SELFCEPTION
Robotic self/other distinction for interaction under uncertainty
Total Cost €
0EC-Contrib. €
0Partnership
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0SELFCEPTION project word cloud
Explore the words cloud of the SELFCEPTION project. It provides you a very rough idea of what is the project "SELFCEPTION" about.
Project "SELFCEPTION" data sheet
The following table provides information about the project.
| Coordinator |
TECHNISCHE UNIVERSITAET MUENCHEN
Organization address contact info |
| Coordinator Country | Germany [DE] |
| Project website | http://www.selfception.eu |
| Total cost | 159˙460 € |
| EC max contribution | 159˙460 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2016 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2017 |
| Duration (year-month-day) | from 2017-05-01 to 2019-04-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | TECHNISCHE UNIVERSITAET MUENCHEN | DE (MUENCHEN) | coordinator | 159˙460.00 |
Map
Project objective
There will be around 35 million private or non-industrial use robots in the world by 2018, a market of 19 billion euros. However, autonomous robot technology in Europe is not yet ready to lead this high expectancy due to the lack of robust functionality in uncertain environments. Particularly, safe interaction is an essential requirement. A basic skill, still unachieved, is to allow the robot to be aware of its own body and perceive other agents. Recent evidence suggests that self/other distinction will be a major breakthrough for improving interaction and might be the connection between low-level sensorimotor abilities and conceptual interpretation.
Advanced sensorimotor learning combined with new multimodal sensing devices, such as artificial skin, makes now possible that the robot acquires its perceptual representation, and I hypothesize that learning the multisensory-motor spatiotemporal contingencies permits self/other distinction. Hence, the aim of the project is to provide a hierarchical probabilistic model for self/other distinction in robots, learning the sensorimotor contingencies during interaction. This model not only provides a holistic solution for building the perceptual schema and improves interaction under uncertainty but it might also give insights about how humans construct their own perceptual representation and the sense of agency. Finally, the model will be tested in a whole body sensing humanoid and validated in a service robot in collaboration with a robotics SME. I will use an interdisciplinary approach that combines probabilistic and information sciences modelling with cognitive psychology, creating a highly attractive career profile.
SELFCEPTION will boost the materialization of the next generation of perceptive robots: multisensory machines able to build their perceptual body schema and distinguish their actions from other entities. We already have robots that navigate and now it is the time to develop robots that interact.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2019 |
Michael Deistler, Yagmur Yener, Florian Bergner, Pablo Lanillos, Gordon Cheng Tactile Hallucinations on Artificial Skin Induced by Homeostasis in a Deep Boltzmann Machine published pages: , ISSN: , DOI: |
2019 IEEE International Conference on Cyborg and Bionic Systems | 2019-09-30 |
| 2019 |
Guillermo Oliver, Pablo Lanillos, Gordon Cheng Active inference body perception and action for humanoid robots published pages: , ISSN: 2377-3766, DOI: |
IEEE Robotics and Automation Letters 2/4 | 2019-09-30 |
| 2018 |
Hinz, Nina-Alisa; Lanillos, Pablo; Mueller, Hermann; Cheng, Gordon Drifting perceptual patterns suggest prediction errors fusion rather than hypothesis selection: replicating the rubber-hand illusion on a robot published pages: , ISSN: 2161-9484, DOI: |
IEEE Developmental Learning and Epigenetic Robotics (ICDL-Epirob) | 2019-09-30 |
| 2018 |
Diez-Valencia, German; Ohashi, Takuya; Lanillos, Pablo; Cheng, Gordon Sensorimotor learning for artificial body perception published pages: , ISSN: , DOI: |
Workshop on Crossmodal Learning for Intelligent Robotics. IEEE Int. Conference on Intelligent Robots and Systems (IROS 2018) | 2019-09-30 |
| 2018 |
Pablo Lanillos and Gordon Cheng Active inference with function learning for robot body perception published pages: , ISSN: , DOI: |
International Workshop on Continual Unsupervised Sensorimotor Learning, IEEE Developmental Learning and Epigenetic Robotics (ICDL-Epirob) | 2019-09-30 |
| 2017 |
Mohsen Kaboli, Di Feng, Kunpeng Yao, Pablo Lanillos, Gordon Cheng A Tactile-Based Framework for Active Object Learning and Discrimination using Multimodal Robotic Skin published pages: 2143-2150, ISSN: 2377-3766, DOI: 10.1109/lra.2017.2720853 |
IEEE Robotics and Automation Letters 2/4 | 2019-09-30 |
| 2019 |
Lanillos, P., Oliva, D, Philippsen, A., Nagai, Y., Cheng, G A Review on Neural Network Models of Schizophrenia and Autism Spectrum Disorder published pages: , ISSN: 0893-6080, DOI: |
Neural Networks | 2019-09-30 |
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