Proceedings ArticleDOI
An object-based semantic world model for long-term change detection and semantic querying
Mason Julian M,Bhaskara Marthi +1 more
- pp 3851-3858
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TLDR
This work describes and experimentally verify a semantic querying system aboard a mobile robot equipped with a Microsoft Kinect RGB-D sensor, which allows the system to operate in large, dynamic, and uncon-strained environments, where modeling every object that occurs or might occur is impractical.Abstract:
Recent years have seen rising interest in robotic mapping algorithms that operate at the level of objects, rather than two- or three-dimensional occupancy. Such “semantic maps” permit higher-level reasoning than occupancy maps, and are useful for any application that involves dealing with objects, including grasping, change detection, and object search. We describe and experimentally verify such a system aboard a mobile robot equipped with a Microsoft Kinect RGB-D sensor. Our representation is object-based, and makes uniquely weak assumptions about the quality of the perceptual data available; in particular, we perform no explicit object recognition. This allows our system to operate in large, dynamic, and uncon-strained environments, where modeling every object that occurs (or might occur) is impractical. Our dataset, which is publicly available, consists of 67 autonomous runs of our robot over a six-week period in a roughly 1600m2 office environment. We demonstrate two applications built on our system: semantic querying and change detection.read more
Citations
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Journal ArticleDOI
Artificial Intelligence for Long-Term Robot Autonomy: A Survey
TL;DR: In this paper, the authors survey and discuss AI techniques as enablers for long-term robot autonomy, current progress in integrating these techniques within long-running robotic systems, and the future challenges and opportunities for AI in longterm autonomy.
Journal ArticleDOI
RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach
Luis Riazuelo,Moritz Tenorth,Daniel Di Marco,Marta Salas,Dorian Galvez-Lopez,Lorenz Mösenlechner,Lars Kunze,Michael Beetz,Juan D. Tardós,Luis Montano,J. M. Martinez Montiel +10 more
TL;DR: This work describes the RoboEarth semantic mapping system and shows the synergetic relation of the SLAM map of objects that grounds the terminological knowledge coded in the ontology.
Proceedings ArticleDOI
Collar Line Segments for fast odometry estimation from Velodyne point clouds
TL;DR: Evaluation using the KITTI dataset shows that the method outperforms publicly available and commonly used state-of-the-art method GICP for point cloud registration in both accuracy and speed, especially in cases where the scene lacks significant landmarks or in typical urban elements.
Proceedings ArticleDOI
Meta-rooms : Building and Maintaining Long Term Spatial Models in a Dynamic World
TL;DR: A novel method for re-creating the static structure of cluttered office environments from multiple observations collected by an autonomous robot equipped with an RGB-D depth camera over extended periods of time is presented.
Journal ArticleDOI
Data association for semantic world modeling from partial views
TL;DR: Novel clustering-based approaches to the problem of estimating world models from semantic perception modules that provide noisy observations of attributes are presented, which are more efficient and require less severe approximations compared with existing tracking- based approaches.
References
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Proceedings Article
ROS: an open-source Robot Operating System
TL;DR: This paper discusses how ROS relates to existing robot software frameworks, and briefly overview some of the available application software which uses ROS.
Proceedings ArticleDOI
3D is here: Point Cloud Library (PCL)
Radu Bogdan Rusu,Steve Cousins +1 more
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Journal ArticleDOI
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
TL;DR: In this article, the authors proposed an approach to compute an accurate proposal distribution, taking into account not only the movement of the robot, but also the most recent observation, which drastically decreases the uncertainty about the robot's pose in the prediction step of the filter.
Proceedings ArticleDOI
Describing objects by their attributes
TL;DR: This paper proposes to shift the goal of recognition from naming to describing, and introduces a novel feature selection method for learning attributes that generalize well across categories.
Proceedings ArticleDOI
High resolution maps from wide angle sonar
Hans P. Moravec,Alberto Elfes +1 more
TL;DR: The use of multiple wide-angle sonar range measurements to map the surroundings of an autonomous mobile robot deals effectively with clutter, and can be used for motion planning and for extended landmark recognition.
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