BDGS-SLAM: A Probabilistic 3D Gaussian Splatting Framework for Robust SLAM in Dynamic Environments [PDF]
SensorsSimultaneous Localization and Mapping (SLAM) utilizes sensor data to concurrently construct environmental maps and estimate its own position, finding wide application in scenarios like robotic navigation and augmented reality.
Tianyu Yang +4 more
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Towards Biologically-Inspired Visual SLAM in Dynamic Environments: IPL-SLAM with Instance Segmentation and Point-Line Feature Fusion [PDF]
BiomimeticsSimultaneous Localization and Mapping (SLAM) is a fundamental technique in mobile robotics, enabling autonomous navigation and environmental reconstruction.
Jian Liu, Donghao Yao, Na Liu, Ye Yuan
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Safe and Robust Map Updating for Long-Term Operations in Dynamic Environments [PDF]
Sensors, 2023 Ensuring safe and continuous autonomous navigation in long-term mobile robot applications is still challenging. To ensure a reliable representation of the current environment without the need for periodic remapping, updating the map is recommended ...
Elisa Stefanini +3 more
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Perception-Aware Planning for Active SLAM in Dynamic Environments
Remote Sensing, 2022 This paper presents a perception-aware path planner for active SLAM in dynamic environments using micro-aerial vehicles (MAV). The “Next-Best-View” planner (NBVP planner) is combined with an active loop closing, which is called the Active Loop Closing ...
Yao Zhao +5 more
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Chaotic Genetic Algorithm based on Explicit Memory with a new Strategy for Updating and Retrieval of Memory in Dynamic Environments [PDF]
Journal of Artificial Intelligence and Data Mining, 2018 Many of the problems considered in optimization and learning assume that solutions exist in a dynamic. Hence, algorithms are required that dynamically adapt with the problem’s conditions and search new conditions.
M. Mohammadpour, H. Parvin, M. Sina
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Applied Sciences, 2022 Many real-life applications of the vehicle routing problem (VRP) occur in scenarios subject to uncertainty or dynamic conditions. Thus, for instance, traveling times or customers’ demands might be better modeled as random variables than as deterministic ...
Majsa Ammouriova +4 more
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Population-based incremental learning with associative memory for dynamic environments [PDF]
, 2008 Copyright © 2007 IEEE. Reprinted from IEEE Transactions on Evolutionary Computation. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's ...
Yang, S, Yao, X
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Dynamic-DSO: Direct Sparse Odometry Using Objects Semantic Information for Dynamic Environments
Applied Sciences, 2020 Traditional Simultaneous Localization and Mapping (SLAM) (with loop closure detection), or Visual Odometry (VO) (without loop closure detection), are based on the static environment assumption.
Chao Sheng +4 more
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Pixel-Wise Motion Segmentation for SLAM in Dynamic Environments
IEEE Access, 2020 Visual simultaneous localization and mapping (SLAM) is a key prerequisite for many mobile robotic systems. A common assumption for SLAM methods is a static environment.
Thorsten Hempel, Ayoub Al-Hamadi
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Population-based incremental learning with memory scheme for changing environments [PDF]
, 2005 Copyright @ 2005 ACMIn recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications.
Yang, S
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