Quantum robotics is an emerging engineering and scientific research discipline that explores the application of quantum mechanics, quantum computing, quantum algorithms, and related fields to robotics. This work broadly surveys advances in our scientific understanding and engineering of quantum mechanisms and how these developments are expected to impact the technical capability for robots to sense, plan, learn, and act in a dynamic environment. It also discusses the new technological potential that quantum approaches may unlock for sensing and control, especially for exploring and manipulating quantum-scale environments. Finally, the work surveys the state of the art in current implementations, along with their benefits and limitations, and provides a roadmap for the future.Preface.- Acknowledgments.- Notation.- Introduction.- Relevant Background on Quantum Mechanics.- Quantum Search.- Quantum Agent Models.- Machine Learning Mechanisms for Quantum Robotics.- Quantum Filtering and Control.- Current Strategies for Quantum Implementation.- Conclusion.- Bibliography.- Authors' Biographies.- Index.
Benjamin Shih is a Ph.D. student in Mechanical and Aerospace Engineering at the University of California, San Diego. He holds an M.S. and B.S. in Electrical and Computer Engineering from Carnegie Mellon University (2013) and has been a research assistant at Ecole Polytechnique Federale de Lausanne. His main area of research is soft robotics, an intersection of control, materials, and cognitive science. Ben led discussion of quantum control in the Quantum Robotics Group.
Tanay Mehta is a Ph.D. student in Computer Science at Northeastern University. He holds a B.S. in mathematics from the University of Southern California. His research is focused on the theoretical aspects of computer science and the fundamental limits of computation. He is interested in the role ofpseudo-randomness in complexity theory and cryptol#