Color-Based Monocular Visuoinertial 3-D Pose Estimation of a Volant Robot

Abstract

The pose estimation from visual sensors is widely practiced nowadays. The pose vector is estimated by means of homographies and projection geometry. The integration of visual and inertial measurements is getting more attractive due to its robustness and flexibility. The cooperation of visual with inertial sensors for finding a robot's pose bears many advantages, as it exploits their complementary attributes. Most of the visual pose estimation systems identify a geometrically known planar target to extract the pose vector. In this paper, the pose is estimated from a set of colored markers arranged in a known geometry, fused with the measurements of an inertial unit. The utilization of an extended Kalman filter (EKF) compensates the error and fuses the two heterogeneous measurements. The novelty of the proposed system is the use of low-cost colored post-it markers, along with the capability of handling different frames of reference, as the camera and the inertial unit are mounted on different mobile subsystems of a sophisticated volant robotic platform. The proposed system is computationally inexpensive, operates in real time, and exhibits high accuracy.