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About

Aditya Mandalika is a roboticist whose research lies at the intersection of motion planning, search algorithms, and autonomous mobile manipulation. His most impactful work tackles the computational bottleneck of edge evaluation in robotic motion planning. Mandalika pioneered the development of lazy search algorithms, most notably introducing LazySP—an optimal algorithm that dramatically reduces computation by restricting edge evaluations to only the shortest path. This work, published in 2019 and accumulating over 27 citations across its versions, established a new paradigm for interleaving search and evaluation via event-based toggles. Beyond algorithmic foundations, Mandalika has demonstrated the real-world applicability of his research through the RoMan project, which aims to field human-scale mobile manipulation robots capable of performing dangerous tasks in unstructured environments. He has also advanced the field of experience-based planning with his LEGO framework, which leverages prior knowledge to generate sparse, strategically placed roadmaps that enable faster search and lower-cost paths. Mandalika’s contributions bridge the gap between theoretical efficiency and practical deployment, making him a rising figure in modern robotics.