Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Shape registration using optimization for mobile robot navigation
Shape registration using optimization for mobile robot navigation
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
A Robotic Excavator for Autonomous Truck Loading
Autonomous Robots
Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans
Journal of Intelligent and Robotic Systems
Pair-wise range image registration: a study in outlier classification
Computer Vision and Image Understanding - Registration and fusion of range images
A review of recent range image registration methods with accuracy evaluation
Image and Vision Computing
Video Tracking Using Improved Chamfer Matching and Particle Filter
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 03
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Parametric correspondence and chamfer matching: two new techniques for image matching
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Shape context and chamfer matching in cluttered scenes
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Manipulator and object tracking for in-hand 3D object modeling
International Journal of Robotics Research
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A survey of mining accidents has revealed that over 30% of all truck loading accidents can be addressed by providing dipper positioning feedback to the shovel operator. In this paper, a novel approach is presented for estimating a mining shovelâ聙聶s dipper pose to obtain its arm geometry in real-time utilizing a two-dimensional laser scanner. The low spatial resolution of laser scanners and the need for accurate initialization challenge the reliability and accuracy of most laser-scanner-based object tracking methods. This work addresses these issues by using the shovel dipperâ聙聶s kinematics model and position history, in conjunction with the dipper geometrical model, to track the dipper in space. The proposed method uses a bootstrap particle filter with a distance transformation in order to perform a global search in the workspace. The particle filterâ聙聶s result is then used as the initial pose for an Iterative Closest Point algorithm that increases the accuracy of the pose estimate. The proposed method can be applied to other laser scanner-based object tracking applications in outdoor environments. Experiments performed on a mining shovel demonstrate the reliability, accuracy, and computational efficiency of the proposed approach. Moreover, using a single proximal sensor can simplify mounting, reduce maintenance costs and machine down time, and enhance tracking reliability.