Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Graeme Best"'
Autor:
Graeme Best, Matthew Frantz, Gilberto Marcon dos Santos, Seth McCammon, John A. Barth, Julie A. Adams, Jonathan D. Nash, Geoffrey A. Hollinger, T. P. Welch, R. Kipp Shearman
Publikováno v:
Journal of Field Robotics. 38:854-881
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cf2922baa7537d0f362cbcf84057daa
https://doi.org/10.1002/rob.22014
https://doi.org/10.1002/rob.22014
Publikováno v:
2021 International Symposium on Multi-Robot and Multi-Agent Systems (MRS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34b5d461e59e2ed642cf9b1074397943
https://doi.org/10.1109/mrs50823.2021.9620693
https://doi.org/10.1109/mrs50823.2021.9620693
We present a new algorithm for deploying passenger robots in marsupial robot systems. A marsupial robot system consists of a carrier robot (e.g., a ground vehicle), which is highly capable and has a long mission duration, and at least one passenger r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77d6fac3f7cb57c05d1838e658468695
http://arxiv.org/abs/2110.10236
http://arxiv.org/abs/2110.10236
We address the problem of generating navigation roadmaps for uncertain and cluttered environments represented with probabilistic occupancy maps. A key challenge is to generate roadmaps that provide connectivity through tight passages and paths around
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18ef8f828855f0f9e9f21f55731bdd98
https://hdl.handle.net/10453/157555
https://hdl.handle.net/10453/157555
Publikováno v:
ICRA
We present an algorithm for learning behavior trees for robotic task planning, which alleviates the need for time-intensive or infeasible manual design of control architectures. Our method involves representing the search space of behavior trees as a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d2229f968a54059eb244424480b236f
https://doi.org/10.1109/icra48506.2021.9561027
https://doi.org/10.1109/icra48506.2021.9561027
Publikováno v:
IROS
Robotic exploration requires adaptively selecting navigation goals that result in the rapid discovery and mapping of an unknown world. In many real-world environments, subtle structural cues can provide insight about the unexplored world, which may b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::012f993c71d57085d1948ba9600174ff
https://doi.org/10.1109/iros45743.2020.9341170
https://doi.org/10.1109/iros45743.2020.9341170
Publikováno v:
Autonomous Robots. 43:789-811
In this paper we introduce a novel algorithm for online distributed non-myopic task-selection in heterogeneous robotic teams. Our algorithm uses a temporal probabilistic representation that allows agents to evaluate their actions in the team’s join
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef220e32f5111d579b8bde0cfcd74953
https://doi.org/10.1007/s10514-018-9811-9
https://doi.org/10.1007/s10514-018-9811-9
Publikováno v:
Autonomous Robots. 42:715-738
We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e37f811065364134db81943b87921e08
https://doi.org/10.1007/s10514-017-9691-4
https://doi.org/10.1007/s10514-017-9691-4
Publikováno v:
IEEE Transactions on Robotics. 33:629-646
© 2017 IEEE. We consider an optimal stopping formulation of the mission monitoring problem, in which a monitor vehicle must remain in close proximity to an autonomous robot that stochastically follows a predicted trajectory. This problem arises in a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f108a36dd59c7be92fb5e0463dba0313
https://doi.org/10.1109/tro.2017.2653196
https://doi.org/10.1109/tro.2017.2653196
Autor:
Geoffrey A. Hollinger, Graeme Best
Publikováno v:
MRS
This extended abstract presents a new coordination algorithm for decentralised multi-robot information gathering. We consider planning for an online variant of the multi-agent orienteering problem with neighbourhoods. This formulation closely aligns
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::abc64e8b59fbda77f76b7afbc3940bcd
https://doi.org/10.1109/mrs.2019.8901053
https://doi.org/10.1109/mrs.2019.8901053