Abstract-In this paper we present a state estimation method based on an inertial measurement unit (IMU) and a planar laser range finder suitable for use in real-time on a fixedwing micro air vehicle (MAV). The algorithm is capable of maintaing accurate state estimates during aggressive flight in unstructured 3D environments without the use of an external positioning system. Our localization algorithm is based on an extension of the Gaussian Particle Filter. We partition the state according to measurement independence relationships and then calculate a pseudo-linear update which allows us to use 20x fewer particles than a naive implementation to achieve similar accuracy in the state estimate. We also propose a multi-step forward fitting method to identify the noise parameters of the IMU and compare results with and without accurate position measurements. Our process and measurement models integrate naturally with an exponential coordinates representation of the attitude uncertainty. We demonstrate our algorithms experimentally on a fixed-wing vehicle flying in a challenging indoor environment.
Bry et al. REF presented a state estimation method using an on-board laser range finder and inertial measurement unit and showed aggressive flight in GPS-denied environments.
State estimation for aggressive flight in GPS-denied environments using onboard sensing
2012 IEEE International Conference on Robotics and Automation
2012 IEEE International Conference on Robotics and Automation
Engineering Computer Science