SLAM with SC-PHD Filters An Underwater Vehicle Application By Chee Sing Lee, Sharad Nagappa, Narcis Palomeras, Daniel E. Clark, and Joaquim Salvi Underwater Robotics and SLAM The subsea industry is increasingly interested in the use of autonomous underwater vehicles (AUVs) to perform inspection, maintenance, and light intervention tasks at submarine facilities. Of particular interest is the ability to have vehicles operating unattended for extended periods of time, which is a key to reducing operating costs. A critical issue in this is the vehicle's awareness of its Digital Object Identifier 10.1109/MRA.2014.2310132 Date of publication: 7 May 2014 38 * IEEE ROBOTICS & AUTOMATION MAGAZINE * T he random finite-set formulation for multiobject estimation provides a means of estimating the number of objects in cluttered environments with missed detections within a unified probabilistic framework. This methodology is now becoming the dominant mathematical framework within the sensor fusion community for developing multiple-target tracking algorithms. These techniques are also gaining traction in the field of feature-based simultaneous localization and mapping (SLAM) for mobile robotics. Here, we present one such instance of this approach with an underwater vehicle using a hierarchical multiobject estimation method for estimating both landmarks and vehicle position. June 2014 1070-9932/14/$31.00©2014IEEE