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pro vyhledávání: '"Römer, Ralf"'
Learning models or control policies from data has become a powerful tool to improve the performance of uncertain systems. While a strong focus has been placed on increasing the amount and quality of data to improve performance, data can never fully e
Externí odkaz:
http://arxiv.org/abs/2403.09504
Publikováno v:
IEEE Robotics and Automation Letters, vol. 8, no. 11, pp. 7825-7832, 2023
For safe operation, a robot must be able to avoid collisions in uncertain environments. Existing approaches for motion planning under uncertainties often assume parametric obstacle representations and Gaussian uncertainty, which can be inaccurate. Wh
Externí odkaz:
http://arxiv.org/abs/2209.06936
Akademický článek
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For safe operation, a robot must be able to avoid collisions in uncertain environments. Existing approaches for motion planning with uncertainties often make conservative assumptions about Gaussianity and the obstacle geometry. While visual perceptio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::355053b9d448a927b827d46ecf710dea