Diego Deplano

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About

Diego Deplano is a robotics researcher specializing in multi-robot coordination, collision avoidance, and motion planning. His work addresses the fundamental challenge of enabling multiple autonomous robots to navigate shared environments efficiently and safely, a problem of increasing importance in logistics, manufacturing, and warehouse automation. Deplano’s most impactful contribution is his 2020 paper, "A Discrete Event Formulation for Multi-Robot Collision Avoidance on Pre-planned Trajectories," which has garnered 12 citations. In this work, he introduced a novel approach that models robots as automata within a discrete event framework, minimizing the maximum traveling time while ensuring collision-free operation on pre-planned paths. This formulation offers a computationally tractable alternative to the notoriously PSPACE-complete multi-robot path planning problem. Earlier, in 2017, Deplano proposed a heuristic algorithm to optimize execution time for multi-robot paths, laying groundwork for scalable solutions in large-scale systems. His research bridges theoretical rigor with practical efficiency, making him a notable contributor to the field of multi-agent robotics.