Potential of Time-of-Flight Range Imaging for Object Identification and Manipulation in Construction

AbstractIn this paper, we examine the potential of a range camera in construction material sorting applications. By utilizing the depth information from a time-of-flight (TOF) camera, we identify and classify objects placed on a conveyor belt. The motivation stems from the fact that object manipulation and identification are two primary problems associated with automated handling and sorting of material objects moving on a conveyor belt. Such a problem may arise in the construction industry for handling objects such as formwork when it is returned to the distribution facility. We present algorithms and experimental results using the depth information from a TOF range camera for two distinct tasks: (1) object attribute measurement and (2) object identification. Experiments and results for both tasks indicate a potential benefit for the use of TOF range cameras in construction automation and robotic arm tasks as they relate, for example, to sorting applications in the construction-formwork business.

[1]  Dejan Pangercic,et al.  Real-time CAD model matching for mobile manipulation and grasping , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[2]  Frédéric Bosché,et al.  Rapid human-assisted, obstacle avoidance system using sparse range point clouds , 2004 .

[3]  Hulya Yalcin,et al.  Visual processing and classification of items on a moving conveyor: a selective perception approach , 2002 .

[4]  Jochen Teizer,et al.  Range Imaging as Emerging Optical Three-Dimension Measurement Technology , 2007 .

[5]  R. Mattone,et al.  Sorting of items on a moving conveyor belt. Part 1: a technique for detecting and classifying objects , 2000 .

[6]  Rasmus Larsen,et al.  Cluster tracking with Time-of-Flight cameras , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[7]  Mohamed A. Khabou,et al.  Shape recognition using eigenvalues of the Dirichlet Laplacian , 2007, Pattern Recognit..

[8]  R. Lange,et al.  Solid-state time-of-flight range camera , 2001 .

[9]  Nico Blodow,et al.  Persistent Point Feature Histograms for 3D Point Clouds , 2008 .

[10]  Luigi di Stefano,et al.  People Tracking Using a Time-of-Flight Depth Sensor , 2006, 2006 IEEE International Conference on Video and Signal Based Surveillance.

[11]  Thomas B. Moeslund,et al.  Fusion of range and intensity information for view invariant gesture recognition , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[12]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Jochen Teizer,et al.  Human Motion Analysis Using 3D Range Imaging Technology , 2009 .

[14]  Manolis I. A. Lourakis,et al.  Toward automated generation of parametric BIMs based on hybrid video and laser scanning data , 2010, Adv. Eng. Informatics.

[15]  Sonia Chernova,et al.  Mobile human-robot teaming with environmental tolerance , 2009, 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  Jitendra Malik,et al.  Recognizing Objects in Range Data Using Regional Point Descriptors , 2004, ECCV.

[17]  Mehmet Ölmez,et al.  An automated industrial conveyor belt system using image processing and hierarchical clustering for classifying marble slabs , 2011 .

[18]  Seokho Chi,et al.  Object identification based on 3D spatial models of construction sites , 2007 .

[19]  Behzad Dariush,et al.  Controlled human pose estimation from depth image streams , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[20]  Hyojoo Son,et al.  Rapid 3D object detection and modeling using range data from 3D range imaging camera for heavy equipment operation , 2010 .

[21]  Niklas Peinecke,et al.  Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids , 2006, Comput. Aided Des..

[22]  Mohammed Bennamoun,et al.  Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  R. Mattone,et al.  Sorting of items on a moving conveyor belt. Part 2: performance evaluation and optimization of pick-and-place operations , 2000 .

[24]  Hyojoo Son,et al.  Rapid 3D Object Modeling Using 3D Data from Flash LADAR for Automated Construction Equipment Operations , 2009 .

[25]  Alexander M. Bronstein,et al.  Three-Dimensional Face Recognition , 2005, International Journal of Computer Vision.

[26]  Igor Guskov,et al.  3D object recognition from range images using pyramid matching , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[27]  Carlos H. Caldas,et al.  Real-Time Three-Dimensional Occupancy Grid Modeling for the Detection and Tracking of Construction Resources , 2007 .