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OctoMap: an efficient probabilistic 3D mapping framework based on octrees
TLDR
An open-source framework to generate volumetric 3D environment models based on octrees and uses probabilistic occupancy estimation that represents not only occupied space, but also free and unknown areas and an octree map compression method that keeps the 3D models compact.
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
TLDR
A large dataset to propel research on laser-based semantic segmentation, which opens the door for the development of more advanced methods, but also provides plentiful data to investigate new research directions.
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
Recently, Rao-Blackwellized particle filters (RBPF) have been introduced as an effective means to solve the simultaneous localization and mapping problem. This approach uses a particle filter in
A Tutorial on Graph-Based SLAM
TLDR
An introductory description to the graph-based SLAM problem is provided and a state-of-the-art solution that is based on least-squares error minimization and exploits the structure of the SLAM problems during optimization is discussed.
Coordinated multi-robot exploration
TLDR
This paper presents an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility and describes how this algorithm can be extended to situations in which the communication range of the robots is limited.
RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation
TLDR
This paper proposes a novel post-processing algorithm that deals with problems arising from this intermediate representation of range images as an intermediate representation in combination with a Convolutional Neural Network exploiting the rotating LiDAR sensor model.
Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling
TLDR
Adapt techniques to reduce the number of particles in a Rao-Blackwellized particle filter for learning grid maps are presented and an approach to selectively carry out re-sampling operations which seriously reduces the problem of particle depletion is presented.
OctoMap : A Probabilistic , Flexible , and Compact 3 D Map Representation for Robotic Systems
TLDR
This paper presents an approach for modeling 3D environments based on octrees using a probabilistic occupancy estimation that is able to represent full 3D models including free and unknown areas and provides a detailed review of existing approaches to 3D modeling.
Robust map optimization using dynamic covariance scaling
Developing the perfect SLAM front-end that produces graphs which are free of outliers is generally impossible due to perceptual aliasing. Therefore, optimization back-ends need to be able to deal
A Tree Parameterization for Efficiently Computing Maximum Likelihood Maps using Gradient Descent
TLDR
This paper applies a novel parameterization of the nodes in the graph that significantly improves the performance and enables the algorithm to cope with arbitrary network topologies and converge faster than the other approaches and yields accurate maps of the environment.
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