Zobrazeno 1 - 10
of 15 607
pro vyhledávání: '"Semantic Mapping"'
Autor:
Igelbrink, Felix, Renz, Marian, Günther, Martin, Powell, Piper, Niecksch, Lennart, Lima, Oscar, Atzmueller, Martin, Hertzberg, Joachim
Semantic mapping is a key component of robots operating in and interacting with objects in structured environments. Traditionally, geometric and knowledge representations within a semantic map have only been loosely integrated. However, recent advanc
Externí odkaz:
http://arxiv.org/abs/2411.18147
Autor:
Cuaran, Jose, Ahluwalia, Kulbir Singh, Koe, Kendall, Uppalapati, Naveen Kumar, Chowdhary, Girish
Semantic maps are fundamental for robotics tasks such as navigation and manipulation. They also enable yield prediction and phenotyping in agricultural settings. In this paper, we introduce an efficient and scalable approach for active semantic mappi
Externí odkaz:
http://arxiv.org/abs/2412.10515
Autor:
Jiao, Jianhao, Geng, Ruoyu, Li, Yuanhang, Xin, Ren, Yang, Bowen, Wu, Jin, Wang, Lujia, Liu, Ming, Fan, Rui, Kanoulas, Dimitrios
The creation of a metric-semantic map, which encodes human-prior knowledge, represents a high-level abstraction of environments. However, constructing such a map poses challenges related to the fusion of multi-modal sensor data, the attainment of rea
Externí odkaz:
http://arxiv.org/abs/2412.00291
Autor:
Matez-Bandera, Jose-Luis, Ojeda, Pepe, Monroy, Javier, Gonzalez-Jimenez, Javier, Ruiz-Sarmiento, Jose-Raul
Robots in human-centered environments require accurate scene understanding to perform high-level tasks effectively. This understanding can be achieved through instance-aware semantic mapping, which involves reconstructing elements at the level of ind
Externí odkaz:
http://arxiv.org/abs/2411.08727
We present a novel algorithm for real-time planar semantic mapping tailored for humanoid robots navigating complex terrains such as staircases. Our method is adaptable to any odometry input and leverages GPU-accelerated processes for planar extractio
Externí odkaz:
http://arxiv.org/abs/2411.01919
Autor:
Atha, Deegan, Lei, Xianmei, Khattak, Shehryar, Sabel, Anna, Miller, Elle, Noca, Aurelio, Lim, Grace, Edlund, Jeffrey, Padgett, Curtis, Spieler, Patrick
Off-road environments pose significant perception challenges for high-speed autonomous navigation due to unstructured terrain, degraded sensing conditions, and domain-shifts among biomes. Learning semantic information across these conditions and biom
Externí odkaz:
http://arxiv.org/abs/2411.06632
Autor:
Lei, Jiuzhou, Prabhu, Ankit, Liu, Xu, Cladera, Fernando, Mortazavi, Mehrad, Ehsani, Reza, Chaudhari, Pratik, Kumar, Vijay
Automated persistent and fine-grained monitoring of orchards at the individual tree or fruit level helps maximize crop yield and optimize resources such as water, fertilizers, and pesticides while preventing agricultural waste. Towards this goal, we
Externí odkaz:
http://arxiv.org/abs/2409.19786
In the field of autonomous driving, Bird's-Eye-View (BEV) perception has attracted increasing attention in the community since it provides more comprehensive information compared with pinhole front-view images and panoramas. Traditional BEV methods,
Externí odkaz:
http://arxiv.org/abs/2409.13912
Semantic navigation enables robots to understand their environments beyond basic geometry, allowing them to reason about objects, their functions, and their interrelationships. In semantic robotic navigation, creating accurate and semantically enrich
Externí odkaz:
http://arxiv.org/abs/2410.14851