Multiple hypothesis semantic mapping for robust data association
In this letter, we present a semantic mapping approach with multiple hypothesis tracking for
data association. As semantic information has the potential to overcome ambiguity in …
data association. As semantic information has the potential to overcome ambiguity in …
Probabilistic data association for semantic slam
Traditional approaches to simultaneous localization and mapping (SLAM) rely on low-level
geometric features such as points, lines, and planes. They are unable to assign semantic …
geometric features such as points, lines, and planes. They are unable to assign semantic …
Multimodal semantic slam with probabilistic data association
The recent success of object detection systems motivates object-based representations for
robot navigation; ie semantic simultaneous localization and mapping (SLAM). The semantic …
robot navigation; ie semantic simultaneous localization and mapping (SLAM). The semantic …
Robust non-gaussian semantic simultaneous localization and mapping
KJ Doherty - 2019 - dspace.mit.edu
The recent success of object detection systems motivates object-based representations for
robot navigation; ie semantic simultaneous localization and mapping (SLAM), in which we …
robot navigation; ie semantic simultaneous localization and mapping (SLAM), in which we …
Not only look but infer: Multiple hypothesis clustering of data association inference for semantic SLAM
T Ran, L Yuan, J Zhang, L He… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In semantic visual simultaneous localization and mapping (VSLAM), accurate data
association of semantic measurement from visual sensor is very crucial for robot state …
association of semantic measurement from visual sensor is very crucial for robot state …
Representing and updating objects' identities in semantic SLAM
Simultaneous localization and mapping (SLAM) deals with localizing and mapping in
unknown environment. Semantic SLAM incorporates an additional layer of objects identities …
unknown environment. Semantic SLAM incorporates an additional layer of objects identities …
Probabilistic data association via mixture models for robust semantic SLAM
KJ Doherty, DP Baxter, E Schneeweiss… - … on Robotics and …, 2020 - ieeexplore.ieee.org
Modern robotic systems sense the environment geometrically, through sensors like
cameras, lidar, and sonar, as well as semantically, often through visual models learned from …
cameras, lidar, and sonar, as well as semantically, often through visual models learned from …
Bayesian nonparametric object association for semantic SLAM
J Zhang, L Yuan, T Ran, Q Tao… - IEEE Robotics and …, 2021 - ieeexplore.ieee.org
Semantic simultaneous localization and mapping (SLAM) can provide the foundation for
robots to perform more advanced tasks than traditional geometric SLAM. Object association …
robots to perform more advanced tasks than traditional geometric SLAM. Object association …
Probabilistic data association for semantic SLAM at scale
With advances in image processing and machine learning, it is now feasible to incorporate
semantic information into the problem of simultaneous localisation and mapping (SLAM) …
semantic information into the problem of simultaneous localisation and mapping (SLAM) …
Accurate object association and pose updating for semantic SLAM
Current pandemic has caused the medical system to operate under high load. To relieve it,
robots with high autonomy can be used to effectively execute contactless operations in …
robots with high autonomy can be used to effectively execute contactless operations in …