Particle Filter SLAM with High Dimensional Vehicle Model

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Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering (2015, methodology): “To deal with the high-dimensional state-vector, Törnqvist et al. (2009) used a Rao-Blackwellized PF (see Appendix A) to solve the filtering problem, marginalizing all but 6 state components (being the pose, i.”
Survey on Computer Vision for UAVs: Current Developments and Trends (2017, methodology): “Furthermore, in [69] a particle filter approach for the SLAM method has been presented, where an IMU and a camera were mounted on-board the RMAX aircraft and fused.”
Indoor Tracking: Theory, Methods, and Technologies (2015, background): “Finally, the computational demands of SLAM techniques are generally high [75].”
Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems (2012, unknown): “…detect obstacles or to guide the vehicle through free spaces (Artieda et al., 2009; Bryson & Sukkarieh, 2009; Caballero et al., 2009; Kanade et al., 2004; Kendoul, Fantoni, & Nonami, 2009; Kima & Sukkarieh, 2007; Lemaire, Berger, Jung, & Lacroix, 2007; Nemra & Aouf, 2009; Tornqvist et al., 2009).”