Andrew Felder

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About

Andrew Felder is a researcher whose work lies at the intersection of decentralized robotics, multi-agent coordination, and smart sensing for autonomous navigation. His most notable contribution is the development of the Decentralized Indoor Smart Mapping and Hierarchical Navigation (DISCMAHN) system, a novel framework that enables multiple robots to navigate indoor environments without centralized control. By leveraging distributed ceiling-mounted smart cameras, Felder’s approach automatically generates waypoint graphs, allowing robots to build shared maps and plan paths collaboratively in real time. This work, published in 2019, has garnered 3 citations and represents a significant step toward scalable, infrastructure-assisted multi-robot systems. Felder’s research addresses critical challenges in autonomous indoor navigation, including map-building, path planning, and decentralized coordination, with implications for warehouse logistics, search-and-rescue, and smart building automation. His contributions demonstrate a strong commitment to practical, hardware-aware solutions that bridge sensing, communication, and control. For students and researchers exploring the frontiers of multi-robot systems, Felder’s work offers a compelling example of how distributed intelligence can overcome the limitations of centralized approaches.