18550944. METHOD FOR THINNING A SLAM GRAPH, METHOD FOR OPERATING A MOBILE DEVICE, AND MOBILE DEVICE simplified abstract (Robert Bosch GmbH)
Contents
- 1 METHOD FOR THINNING A SLAM GRAPH, METHOD FOR OPERATING A MOBILE DEVICE, AND MOBILE DEVICE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD FOR THINNING A SLAM GRAPH, METHOD FOR OPERATING A MOBILE DEVICE, AND MOBILE DEVICE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
METHOD FOR THINNING A SLAM GRAPH, METHOD FOR OPERATING A MOBILE DEVICE, AND MOBILE DEVICE
Organization Name
Inventor(s)
Gerhard Kurz of Karlsruhe (DE)
Matthias Holoch of Leonberg (DE)
METHOD FOR THINNING A SLAM GRAPH, METHOD FOR OPERATING A MOBILE DEVICE, AND MOBILE DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 18550944 titled 'METHOD FOR THINNING A SLAM GRAPH, METHOD FOR OPERATING A MOBILE DEVICE, AND MOBILE DEVICE
Simplified Explanation
The method described in the patent application involves thinning a SLAM graph used for operating a mobile device by removing nodes with the highest scale-invariant density at further nodes around them.
- The method involves thinning a SLAM graph used for operating a mobile device.
- Nodes are removed from the SLAM graph based on their scale-invariant density at surrounding nodes.
- The node with the highest density at further nodes is removed in each case.
- The updated SLAM graph is output after nodes are removed.
Potential Applications
The technology described in this patent application could be applied in various fields such as robotics, autonomous vehicles, augmented reality, and indoor navigation systems.
Problems Solved
This technology helps in optimizing the efficiency and accuracy of SLAM algorithms by removing unnecessary nodes from the graph, leading to improved performance and resource utilization.
Benefits
- Improved performance of SLAM algorithms.
- Enhanced accuracy in mobile device operations.
- Resource optimization in graph-based systems.
Potential Commercial Applications
- Robotics industry for navigation and mapping.
- Autonomous vehicles for localization and mapping.
- Augmented reality applications for accurate positioning.
- Indoor navigation systems for efficient route planning.
Possible Prior Art
One possible prior art in this field is the use of graph optimization techniques in SLAM algorithms to improve efficiency and accuracy. Researchers have explored various methods to optimize graph structures in SLAM systems for better performance.
Unanswered Questions
How does this method compare to existing node removal techniques in SLAM graphs?
The article does not provide a direct comparison with other node removal techniques in SLAM graphs. It would be interesting to know the specific advantages of this method over existing approaches.
What impact does node thinning have on the overall performance of the SLAM system?
While the article mentions that node thinning improves efficiency, it does not delve into the specific performance metrics or the extent of improvement achieved. Further details on the impact of node thinning on SLAM system performance would be valuable for a comprehensive understanding.
Original Abstract Submitted
A method for thinning a SLAM graph, which is used for operating a mobile device and has a multiplicity of nodes and a multiplicity of edges, each of which ends with an end point at a node. The SLAM graph is obtained, nodes are removed from the SLAM graph, and then an updated SLAM graph is output. Removing a node in each case includes determining, out of the multiplicity of nodes, the node whose scale-invariant density at further nodes around said node is the highest, and removing the determined node whose density is the highest from the SLAM graph.
