Multi-camera coverage of deformable contour shapes

Perception of deformation is a key problem when dealing with autonomous manipulation of deformable objects. Particularly, this work is motivated by tasks where the manipulated object follows a prescribed known deformation with the goal of performing a desired coverage of the object’s contour along its deformation. The main contribution is a simple yet effective novel perception system in which a team of robots equipped with limited field-of-view cameras covers the object’s contour according to a prescribed visibility objective. In order to define a feasible visibility objective, we propose a new method for obtaining the maximum achievable visibility of a contour from a circumference around its centroid. Then, we define a constrained optimization problem and we solve it iteratively to compute the minimum number of cameras and their nearoptimal positions around the object that guarantee the visibility objective, over the entire deformation process.

[1]  Karl Henrik Johansson,et al.  Cooperative coverage for surveillance of 3D structures , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[2]  Wei Lin,et al.  Model-based coverage motion planning for industrial 3D shape inspection applications , 2017, 2017 13th IEEE Conference on Automation Science and Engineering (CASE).

[3]  Xin-Ping Guan,et al.  Model-based active viewpoint transfer for purposive perception , 2017, 2017 13th IEEE Conference on Automation Science and Engineering (CASE).

[4]  Mac Schwager,et al.  Eyes in the Sky: Decentralized Control for the Deployment of Robotic Camera Networks , 2011, Proceedings of the IEEE.

[5]  Gershon Elber,et al.  Geometric multi-covering , 2014, Comput. Graph..

[6]  Gonzalo López-Nicolás,et al.  Formation of differential-drive vehicles with field-of-view constraints for enclosing a moving target , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[7]  Belhassen-Chedli Bouzgarrou,et al.  Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey , 2018, Int. J. Robotics Res..

[8]  Min Liu,et al.  On minimal orthographic view covers for polyhedra , 2009, 2009 IEEE International Conference on Shape Modeling and Applications.

[9]  Beno Benhabib,et al.  Multi-Camera Active-Vision for Markerless Shape Recovery of Unknown Deforming Objects , 2018, J. Intell. Robotic Syst..

[10]  Beno Benhabib,et al.  A Multi-Camera Active-Vision System for Deformable-Object-Motion Capture , 2014, J. Intell. Robotic Syst..

[11]  Christian Gagné,et al.  Multisensor placement in 3D environments via visibility estimation and derivative-free optimization , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[12]  Charles Audet,et al.  Analysis of Generalized Pattern Searches , 2000, SIAM J. Optim..

[13]  Krishnanand N. Kaipa,et al.  Robotic bimanual cleaning of deformable objects with online learning of part and tool models , 2016, 2016 IEEE International Conference on Automation Science and Engineering (CASE).

[14]  Ulrich Eckhardt,et al.  Shape descriptors for non-rigid shapes with a single closed contour , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[15]  Davide Scaramuzza,et al.  A comparison of volumetric information gain metrics for active 3D object reconstruction , 2018, Auton. Robots.

[16]  Yunhui Liu,et al.  Automatic 3-D Manipulation of Soft Objects by Robotic Arms With an Adaptive Deformation Model , 2016, IEEE Transactions on Robotics.

[17]  Gonzalo López-Nicolás,et al.  Three-dimensional multirobot formation control for target enclosing , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.