Automatic large-scale three dimensional modeling using cooperative multiple robots

A robotic 3D scanning system using multiple robots named CPS-SLAM is presented.An automatic planning technique for a laser measurement by using CPS-SLAM is proposed.The validity is verified through simulations and experiments by two types of CPS-SLAMs. 3D modeling of real objects by a 3D laser scanner has become popular in many applications, such as reverse engineering of petrochemical plants, civil engineering and construction, and digital preservation of cultural properties. Despite the development of lightweight and high-speed laser scanners, the complicated measurement procedure and long measurement time are still heavy burdens for widespread use of laser scanning. To solve these problems, a robotic 3D scanning system using multiple robots has been proposed. This system, named CPS-SLAM, consists of a parent robot with a 3D laser scanner and child robots with target markers. A large-scale 3D model is acquired by an on-board 3D laser scanner on the parent robot from several positions determined precisely by a localization technique, named the Cooperative Positioning System (CPS), that uses multiple robots. Therefore, this system can build a 3D model without complicated post-processing procedures such as ICP. In addition, this system is an open-loop SLAM system and a very precise 3D model can be obtained without closed loops. This paper proposes an automatic planning technique for a laser measurement by using CPS-SLAM. Planning a proper scanning strategy depending on a target structure makes it possible to perform laser scanning efficiently and accurately even for a large-scale and complex environment. The proposed technique plans an efficient scanning strategy automatically by taking account of several criteria, such as visibility between robots, error accumulation, and efficient traveling. We conducted computer simulations and outdoor experiments to verify the performance of the proposed technique.

[1]  Wolfram Burgard,et al.  Exploration with active loop-closing for FastSLAM , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[2]  Yoonseok Pyo,et al.  High-precision three-dimensional laser measurement system by cooperative multiple mobile robots , 2012, 2012 IEEE/SICE International Symposium on System Integration (SII).

[3]  Shengyong Chen,et al.  Vision sensor planning for 3-D model acquisition , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[4]  Brian Yamauchi,et al.  A frontier-based approach for autonomous exploration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[5]  Jingjing Du,et al.  An application of Kullback-Leibler divergence to active SLAM and exploration with Particle Filters , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Tanneguy Redarce,et al.  CAD-based range sensor placement for optimum 3D data acquisition , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[7]  M. Milanova,et al.  Active perception system for recognition of 3D objects in image sequences , 1998, AMC'98 - Coimbra. 1998 5th International Workshop on Advanced Motion Control. Proceedings (Cat. No.98TH8354).

[8]  Ryo Kurazume,et al.  Cooperative positioning with multiple robots , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[9]  Ryo Kurazume,et al.  Laser-based geometric modeling using cooperative multiple mobile robots , 2009, 2009 IEEE International Conference on Robotics and Automation.

[10]  Dimitri Papadopoulos-Orfanos,et al.  Automatic 3-D digitization using a laser rangefinder with a small field of view , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[11]  Hongbin Zha,et al.  Active modeling of 3-D objects: planning on the next best pose (NBP) for acquiring range images , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[12]  Y.F. Li,et al.  Automatic sensor placement for model-based robot vision , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Yunfeng Zhang,et al.  Mission planning of autonomous UAVs for urban surveillance with evolutionary algorithms , 2013, 2013 10th IEEE International Conference on Control and Automation (ICCA).

[14]  Konstantinos A. Tarabanis,et al.  A survey of sensor planning in computer vision , 1995, IEEE Trans. Robotics Autom..

[15]  Franz Aurenhammer,et al.  Voronoi diagrams—a survey of a fundamental geometric data structure , 1991, CSUR.

[16]  R. Bajcsy Active perception , 1988 .

[17]  Petter Ögren,et al.  Optimal positioning of surveillance UGVs , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Ioannis Stamos,et al.  Interactive sensor planning , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[19]  Y. Aloimonos Active Perception , 1993 .

[20]  Ryo Kurazume,et al.  Automatic Planning of Laser Measurements for a Large-scale Environment using CPS-SLAM System , 2015 .

[21]  Yasir Latif,et al.  On the monotonicity of optimality criteria during exploration in active SLAM , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[22]  Gamini Dissanayake,et al.  Active SLAM using Model Predictive Control and Attractor based Exploration , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Simon Lacroix,et al.  Multi-robot target detection and tracking: taxonomy and survey , 2016, Auton. Robots.

[24]  Anil K. Jain,et al.  A Survey of Automated Visual Inspection , 1995, Comput. Vis. Image Underst..

[25]  Haluk Topcuoglu,et al.  Positioning and Utilizing Sensors on a 3-D Terrain Part I—Theory and Modeling , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[26]  Robert Sim Stable Exploration for Bearings-only SLAM , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[27]  Xiang Chen,et al.  Modeling Coverage in Camera Networks: A Survey , 2012, International Journal of Computer Vision.

[28]  Pratap Tokekar,et al.  Polygon guarding with orientation , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[29]  J. O'Rourke Art gallery theorems and algorithms , 1987 .

[30]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[31]  Éric Marchand,et al.  Active sensor placement for complete scene reconstruction and exploration , 1997, Proceedings of International Conference on Robotics and Automation.

[32]  Ryo Kurazume,et al.  Study on Cooperative Positioning System , 1996 .

[33]  Ryo Kurazume,et al.  Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots , 2012, Auton. Robots.

[34]  George J. Pappas,et al.  Decentralized active information acquisition: Theory and application to multi-robot SLAM , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[35]  A. Aggarwal The art gallery theorem: its variations, applications and algorithmic aspects , 1984 .

[36]  Kurt Konolige,et al.  Distributed Multirobot Exploration and Mapping , 2005, Proceedings of the IEEE.

[37]  Youfu Li,et al.  Information entropy-based viewpoint planning for 3-D object reconstruction , 2005, IEEE Transactions on Robotics.

[38]  W.R. Scott,et al.  View planning with a registration constraint , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.