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TwistSLAM: Constrained SLAM in Dynamic Environment
- Source :
- IEEE Robotics and Automation Letters, IEEE Robotics and Automation Letters, 2022, 7 (3), pp.6846-6853, HAL
- Publication Year :
- 2022
- Publisher :
- HAL CCSD, 2022.
-
Abstract
- Classical visual simultaneous localization and mapping (SLAM) algorithms usually assume the environment to be rigid. This assumption limits the applicability of those algorithms as they are unable to accurately estimate the camera poses and world structure in real life scenes containing moving objects (e.g. cars, bikes, pedestrians, etc.). To tackle this issue, we propose TwistSLAM: a semantic, dynamic and stereo SLAM system that can track dynamic objects in the environment. Our algorithm creates clusters of points according to their semantic class. Thanks to the definition of inter-cluster constraints modeled by mechanical joints (function of the semantic class), a novel constrained bundle adjustment is then able to jointly estimate both poses and velocities of moving objects along with the classical world structure and camera trajectory. We evaluate our approach on several sequences from the public KITTI dataset and demonstrate quantitatively that it improves camera and object tracking compared to state-of-the-art approaches.<br />Comment: This work has been accepted at IEEE Robotics and Automation Letters
- Subjects :
- FOS: Computer and information sciences
Control and Optimization
Mechanical Engineering
Computer Vision and Pattern Recognition (cs.CV)
[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]
Computer Science - Computer Vision and Pattern Recognition
Biomedical Engineering
Computer Science Applications
Human-Computer Interaction
Computer Science - Robotics
Mapping
Artificial Intelligence
Control and Systems Engineering
Localization
SLAM
[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]
Computer Vision and Pattern Recognition
Robotics (cs.RO)
Subjects
Details
- Language :
- English
- ISSN :
- 23773766
- Database :
- OpenAIRE
- Journal :
- IEEE Robotics and Automation Letters, IEEE Robotics and Automation Letters, 2022, 7 (3), pp.6846-6853, HAL
- Accession number :
- edsair.doi.dedup.....729e2bd9da898cd7380c6f4405615637