Special Issue on Deep Learning and Machine Learning in Robotics

Name for Papers

Deep studying and Machine Studying have gone by way of a large development prior to now a number of years. In lots of domains, comparable to notion, imaginative and prescient, picture recognition, picture captioning, speech recognition, machine translation, and board video games, particularly, deep studying has drastically outperformed conventional strategies and overtaken them to turn into the tactic of alternative. Will the identical occur to robotics and automation? These approaches usually require large quantities of labeled information, i.e., large information, and big quantities of compute. In lots of actual robotics and automation functions information is ample however labeling sparse and costly. (Deep) reinforcement studying usually requires considerably extra iterations than are possible on actual methods. Therefore gathering adequate quantities of information is impractical at finest. Subsequently, plenty of work is finished in purely digital or digital environments. On this particular subject we’ll concentrate on approaches which have been validated on actual world robots, eventualities, and automation issues. Whereas plenty of progress has been achieved on this entrance in robotic and automation functions, nonetheless plenty of progress must be made as a way to render deep studying approaches instantly relevant. Robots and automation methods are interacting with the true world. Therefore errors that may be expensive by way of misplaced income in approaches that function in a purely digital world, may cause important injury and lack of human lives. Subsequently, secure studying turns into paramount. A associated subject is interpretable studying, i.e. the aptitude to interpret studying processes, transferring in the direction of approaches the place people have the choice to be in management and perceive with adequate human-readable particulars the choice processes of the machine. Profitable functions in ‘neighboring’ fields characterised by restricted quantities of sparse, labeled information coming from bodily methods can even be thought of.

Papers ought to observe the usual RAM tips. A full peer-review course of will probably be utilized to pick papers for the particular subject. Submissions needs to be made by way of the RAM submission web site by August 1, 2019.

Contributions are anticipated to current authentic analysis on deep studying and machine studying with actual world functions in robotics and automation.

Subjects of Curiosity

• deep/machine studying

  • supervised
  • unsupervised
  • reinforcement

• pattern environment friendly studying

  • new strategies
  • use of fashions
  • simulation to actual switch
  • information augmentation
  • embedding prior data
  • …

• secure studying

  • confidence estimates
  • ensures
  • verification
  • interpretable studying
  • …

• actual functions and use case eventualities of deep/machine studying

  • robotics

    • notion
    • management
    • planning
    • navigation
    • manipulation and greedy
    • …

  • automation

    • upkeep and inspection
    • manufacturing
    • high quality administration and assurance
    • product monitoring
    • …

  • success tales of deep/machine studying applied sciences in robotics and automation
  • widespread points and options in deep/machine studying functions in robotics and automation and neighboring fields comparable to:

    • gravitational waves detection
    • geophysics
    • excessive vitality physics
    • …

Tentative Schedule/Vital Dates

15 September 2019  1 August 2019 – Submission deadline EXTENDED
15 November 2019  1 November 2019 – First determination communicated to authors EXTENDED
1 January 2020 15 December 2019 – Revised paper submitted EXTENDED
20 February 2020 – Last acceptance determination communicated to authors
10 March 2020 – Last manuscripts uploaded by authors
10 June 2020 – Particular subject

Visitor Editors

Particular Challenge- Deep Studying and Machine Studying in Robotics Visitor Editors

Particular Challenge on Deep Studying and Machine Studying in Robotics

Particular Challenge on Deep Studying and Machine Studying in Robotics

Heron Robots and Scuola Superiore Sant’Anna, Italy
Italy

Particular Challenge on Deep Studying and Machine Studying in Robotics

Nationwide College of Singapore
Singapore

Particular Challenge on Deep Studying and Machine Studying in Robotics

College of Michigan
Ann Arbor, Michigan, USA

Particular Challenge on Deep Studying and Machine Studying in Robotics

Delft College of Know-how
Delft, Netherlands