Zobrazeno 1 - 10
of 1 062
pro vyhledávání: '"Informative path planning"'
Navigating efficiently to an object in an unexplored environment is a critical skill for general-purpose intelligent robots. Recent approaches to this object goal navigation problem have embraced a modular strategy, integrating classical exploration
Externí odkaz:
http://arxiv.org/abs/2410.19697
Informative path planning (IPP) is an important planning paradigm for various real-world robotic applications such as environment monitoring. IPP involves planning a path that can learn an accurate belief of the quantity of interest, while adhering t
Externí odkaz:
http://arxiv.org/abs/2410.17186
Autor:
Rückin, Julius, Morilla-Cabello, David, Stachniss, Cyrill, Montijano, Eduardo, Popović, Marija
Robots are frequently tasked to gather relevant sensor data in unknown terrains. A key challenge for classical path planning algorithms used for autonomous information gathering is adaptively replanning paths online as the terrain is explored given l
Externí odkaz:
http://arxiv.org/abs/2410.17166
Autor:
Kiessling, Alexander, Torroba, Ignacio, Sidrane, Chelsea Rose, Stenius, Ivan, Tumova, Jana, Folkesson, John
Informative path planning (IPP) applied to bathymetric mapping allows AUVs to focus on feature-rich areas to quickly reduce uncertainty and increase mapping efficiency. Existing methods based on Bayesian optimization (BO) over Gaussian Process (GP) m
Externí odkaz:
http://arxiv.org/abs/2410.15720
Multi-Robot Informative Path Planning for Efficient Target Mapping using Deep Reinforcement Learning
Autonomous robots are being employed in several mapping and data collection tasks due to their efficiency and low labor costs. In these tasks, the robots are required to map targets-of-interest in an unknown environment while constrained to a given r
Externí odkaz:
http://arxiv.org/abs/2409.16967
Autor:
Gadipudi, Srikar Babu, Deolasee, Srujan, Kailas, Siva, Luo, Wenhao, Sycara, Katia, Kim, Woojun
Informative path planning (IPP) is a crucial task in robotics, where agents must design paths to gather valuable information about a target environment while adhering to resource constraints. Reinforcement learning (RL) has been shown to be effective
Externí odkaz:
http://arxiv.org/abs/2409.16830
The ability to traverse an unknown environment is crucial for autonomous robot operations. However, due to the limited sensing capabilities and system constraints, approaching this problem with a single robot agent can be slow, costly, and unsafe. Fo
Externí odkaz:
http://arxiv.org/abs/2406.05313
Autor:
Nguyen, Binh, Nguyen, Linh, Nghiem, Truong X., La, Hung, Baca, Jose, Rangel, Pablo, Montoya, Miguel Cid, Nguyen, Thang
This paper investigates the problem of informative path planning for a mobile robotic sensor network in spatially temporally distributed mapping. The robots are able to gather noisy measurements from an area of interest during their movements to buil
Externí odkaz:
http://arxiv.org/abs/2403.16489
Adaptive informative path planning (AIPP) is important to many robotics applications, enabling mobile robots to efficiently collect useful data about initially unknown environments. In addition, learning-based methods are increasingly used in robotic
Externí odkaz:
http://arxiv.org/abs/2404.06940
We consider the problem of an autonomous agent equipped with multiple sensors, each with different sensing precision and energy costs. The agent's goal is to explore the environment and gather information subject to its resource constraints in unknow
Externí odkaz:
http://arxiv.org/abs/2404.18374