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1993


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Roles for memory-based learning in robotics

Atkeson, C. G., Schaal, S.

In Proceedings of the Sixth International Symposium on Robotics Research, pages: 503-521, Hidden Valley, PA, 1993, clmc (inproceedings)

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[BibTex]

1993


[BibTex]


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Design concurrent calculation: A CAD- and data-integrated approach

Schaal, S., Ehrlenspiel, K.

Journal of Engineering Design, 4, pages: 71-85, 1993, clmc (article)

Abstract
Besides functional regards, product design demands increasingly more for further reaching considerations. Quality alone cannot suffice anymore to compete in the market; design for manufacturability, for assembly, for recycling, etc., are well-known keywords. Those can largely be reduced to the necessity of design for costs. This paper focuses on a CAD-based approach to design concurrent calculation. It will discuss how, in the meantime well-established, tools like feature technology, knowledge-based systems, and relational databases can be blended into one coherent concept to achieve an entirely CAD- and data-integrated cost information tool. This system is able to extract data from the CAD-system, combine it with data about the company specific manufacturing environment, and subsequently autonomously evaluate manufacturability aspects and costs of the given CAD-model. Within minutes the designer gets quantitative in-formation about the major cost sources of his/her design. Additionally, some alternative methods for approximating manu-facturing times from empirical data, namely neural networks and local weighted regression, are introduced.

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[BibTex]

[BibTex]


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Open loop stable control strategies for robot juggling

Schaal, S., Atkeson, C. G.

In IEEE International Conference on Robotics and Automation, 3, pages: 913-918, Piscataway, NJ: IEEE, Georgia, Atlanta, May 2-6, 1993, clmc (inproceedings)

Abstract
In a series of case studies out of the field of dynamic manipulation (Mason, 1992), different principles for open loop stable control are introduced and analyzed. This investigation may provide some insight into how open loop control can serve as a useful foundation for closed loop control and, particularly, what to focus on in learning control. 

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link (url) [BibTex]

link (url) [BibTex]


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In vivo diabetic wound healing with nanofibrous scaffolds modified with gentamicin and recombinant human epidermal growth factor

Dwivedi, C., Pandey, I., Pandey, H., Patil, S., Mishra, S. B., Pandey, A. C., Zamboni, P., Ramteke, P. W., Singh, A. V.

Journal of Biomedical Materials Research Part A, 106(3):641-651, March (article)

Abstract
Abstract Diabetic wounds are susceptible to microbial infection. The treatment of these wounds requires a higher payload of growth factors. With this in mind, the strategy for this study was to utilize a novel payload comprising of Eudragit RL/RS 100 nanofibers carrying the bacterial inhibitor gentamicin sulfate (GS) in concert with recombinant human epidermal growth factor (rhEGF); an accelerator of wound healing. GS containing Eudragit was electrospun to yield nanofiber scaffolds, which were further modified by covalent immobilization of rhEGF to their surface. This novel fabricated nanoscaffold was characterized using scanning electron microscopy, Fourier transform infrared spectroscopy, and X‐ray diffraction. The thermal behavior of the nanoscaffold was determined using thermogravimetric analysis and differential scanning calorimetry. In the in vitro antibacterial assays, the nanoscaffolds exhibited comparable antibacterial activity to pure gentemicin powder. In vivo work using female C57/BL6 mice, the nanoscaffolds induced faster wound healing activity in dorsal wounds compared to the control. The paradigm in this study presents a robust in vivo model to enhance the applicability of drug delivery systems in wound healing applications. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 641–651, 2018.

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link (url) DOI [BibTex]


link (url) DOI [BibTex]


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Classified Regression for Bayesian Optimization: Robot Learning with Unknown Penalties

Marco, A., Baumann, D., Hennig, P., Trimpe, S.

Submitted to Journal (under review) (article)

Abstract
Learning robot controllers by minimizing a black-box objective cost using Bayesian optimization (BO) can be time-consuming and challenging. It is very often the case that some roll-outs result in failure behaviors, causing premature experiment detention. In such cases, the designer is forced to decide on heuristic cost penalties because the acquired data is often scarce, or not comparable with that of the stable policies. To overcome this, we propose a Bayesian model that captures exactly what we know about the cost of unstable controllers prior to data collection: Nothing, except that it should be a somewhat large number. The resulting Bayesian model, approximated with a Gaussian process, predicts high cost values in regions where failures are likely to occur. In this way, the model guides the BO exploration toward regions of stability. We demonstrate the benefits of the proposed model in several illustrative and statistical synthetic benchmarks, and also in experiments on a real robotic platform. In addition, we propose and experimentally validate a new BO method to account for unknown constraints. Such method is an extension of Max-Value Entropy Search, a recent information-theoretic method, to solve unconstrained global optimization problems.

PDF link (url) [BibTex]


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test jon
(book)

[BibTex]


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test
(article)

[BibTex]

[BibTex]


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Geometric Image Synthesis

Alhaija, H. A., Mustikovela, S. K., Geiger, A., Rother, C.

(conference)

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Project Page [BibTex]

Project Page [BibTex]


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Robotics Research

Tong, Chi Hay, Furgale, Paul, Barfoot, Timothy D, Guizilini, Vitor, Ramos, Fabio, Chen, Yushan, T\uumová, Jana, Ulusoy, Alphan, Belta, Calin, Tenorth, Moritz, others

(article)

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[BibTex]

[BibTex]