Zobrazeno 1 - 10
of 34 812
pro vyhledávání: '"Replanning"'
Autor:
Inoo, Hiroyuki1 (AUTHOR), Sakanaka, Katsuyuki1 (AUTHOR) sakanaka@kuhp.kyoto-u.ac.jp, Mizowaki, Takashi1 (AUTHOR)
Publikováno v:
Scientific Reports. 10/10/2024, Vol. 14 Issue 1, p1-9. 9p.
During the Mars ascent vehicle (MAV) launch missions, when encountering a thrust drop type of propulsion system fault problem, the general trajectory replanning methods relying on step-by-step judgments may fail to make timely decisions, potentially
Externí odkaz:
http://arxiv.org/abs/2409.19536
Autor:
Sivaramakrishnan, Aravind, Tangirala, Sumanth, Ramesh, Dhruv Metha, Granados, Edgar, Bekris, Kostas E.
This paper aims to increase the safety and reliability of executing trajectories planned for robots with non-trivial dynamics given a light-weight, approximate dynamics model. Scenarios include mobile robots navigating through workspaces with imperfe
Externí odkaz:
http://arxiv.org/abs/2409.11522
Multi-robot collaboration for target tracking presents significant challenges in hazardous environments, including addressing robot failures, dynamic priority changes, and other unpredictable factors. Moreover, these challenges are increased in adver
Externí odkaz:
http://arxiv.org/abs/2409.11230
Movement Primitives (MPs) are a well-established method for representing and generating modular robot trajectories. This work presents FA-ProDMP, a new approach which introduces force awareness to Probabilistic Dynamic Movement Primitives (ProDMP). F
Externí odkaz:
http://arxiv.org/abs/2409.11144
Pre-explored Semantic Maps, constructed through prior exploration using visual language models (VLMs), have proven effective as foundational elements for training-free robotic applications. However, existing approaches assume the map's accuracy and d
Externí odkaz:
http://arxiv.org/abs/2409.04837
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Thoracic bulky esophageal cancer shrinks during radiotherapy, changing the location and shape of the surrounding heart and lungs. The current study aimed to explore how replanning by volumetric-modulated arc radiotherapy (VMAT) and three-dim
Externí odkaz:
https://doaj.org/article/333f1e733b204c7e949d2af4f89ee3e7
Large language models (LLMs) have gained increasing popularity in robotic task planning due to their exceptional abilities in text analytics and generation, as well as their broad knowledge of the world. However, they fall short in decoding visual cu
Externí odkaz:
http://arxiv.org/abs/2407.21762
This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-based task planning in a dynamically changing environment. Unexpected changes in the environment may lead to failures in satisfying a task specification in the
Externí odkaz:
http://arxiv.org/abs/2404.01219