Annual Review of Control, Robotics, and Autonomous Systems

Annual Review of Control, Robotics, and Autonomous Systems

eISSN: 2573-5144

AIMS AND SCOPE OF JOURNAL: The Annual Review of Control, Robotics, and Autonomous Systems provides comprehensive reviews of significant theoretical and applied developments that impact the engineering of autonomous and semiautonomous systems. The broad fields of control and robotics are the major areas covered, together with connections to theoretical and applied mechanics, optimization, communication, information theory, machine learning, computing, and signal processing. The journal covers important intersections with fields outside of engineering, including biology, neuroscience, and human behavioral sciences.

Published Since	2018
Journal Status	Active

Impact Factor	11.2

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- From Virtual Reality to the Emerging Discipline of Perception Engineering
  
  Steven M. LaValle, Evan G. Center, Timo Ojala, Matti Pouke, Nicoletta Prencipe, Basak Sakcak, Markku Suomalainen, Kalle G. Timperi, and Vadim Weinstein
  
  Vol. 7 (2024), pp. 409–436
- Endovascular Microrobotics for Neurointervention
  
  David R. Santiago-Dieppa, and James Friend
  
  Vol. 7 (2024), pp. 385–408
- An Overview of Microrobotic Systems for Microforce Sensing
  
  Georges Adam, Mokrane Boudaoud, Valentin Reynaud, Joel Agnus, David J. Cappelleri, and Cédric Clévy
  
  Vol. 7 (2024), pp. 359–383
- Machine Learning in Robotic Ultrasound Imaging: Challenges and Perspectives
  
  Yuan Bi, Zhongliang Jiang, Felix Duelmer, Dianye Huang, and Nassir Navab
  
  Vol. 7 (2024), pp. 335–357
- Robot Model Identification and Learning: A Modern Perspective
  
  Taeyoon Lee, Jaewoon Kwon, Patrick M. Wensing, and Frank C. Park
  
  Vol. 7 (2024), pp. 311–334
- Sampling-Based Motion Planning: A Comparative Review
  
  Andreas Orthey, Constantinos Chamzas, and Lydia E. Kavraki
  
  Vol. 7 (2024), pp. 285–310
- Robotics Software: Past, Present, and Future
  
  Jesse Haviland, and Peter Corke
  
  Vol. 7 (2024), pp. 253–283
- A Control Framework for Ocean Wave Energy Conversion Systems: The Potential of Moments
  
  Nicolás Faedo, and John V. Ringwood
  
  Vol. 7 (2024), pp. 227–252
- Control Co-Design of Wind Turbines
  
  Lucy Y. Pao, Manuel Pusch, and Daniel S. Zalkind
  
  Vol. 7 (2024), pp. 201–226
- Control of Solar Energy Systems
  
  Eduardo F. Camacho, Sara Ruiz-Moreno, José M. Aguilar-López, Antonio J. Gallego, and Ramón A. García
  
  Vol. 7 (2024), pp. 175–200
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- Planning and Decision-Making for Autonomous Vehicles
  
  Wilko Schwarting, Javier Alonso-Mora, and Daniela Rus
  
  Vol. 1 (2018), pp. 187–210
- Learning-Based Model Predictive Control: Toward Safe Learning in Control
  
  Lukas Hewing, Kim P. Wabersich, Marcel Menner, and Melanie N. Zeilinger
  
  Vol. 3 (2020), pp. 269–296
- Recent Advances in Robot Learning from Demonstration
  
  Harish Ravichandar, Athanasios S. Polydoros, Sonia Chernova, and Aude Billard
  
  Vol. 3 (2020), pp. 297–330
- A Tour of Reinforcement Learning: The View from Continuous Control
  
  Benjamin Recht
  
  Vol. 2 (2019), pp. 253–279
- Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
  
  Lukas Brunke, Melissa Greeff, Adam W. Hall, Zhaocong Yuan, Siqi Zhou, Jacopo Panerati, and Angela P. Schoellig
  
  Vol. 5 (2022), pp. 411–444
- Haptics: The Present and Future of Artificial Touch Sensation
  
  Heather Culbertson, Samuel B. Schorr, and Allison M. Okamura
  
  Vol. 1 (2018), pp. 385–409
- Magnetic Methods in Robotics
  
  Jake J. Abbott, Eric Diller, and Andrew J. Petruska
  
  Vol. 3 (2020), pp. 57–90
- A Century of Robotic Hands
  
  C. Piazza, G. Grioli, M.G. Catalano, and A. Bicchi
  
  Vol. 2 (2019), pp. 1–32
- Distributed Optimization for Control
  
  Angelia Nedić, and Ji Liu
  
  Vol. 1 (2018), pp. 77–103
- Integrated Task and Motion Planning
  
  Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, and Tomás Lozano-Pérez
  
  Vol. 4 (2021), pp. 265–293
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Annual Review of Control, Robotics, and Autonomous Systems

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