A comparison of inertial-based navigation algorithms for a low-cost indoor mobile robot

Reliable navigation of a low-cost mobile robot in an indoor environment can prove to be challenging as position fixing sensors, such as a GNSS receiver, are typically unavailable. Subscribing to the premise of a baseline of odometry and inertial sensors, this paper compares three navigation strategies, namely, a full 6-DOF inertial measurement unit (IMU) with kinematic constraints, a partial IMU with gyro pseudo-measurements, and an IMU with a depth camera. In the third configuration, by embracing the reality that vertical and horizontal planes dominate the indoor environment, an infrared depth camera is employed to determine surface normals and thereby provide attitude aiding. The paper presents a theoretical basis of the aided inertial navigational problems, MATLAB/Simulink-based simulation results, and finally the performance realized from the implementation of the algorithms on a QUANSER QBot 2 mobile robot employing a VectorNav VN-200 IMU and Kinect IR depth camera.