Learning tactile skills through curious exploration
Frontiers in Neurorobotics, ISSN: 1662-5218, Vol: 6, Issue: JULY, Page: 6
2012
- 42Citations
- 130Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations42
- Citation Indexes42
- 42
- CrossRef18
- Captures130
- Readers130
- 130
Article Description
We present curiosity-driven, autonomous acquisition of tactile exploratory skills on a biomimetic robot finger equipped with an array of microelectromechanical touch sensors. Instead of building tailored algorithms for solving a specific tactile task, we employ a more general curiosity-driven reinforcement learning approach that autonomously learns a set of motor skills in absence of an explicit teacher signal. In this approach, the acquisition of skills is driven by the information content of the sensory input signals relative to a learner that aims at representing sensory inputs using fewer and fewer computational resources. We show that, from initially random exploration of its environment, the robotic system autonomously develops a small set of basic motor skills that lead to different kinds of tactile input. Next, the system learns how to exploit the learned motor skills to solve supervised texture classification tasks. Our approach demonstrates the feasibility of autonomous acquisition of tactile skills on physical robotic platforms through curiosity-driven reinforcement learning, overcomes typical difficulties of engineered solutions for active tactile exploration and underactuated control, and provides a basis for studying developmental learning through intrinsic motivation in robots. © 2012 Pape, Oddo, Controzzi, Cipriani, Förster, Carrozza and Schmidhuber.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84866027577&origin=inward; http://dx.doi.org/10.3389/fnbot.2012.00006; http://www.ncbi.nlm.nih.gov/pubmed/22837748; http://journal.frontiersin.org/article/10.3389/fnbot.2012.00006/abstract; https://dx.doi.org/10.3389/fnbot.2012.00006; https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2012.00006/full
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