern optimization strategies, as seen in his Optimized RRT-A* approach. With over 227 cumulative citations, his research offers invaluable tools for the next generation of autonomous systems engineers and robotics scholars.
Research Focus
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Top Papers
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