A Roadmap for US Robotics - From Internet to Robotics 2020 Edition

Recently, the robotics industry celebrated its 60-year anniversary. We have used robots for more than six decades to empower people to do things that are typically dirty, dull and/or dangerous. The industry has progressed significantly over the period from basic mechanical assist systems to fully autonomous cars, environmental monitoring and exploration of outer space. We have seen tremendous adoption of IT technology in our daily lives for a diverse set of support tasks. Through use of robots we are starting to see a new revolution, as we not only will have IT support from tablets, phones, computers but also systems that can physically interact with the world and assist with daily tasks, work, and leisure activities. The present document is a summary of the main societal opportunities identified, the associated challenges to deliver desired solutions and a presentation of efforts to be undertaken to ensure that US will continue to be a leader in robotics both in terms of research innovation, adoption of the latest technology, and adoption of appropriate policy frameworks that ensure that the technology is utilized in a responsible fashion. H. I. Christensen, N. Amato, H. Yanco, M. Mataric, H. Choset, A. Drobnis, K. Goldberg, J. Grizzle, G. Hager, J. Hollerbach, S. Hutchinson, V. Krovi, D. Lee, W. Smart and J. Trinkle (2021), “A Roadmap for US Robotics – From Internet to Robotics 2020 Edition”, Foundations and Trends® in Robotics: Vol. 8, No. 4, pp 307–424. DOI: 10.1561/2300000066. Full text available at: http://dx.doi.org/10.1561/2300000066

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  H. Simon,et al.  The shape of automation for men and management , 1965 .

[3]  R. Waters,et al.  Energy cost of walking of amputees: the influence of level of amputation. , 1976, The Journal of bone and joint surgery. American volume.

[4]  J. Galvin,et al.  Coronavirus , 2013, Pediatrics.

[5]  J. Pell,et al.  Quality of life following lower limb amputation for peripheral arterial disease. , 1993, European journal of vascular surgery.

[6]  C.D. Martin,et al.  The Media Equation: How People Treat Computers, Television and New Media Like Real People and Places [Book Review] , 1997, IEEE Spectrum.

[7]  W. Miller,et al.  The influence of falling, fear of falling, and balance confidence on prosthetic mobility and social activity among individuals with a lower extremity amputation. , 2001, Archives of physical medicine and rehabilitation.

[8]  Jennifer Ann Lean Web , 2006 .

[9]  Aaron M. Dollar,et al.  Lower Extremity Exoskeletons and Active Orthoses: Challenges and State-of-the-Art , 2008, IEEE Transactions on Robotics.

[10]  Kathryn Ziegler-Graham,et al.  Estimating the prevalence of limb loss in the United States: 2005 to 2050. , 2008, Archives of physical medicine and rehabilitation.

[11]  Ryan Calo Open Robotics , 2010 .

[12]  L. Briguglio,et al.  THE FUTURE OF FARMING , 2021, Eureka!.

[13]  Robert E. Pinsker,et al.  Alone Together: Why We Expect More from Technology and Less from Each Other. , 2012 .

[14]  N. Engstrom An Alternative Explanation for No-Fault's 'Demise' , 2012 .

[15]  A. Maslow A Theory of Human Motivation , 1943 .

[16]  Danica Kragic,et al.  Data-Driven Grasp Synthesis—A Survey , 2013, IEEE Transactions on Robotics.

[17]  Ryan Calo Robotics and the Lessons of Cyberlaw , 2014 .

[18]  Michael Marien,et al.  Book Review: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies , 2014 .

[19]  Woodrow Hartzog,et al.  UNFAIR AND DECEPTIVE ROBOTS , 2015 .

[20]  Felix Wortmann,et al.  Internet of Things , 2015, Business & Information Systems Engineering.

[21]  Elizabeth E. Joh Policing Police Robots , 2016 .

[22]  Sergey Levine,et al.  Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection , 2016, ISER.

[23]  Ryan Calo,et al.  There is a blind spot in AI research , 2016, Nature.

[24]  Vijay Kumar,et al.  Next Generation Robotics , 2016, ArXiv.

[25]  Abhinav Gupta,et al.  Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[26]  Xinyu Liu,et al.  Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics , 2017, Robotics: Science and Systems.

[27]  Peter I. Corke,et al.  Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[28]  K. Manton The White Papers , 2018, Population Registers and Privacy in Britain, 1936—1984.

[29]  Richard Hodson,et al.  How robots are grasping the art of gripping , 2018, Nature.

[30]  L. Schieve,et al.  Prevalence and Trends of Developmental Disabilities among Children in the United States: 2009–2017 , 2019, Pediatrics.

[31]  Ken Goldberg,et al.  Learning ambidextrous robot grasping policies , 2019, Science Robotics.

[32]  Emmanuel Lemoine,et al.  Amazon Prime Air , 2019 .

[33]  Silvio Savarese,et al.  Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[34]  Robert D. Atkinson,et al.  Robotics and the Future of Production and Work , 2019 .