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2015


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Gaussian Process Optimization for Self-Tuning Control

Marco, A.

Polytechnic University of Catalonia (BarcelonaTech), October 2015 (mastersthesis)

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PDF Project Page [BibTex]

2015


PDF Project Page [BibTex]


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Adaptive and Learning Concepts in Hydraulic Force Control

Doerr, A.

University of Stuttgart, September 2015 (mastersthesis)

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[BibTex]

[BibTex]


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Policy Search for Imitation Learning

Doerr, A.

University of Stuttgart, January 2015 (thesis)

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Novel plasticity rule can explain the development of sensorimotor intelligence

Der, R., Martius, G.

Proceedings of the National Academy of Sciences, 112(45):E6224-E6232, 2015 (article)

Abstract
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no system-specific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking, which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Quantifying Emergent Behavior of Autonomous Robots

Martius, G., Olbrich, E.

Entropy, 17(10):7266, 2015 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]

2014


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Wenn es was zu sagen gibt

(Klaus Tschira Award 2014 in Computer Science)

Trimpe, S.

Bild der Wissenschaft, pages: 20-23, November 2014, (popular science article in German) (article)

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PDF Project Page [BibTex]

2014


PDF Project Page [BibTex]


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A Limiting Property of the Matrix Exponential

Trimpe, S., D’Andrea, R.

IEEE Transactions on Automatic Control, 59(4):1105-1110, 2014 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Event-Based State Estimation With Variance-Based Triggering

Trimpe, S., D’Andrea, R.

IEEE Transactions on Automatic Control, 59(12):3266-3281, 2014 (article)

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PDF Supplementary material DOI Project Page [BibTex]

PDF Supplementary material DOI Project Page [BibTex]

2009


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A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior

Hesse, F., Martius, G., Der, R., Herrmann, J. M.

Algorithms, 2(1):398-409, 2009 (article)

Abstract
Ideally, sensory information forms the only source of information to a robot. We consider an algorithm for the self-organization of a controller. At short timescales the controller is merely reactive but the parameter dynamics and the acquisition of knowledge by an internal model lead to seemingly purposeful behavior on longer timescales. As a paradigmatic example, we study the simulation of an underactuated snake-like robot. By interacting with the real physical system formed by the robotic hardware and the environment, the controller achieves a sensitive and body-specific actuation of the robot.

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link (url) [BibTex]

2009


link (url) [BibTex]