Visual SLAM-based Localization and Navigation for Service Robots: The Pepper Case
arXiv:1811.08414 · doi:10.1007/978-3-030-27544-0_3
Abstract
We propose a Visual-SLAM based localization and navigation system for service robots. Our system is built on top of the ORB-SLAM monocular system but extended by the inclusion of wheel odometry in the estimation procedures. As a case study, the proposed system is validated using the Pepper robot, whose short-range LIDARs and RGB-D camera do not allow the robot to self-localize in large environments. The localization system is tested in navigation tasks using Pepper in two different environments: a medium-size laboratory, and a large-size hall.
12 pages, 6 figures. Presented in RoboCup Symposium 2018. Final version will appear in Springer