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About

Maurizio Di Rocco is a leading researcher in multi-robot systems and cognitive robotic ecologies, with a particular focus on ambient assisted living (AAL) and smart home environments. His work bridges the gap between high-level AI planning and low-level robot execution, addressing the critical challenge of making autonomous systems socially believable and adaptive to human needs. His most influential contribution, "Development of a Socially Believable Multi-Robot Solution from Town to Home," has garnered 106 citations, demonstrating its foundational impact on the field. Di Rocco pioneered approaches to distributed target localization and encirclement (47 citations) and introduced the concept of robotic ubiquitous cognitive ecologies for smart homes (35 citations), where multiple robots and sensors self-configure and evolve to support elderly assistance. His innovative work on configuration planning for robots with dynamic goals (29 citations) tackles the real-world problem of unexpected execution contingencies, enabling robots to reason across time, resources, and information dependencies. Di Rocco also developed stigmergic algorithms for minimalistic robots using RFID floors (26 citations) and context-aware navigation systems that learn user preferences (24 citations). His research consistently advances the frontier of deploying intelligent, adaptive robotic systems in human-centered environments.