publication . Bachelor thesis . 2016

Integrering av IMU och Velodyne LiDAR i en ICP-SLAM struktur

Zhang, Erik;
Open Access English
  • Published: 01 Jan 2016
  • Publisher: KTH, Optimeringslära och systemteori
  • Country: Sweden
Abstract
Simultaneous localization and mapping (SLAM) of an unknown environment is a critical step for many autonomous processes. For this work, we propose a solution which does not rely on storing descriptors of the environment and performing descriptors filtering. Compared to most SLAM based methods this work with general sparse point clouds with the underlying generalized ICP (GICP) algorithm for point cloud registration. This thesis presents a modified GICP method and an investigation of how and if an IMU can assist the SLAM process by different methods of integrating the IMU measurements. All the data in this thesis have been sampled from a LiDAR scanner mounted on ...
Related Organizations
Download from
38 references, page 1 of 3

1 Introduction 1 1.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1.1 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Related work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2.1 SLAM process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2.2 Point cloud registration . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 Theory 5 2.1 Point Cloud Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Iterative Closest Point . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.2 Generalized ICP . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 The Kalman lter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.1 Correction by IMU observation . . . . . . . . . . . . . . . . . . . 11 2.2.2 Correction by point cloud registration . . . . . . . . . . . . . . . . 12 2.3 Modied GICP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.4 Sequence optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.4.1 Sequence solution method . . . . . . . . . . . . . . . . . . . . . . 17

3 Methods and Implementation 19 3.1 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1.1 3D Scanner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1.2 Forest (Backpack) . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1.3 Urban (Car) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.1.4 Countryside (Aerial) . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.2 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2.1 Test data 1: Forest . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2.2 Test data 2,3: Urban . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2.3 Test data 4: Countryside . . . . . . . . . . . . . . . . . . . . . . . 27 3.3 GICP-SLAM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.2 State estimation and update . . . . . . . . . . . . . . . . . . . . . 29 3.3.3 Point cloud registration . . . . . . . . . . . . . . . . . . . . . . . 29 3.3.4 Sequence optimization . . . . . . . . . . . . . . . . . . . . . . . . 31

[1] Andreas A. Nuchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. 6d slam 3d mapping outdoor environments. Journal of Field Robotics , 24(8-9):699722, 2007.

[2] A. Aditya. Implementation of a 4d fast slam including volumetric sum of the uav. In Sensing Technology (ICST), 2012 Sixth International Conference on , pages 7884. Institute of Electrical & Electronics Engineers (IEEE), Dec 2012.

[3] M Alpen, C Willrodt, K Frick, and J Horn. On-board slam for indoor uav using a laser range nder. In SPIE Defense, Security, and Sensing , pages 769213769213. International Society for Optics and Photonics, 2010. [OpenAIRE]

[4] Paul J Besl and Neil D McKay. Method for registration of 3-d shapes. In Robotics-DL tentative, pages 586606. International Society for Optics and Photonics, 1992.

[5] C. G. BROYDEN. The convergence of a class of double-rank minimization algorithms 1. general considerations. IMA Journal of Applied Mathematics , 6(1):7690, 1970. [OpenAIRE]

[6] M. Bryson and Salah Sukkarieh. Active airborne localisation and exploration in unknown environments using inertial slam. In Aerospace Conference, 2006 IEEE , pages 13 pp., 2006. [OpenAIRE]

[7] F. Caballero, L. Merino, J. Ferruz, and A. Ollero. Vision-based odometry and slam for medium and high altitude ying uavs. Journal of Intelligent and Robotic Systems , 54(1):137161, 2008. [OpenAIRE]

[8] A. Censi. An icp variant using a point-to-line metric. In Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on , pages 1925, May 2008. [OpenAIRE]

[9] G. Conte G. Scaradozzi D. Zanoli S. M. Gambella L. & Marani. Underwater slam with icp localization and neural network objects classication. International Society of Oshore and Polar Engineers. , 2008. [OpenAIRE]

[10] D.W. Eggert, A. Lorusso, and R.B. Fisher. Estimating 3-d rigid body transformations: a comparison of four major algorithms. Machine Vision and Applications , 9(5):272290.

[11] Karl Pearson F.R.S. Liii. on lines and planes of closest t to systems of points in space. Philosophical Magazine Series 6 , 2(11):559572, 1901.

[13] Kyuseo Han, C. Aeschliman, J. Park, A. C. Kak, Hyukseong Kwon, and D. J. Pack. Uav vision: Feature based accurate ground target localization through propagated initializations and interframe homographies. In Robotics and Automation (ICRA), 2012 IEEE International Conference on , pages 944950, May 2012.

38 references, page 1 of 3
Any information missing or wrong?Report an Issue