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Robot Ecology: Constraint-Based Design for Long-Duration Autonomy
A revolutionary new framework that draws on insights from ecology for the design and analysis of long-duration...
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9780691211688
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A revolutionary new framework that draws on insights from ecology for the design and analysis of long-duration robots
Robots are increasingly leaving the confines of laboratories, warehouses, and manufacturing facilities, venturing into agriculture and other settings where they must operate in uncertain conditions over long timescales. This multidisciplinary book draws on the principles of ecology to show how robots can take full advantage of the environments they inhabit, including as sources of energy. Magnus Egerstedt introduces a revolutionary new design paradigm--robot ecology--that makes it possible to achieve long-duration autonomy while avoiding catastrophic failures. Central to ecology is the idea that the richness of an organism's behavior is a function of the environmental constraints imposed by its habitat. Moving beyond traditional strategies that focus on optimal policies for making robots achieve targeted tasks, Egerstedt explores how to use survivability constraints to produce both effective and provably safe robot behaviors. He blends discussions of ecological principles with the development of control barrier functions as a formal approach to constraint-based control design, and provides an in-depth look at the design of the SlothBot, a slow and energy-efficient robot used for environmental monitoring and conservation. Visionary in scope, Robot Ecology presents a comprehensive and unified methodology for designing robots that can function over long durations in diverse natural environments.Author: Magnus Egerstedt
Publisher: Princeton University Press
Published: 12/28/2021
Pages: 360
Binding Type: Hardcover
Weight: 1.60lbs
Size: 9.30h x 6.10w x 1.30d
ISBN: 9780691211688
About the Author
Magnus Egerstedt is the Steve W. Chaddick School Chair and Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He is the coauthor of Graph Theoretic Methods in Multiagent Networks and Control Theoretic Splines: Optimal Control, Statistics, and Path Planning (both Princeton).
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