History

Related papers: 20

About

History, as a category in robotics and AI research, refers to the body of foundational texts, intellectual lineages, and contextual narratives that trace how intelligent machines, autonomous systems, and computational thinking have developed over time. It encompasses technical milestones — such as early legged robots, mobile platforms, and surgical systems — alongside broader social, political, and philosophical forces that shaped their emergence. In robotics and AI, historical context matters because the field draws heavily on prior paradigms: behaviorist approaches challenged classical AI assumptions, military funding shaped autonomy research, and cultural attitudes influenced human-robot interaction design. Understanding this lineage helps engineers and researchers recognize why certain architectures, assumptions, or ethical blind spots persist in current systems. History matters because it prevents practitioners from reinventing solutions to solved problems, reveals how societal values become embedded in technical choices, and clarifies the consequences — economic, environmental, and ethical — of deploying intelligent systems at scale. A historically informed engineer is better equipped to anticipate trajectories, critically evaluate dominant assumptions, and design technology that serves broad human needs rather than narrow institutional ones.

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Citations: 956 • 1996

Frontier-based exploration using multiple robots

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Preparing for the Twenty-First Century.

Walter L. Goldfrank, Paul Kennedy

Citations: 627 • 1994

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Killer Robots

Robert Sparrow

Citations: 550 • 2007

Global Warming: Energy, Environmental Pollution, and the Impact of Power Electronics

B.K. Bose

Citations: 530 • 2010

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Time and the Other

Claus Schreiner, Emmanuel Lévinas, Richard I. Cohen

Citations: 462 • 1987

Kinodynamic motion planning

Bruce R. Donald, Patrick Xavier, John Canny, John H. Reif

Citations: 456 • 1993

Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

Citations: 448 • 2019

AI: the tumultuous history of the search for artificial intelligence

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Citations: 409 • 2017

Deep Learning in Natural Language Processing

Li Deng, Yang Liu

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