Tight Coupling of Laser Scanner and Inertial Measurements for a Fully Autonomous Relative Navigation Solution

Abstract

The paper describes a fully autonomous relative navigation solution for urban environments (indoor and outdoor). The navigation solution is derived by combining measurements from a two‐dimensional (2D) laser scanner with measurements from inertial sensors. This derivation relies on the availability of structures (lines and surfaces) within the scan range (80 m depth, typically). Navigation herein is performed in completely unknown environments. No map information is assumed to be available a priori. Indoor and outdoor live data test results are used to demonstrate performance characteristics of the laser/inertial integrated navigation. Relative positioning at the cm‐level is demonstrated for indoor scenarios where well‐defined features and good feature geometry are available. Test data from challenging urban environments show position errors at the meter‐level after approximately 200 m of travel (between 0.6% and 0.8% of distance traveled).

Tightly-Integrated LADAR/INS Algorithm Development to Support Urban Operations

“…Pi-Poj-Di (1) Note that from equation (1) one could also derive an expression for the normal point on planar surface P, :…”

“…The problem of estimating the attitude change of the camera platform is now equivalent to the problem of finding the matrix C^*, 1 ' that maximizes the dot product of the left and right hand sides of equation (7), or…”

“…In the final report of last year as well as reference [18], INS data are exploited to match lines extracted from 2D LADAR images for a 2D navigation case. In order to use INS data for plane matching, line-matching algorithms developed in [18] must be extended for a 3D case.…”

“…In order to use INS data for plane matching, line-matching algorithms developed in [18] must be extended for a 3D case. Hence, the feature matching procedure has to use position and orientation outputs of the INS to predict plane location and orientation in the current scan based on plane parameters observed in previous scans.…”

Seamless Indoor-Outdoor Navigation for Unmanned Multi-Sensor Aerial Platforms

“…GPS provides measurements suited for estimation of the position and the IMU provide measurements that can be used to estimate all 6 unknowns. Two-dimensional (2D) laser scanners have been used extensively in robotics to estimate the 3 degrees-of-freedom (3DOF), , in 2D navigation; for example, [5] and [6] describe methods that extract features such as line segments and points from the laser scans and use these features to estimate the position and heading of the robot or aid an inertial navigator. Alternatively, a large amount research papers have addressed laser scanner-based 3DOF Simultaneous Localisation And Mapping (SLAM) methods such as the grid-based SLAM method described in [7] or methods that use some form of scan-matching such as the Iterative Closest Point (ICP) approach [8].…”