Abstract
In this paper, the observability of the conventional vector field simultaneous localization and mapping (SLAM) is examined by using the Fisher information matrix (FIM). If a mobile robot integrates sensor measurements while moving with a fixed heading, the measurements will be ambiguous because its measurement model is based on bilinear interpolation. To resolve the ambiguity, the authors proposed the novel dual-sensor-based vector-field SLAM (DV-SLAM), which is fully observable by using a mobile robot equipped with two sensors in a specific location to measure vector field signals. By examining its FIM, the condition is derived for the proposed DV-SLAM to be fully observable regardless of how the robot moves. The proposed DV-SLAM is implemented based on the Rao-Blackwellized particle filter with Earth's magnetic field sensors. Simulation and experimental results demonstrate that the proposed dual-sensor-based approach greatly improves the performance of the vector-field SLAM compared with the conventional approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
