Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Mogens Graf Plessen"'
Autor:
Mogens Graf Plessen
Publikováno v:
Artificial Intelligence in Agriculture, Vol 5, Iss , Pp 233-239 (2021)
Within the context of in-field path planning this paper discusses freeform path fitting for the minimisation of the number of transitions between headland path and interior lanes within agricultural fields. This topic is motivated by two observations
Externí odkaz:
https://doaj.org/article/684ae351e4494999b7db4c8a954abf0f
Autor:
Mogens Graf Plessen
Publikováno v:
Artificial Intelligence in Agriculture, Vol 2, Iss , Pp 99-109 (2019)
A method for harvest planning based on the coupling of crop assignment with vehicle routing is presented. Given a setting with multiple fields, a path network connecting these, multiple depots at which a number of harvesters are initially located, th
Externí odkaz:
https://doaj.org/article/35f343a0cbe546d1b4f652e537f99018
Autor:
Mogens Graf Plessen
Publikováno v:
Biosystems Engineering. 171:16-29
This paper presents a path planning method for partial field coverage. Therefore, a specific path planning pattern is proposed. The notion is that lighter machinery with smaller storage tanks can alleviate soil compaction because of a reduced weight,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c63449e11242a61803f42dd0fcd72ab6
https://doi.org/10.1016/j.biosystemseng.2018.04.010
https://doi.org/10.1016/j.biosystemseng.2018.04.010
Publikováno v:
International Journal of Robust and Nonlinear Control. 29:5058-5077
Summary This paper proposes stochastic model predictive control as a tool for hedging derivative contracts (such as plain vanilla and exotic options) in the presence of transaction costs. The methodology combines stochastic scenario generation for th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5075e19c9f58fa572b7efcdf1bd2b79
https://doi.org/10.1002/rnc.3915
https://doi.org/10.1002/rnc.3915
Autor:
Mogens Graf Plessen, Alberto Bemporad
Publikováno v:
Biosystems Engineering. 153:28-41
A method for the control of autonomously and slowly moving agricultural machinery is presented. Special emphasis is on offline reference trajectory generation tailored for high-precision closed-loop tracking within agricultural fields using linear ti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b7ebb7165249210e609ac5d1e439263
https://doi.org/10.1016/j.biosystemseng.2016.10.019
https://doi.org/10.1016/j.biosystemseng.2016.10.019
Autor:
Mogens Graf Plessen
Within the context of biomass production, this paper proposes a method for logistics optimisation. Starting from a headquarter multiple tours are to be executed simultaneously by groups of harvesting units (HUs) and support units (SUs) to first harve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::119462d14eb67dbfcac9f3388a5cbad9
http://arxiv.org/abs/1909.10286
http://arxiv.org/abs/1909.10286
Autor:
Mogens Graf Plessen
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9783030123840
Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21186f602b070721cd33c9a4293ad870
https://doi.org/10.1007/978-3-030-12385-7_16
https://doi.org/10.1007/978-3-030-12385-7_16
Autor:
Mogens Graf Plessen
Within the context of optimising the logistics in agriculture this paper relates to optimal in-field routing for full and partial field coverage with arbitrary non-convex fields and multiple obstacle areas. It is distinguished between nine different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::666c65c0d5b0a7df6a3d908fb145ad9f
Autor:
Mogens Graf Plessen
Publikováno v:
ICMLA
Within the context of trajectory planning for autonomous vehicles this paper proposes methods for efficient encoding of motion primitives in neural networks on top of model-based and gradient-free reinforcement learning. It is distinguished between 5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef37a66a710c08bca7cb4f7cd87249b2
Publikováno v:
IFAC-PapersOnLine. 48:903-908
This paper extends previous work about optimisation algorithms for nuclear norm based subspace identification with uniformly and non-uniformly spaced frequency data to the time domain case, and compares the findings to more standard non-iterative met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64a15b506e31fe001304176ef72ec7db
https://doi.org/10.1016/j.ifacol.2015.12.245
https://doi.org/10.1016/j.ifacol.2015.12.245