3D pose estimation of ground rigid target based on ladar range image

Abstract

In the target recognition of laser radar (ladar), the accurate estimation of target pose can effectively simplify the recognition process. To achieve 3D pose estimation of rigid objects on the ground and simplify the complexity of the algorithm, a novel pose estimation method is proposed in this paper. In this approach, based on the feature that most rigid objects on the ground have large planar areas which are horizontal on the top of the targets and vertical sides and combined with the 3D geometric characteristics of ladar range images, the planar normals of rigid targets were adopted as the vectors in the positive direction of the axes in the model coordinate system to estimate the 3D pose angles of targets. The simulation experiments were performed with six military vehicle models and the performance in self-occlusion, occlusion, and noise was investigated. The results show that the estimation errors are less than 2° in self-occlusion. For the tank LECRERC model, as long as the upper and side planes of the target are not completely occluded, even though the occlusion reaches 80%, the pose angles can be estimated with the estimation error less than 2.5°. Moreover, the proposed method is robust to noise and effective.

A single-shot pose estimation approach for a 2D laser rangefinder

“…Compared to 2D LRF, 3D LRF (or multi-beam LRF) can generate richer data, which can be easily localized in a reference coordinate system. Many methods have been developed to estimate the pose of a 3D LRF, or the pose of a target from 3D LIDAR data [10,[29][30][31]. For example, Gong et al use an arbitrary trihedron for exterior calibration of a 3D LRF and a camera [30].…”

Parallel vision-based pose estimation for non-cooperative spacecraft

“…Xu et al 11 achieved the target recognition and pose measurement based on the stereovision; the guidance, navigation and control (GNC) of the chaser; and the coordinated plan and control (CP&C) of space robot. According to the most rigid objects' feature on the ground with the mutually perpendicular or nearly perpendicular planar structures, Lv et al 12 adopted the normals of planar areas on the target surface to estimate the 3D pose of the target with ladar range image. Sultan et al 13 proposed a monocular camera vision system for a 6-degree of freedom (DOF) drawing robotic arm to estimate 3D pose of the end effecter robustly.…”

Three-dimensional pose estimation model for object with complex surface

“…Shai Segal et al 1 estimate the relative 3D pose of the cooperative satellites by on-board sensors to be used for the spacecraft formation flying or rendezvous and docking. Dan Lv et al 2 achieve a 3D pose estimation model for the rigid objects on the ground to recognize the military vehicles automatically. Malik Saad Sultan et al 3 propose a monocular camera vision system for a 6-degree-of-freedom (DOF) drawing robotic arm by estimating the 3D pose of the end effecter robustly.…”